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Maintenance policy selection in manufacturing firms using the fuzzy MCDM approach
International Journal of Production Research
Abstract
In manufacturing firms, there is a critical need for proper maintenance of manufacturing facilities. The maintenance process enhances customer satisfaction and reliability of the products, and increases the profit of the manufacturer. Therefore, a proper maintenance policy selection is a critical issue for manufacturers, as an inefficient maintenance policy affects not only the direct cost of the firm but also the other aspects. In the present study, maintenance policy selection at the level of the firm rather than the equipment level is shown, and for selection various criteria have been identified. The presented work not only provides the best alternatives but also provides an alternative ranking, which facilitates decision-makers in choosing alternatives according to their constraints. These selection criteria are different in nature, as some give a crisp value, whereas others are defined in linguistic terms. To select the appropriate maintenance policy, a distance-based fuzzy multicriteria decision-making (MCDM) approach has been employed. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The MCDM approach is efficient in incorporating data, in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. A comprehensive example illustrates the application of the distance-based fuzzy MCDM approach.
... The most widely used possible alternatives are analyzed as TBPM [2,8], CM [3], CBM [9,10], PdM [11], Total Productive Maintenance (TPM) [12,13], OM [2], RCM [8,14,15], Shutdown Maintenance (SM) [16], Revision Maintenance (RM) [17], Total Quality Maintenance (TQMain) [8,12], and breakdown maintenance (BM) [18], respectively. In the literature, the choice of maintenance policy is applied in a wide variety of sectors such as the automotive [19], chemical production [20,21], textile [22,23], energy [2,13], manufacturing industry [11,24,25], and transportation [1] sectors. ...
... The most widely used possible alternatives are analyzed as TBPM [2,8], CM [3], CBM [9,10], PdM [11], Total Productive Maintenance (TPM) [12,13], OM [2], RCM [8,14,15], Shutdown Maintenance (SM) [16], Revision Maintenance (RM) [17], Total Quality Maintenance (TQMain) [8,12], and breakdown maintenance (BM) [18], respectively. In the literature, the choice of maintenance policy is applied in a wide variety of sectors such as the automotive [19], chemical production [20,21], textile [22,23], energy [2,13], manufacturing industry [11,24,25], and transportation [1] sectors. ...
... After the aggregated pairwise comparison matrices are obtained, criteria weights are calculated using Eqs. (12)(13)(14)(15)(16)(17)(18). The global and local priorities of the main and sub-criteria obtained are presented in Fig. 4. ...
The key to achieving the safety and reliability of the production system is to implement an efficient maintenance management system to reduce or eliminate equipment failures. Maintenance planning costs constitute a large part of operating costs. Determining the optimal maintenance policy plays a significant role in improving system reliability and availability as well as providing cost-savings. For this reason, it is necessary to determine and implement the most appropriate maintenance planning for the production system to ensure the reliable, smooth, and healthy operation of the system. The decision-making process is multidimensional and complicated due to the nature of the maintenace policy selection problem, so it involves various conflicting evaluation criteria in identifying the optimal maintenance policies. Multi-criteria decision-making (MCDM) instruments are appropriate for such complex issues. In this study, a hybrid-two-stage-MCDM-approach consisting of Pythagorean fuzzy Analytical Hierarchical Process (PF-AHP) and Pythagorean fuzzy TOPSIS (PF-TOPSIS) are carried out to determine the best maintenance policy, which is one of the most serious issues, both tactically and operationally, handled by one of the largest food companies in Turkey. Five main evaluation criteria (reliability, safety, cost, added-value, and feasibility), and six alternative possible maintenance policies (reliability-centered, predictive, time-based preventive, condition-based, opportunistic, and corrective maintenance) are considered to specify the optimal maintenance strategies. As a result of the application, the most appropriate maintenance strategy was emerged as reliability-centered maintenance (RCM). Other alternatives were appeared as predictive (PdM), time-based preventive (TBPM), condition-based (CBM), opportunistic (OM), and corrective maintenance (CM). The validation of the method was performed using the PF-VIKOR technique as a comparative study. In the final stage of the study, a sensitivity analysis based on criteria weights was conducted to test the robustness of the proposed integrated methodology.
... Chan and Prakash [41] employed fuzzy TOPSIS in deciding on the appropriate maintenance candidate from a monetary gure of legitimacy. Besides the mix of di erent methods and tools with AHP, other combined works done by Al-Najjar and Alsyouf [7], Jafari et al. [42], and Li et al. [43] exist. ...
... Notably, exibility, fault tolerance, redundancy, and awareness are introduced as important factors of RE [72{75]. Brief explanations of all these main criteria based on safety and risk concepts are provided as follows (e.g., [41,46]): ...
... The standard deviation measure could push specialists to e ortlessly choose the best maintenance policy among the various up-and-comers in an uncertain situation. In doing so, the proposed IVFdecision-making model with PSCs and Monte Carlo simulation has a better quality deviation with respect to four di erent maintenance policies than two decision methods: the fuzzy distance-based method of Chan and Prakash [41] and IVF-SAW method of Chen [76]. ...
... Properly performed maintenance can contribute to gaining a competitive advantage. The maintenance process enhances customer satisfaction (Chan, Prakash, 2012), that is often directly dependent on the reliability, flexibility and speed of suppliers (Branska et al., 2016). ...
... Increasing satisfaction through better products or services is accepted as an essential step leading to customers' repurchase intentions and/or reducing switching intensions (Park, Jang 2014). This is essential for increasing the profit of the manufacturer (Chan, Prakash, 2012). ...
... Maintenance is a business function that serves and supports the primary process in an organisation (Chan, Prakash, 2012). According to ČSN EN 13306 (2010), maintenance can be defined as "a combination of technical, administrative and managerial measures during the life cycle of the object, focusing on its maintenance in the state or its return to the state in which it can perform the desired function". ...
The aim of this article is to use the results of the qualitative research to describe the current form of maintenance systems used in enterprises of chemical and food industries, and then to discuss and generalize the results. The main objective of the research in individual companies was to determine how they perform the strategic and tactical operational planning of maintenance, implementation of these plans and their control. Qualitative primary research has shown that production equipment maintenance systems are irreplaceable in chemical and food industry enterprises, but there is great potential for improvement. Improvement should be focused on the area of strategic as well as tactical and operational planning of production equipment maintenance. In terms of strategy, the biggest opportunity for a dramatic improvement is the implementation of modern maintenance methods. In the context of the existing systems, improvement can be achieved especially in setting strategic objectives, the system of indicators to measure the performance of maintenance and in implementing an information system. In the tactical and operational level, it would be useful to develop a maintenance planning system linked with suppliers and customers and utilize mathematical methods and models to optimize plans for this business activity.
... Karmakar et al [20] developed a deteriorating EOQ model for natural idle time and imprecise demand under Hesitant fuzzy environment. Chan and Prakash [21] used the fuzzy multi-criteria decision-making (MCDM) approach for maintenance policy selection in manufacturing firms. De and Nandi [22] invented the exact defuzzification method based on polynomial approximation of various fuzzy sets. ...
The modern global economy is becoming more challenging and it is hardly possible to minimize the inventory cost for inventory practitioners in the coming days. Basically, most of the enterprises deal with deteriorating items having flexible demand rate and follow natural idle time in the entire inventory process. Moreover, traditionally most of the research articles have been made under non-stop time frame, but in reality, in a day-night scenario there exists a natural idle time and hence the time consumed for inventory run time may be viewed as single shift or periodic model. Here we formulate an economic order quantity (EOQ) inventory model considering natural idle time and deterioration under some constraints and minimize the average inventory cost. Then, the model is converted into an equivalent fuzzy model, taking the demand and all the cost parameters as linguistic polynomial fuzzy set (LPFS). To defuzzify the model, we have adopted indexing method as well as a-cut method. To validate the novelty, numerical experimentations have also been analyzed with the help of metaheuristic and evolutionary algorithms like goat search algorithm (GSA) and particle swarm optimization (PSO). Comparative analysis reveals that GSA approach can give finer optimum (-10 % cost reduction) than other approaches. The main findings of this research give a new technique of (linguistic term) fuzzification-defuzzification of the proposed model and a new solution procedure to optimize the periodic deteriorating inventory model under GSA. To justify this model, sensitivity analysis and graphical illustration have been done. Scopes of future work have been discussed for further improvement of research on optimization problems using metaheuristic algorithms.
... They exploited the algebraic structure of fuzzy graphs for modeling value-related requirement dependencies and their strengths. Chan and Prakash [5] proposed a maintenance policy selection model at the level of the firm rather than the equipment level. Some selection criteria were crisp values, whereas others were obtained in linguistic terms. ...
Triangular fuzzy numbers (TFNs) are widely used for selection problems to determine expert opinions using linguistic expressions. Some aggregation procedures are developed to determine expert opinions more accurately. However, there is a need for a simple and more useful procedure to solve the selection problems more suitably. For this purpose, our study offers a triangular, exparabolic, and parabolic area calculation-based approximation approach for TFNs to aggregate the possible hedges (very and more or less) for TFNs. Hence, this aggregation procedure provides a tuning opportunity for classical TFN expressions to capture possible tuning processes to reflect the hesitancies of experts. The technique for order preferences by similarity to ideal solution (TOPSIS) method is applied in the two studies from extant literature, and suitable alternatives are determined as a result of the ranking process. Finally, a comparative analysis is presented to illustrate the efficiency of the proposed procedure. The conventional TOPSIS model’s ranking scores are very close for exemplified examples (i.e., 0.5308, 0.4510, 0.4550 and 0.5304, 0.4626, 0.4940), but the proposed model’s result has fluctuated for the same examples (i.e., 0.346, 0,669, 0,567 and 0.208, 0.991, 0.148). So, the main advantage of the proposed aggregation procedure is the alternative ranking scores separation capability analyzed with their linguistic diversification.
... In the MCDM method, using the opinion of experts, the weight of the options in the study is evaluated and ranked and helps solve problems in organisations (Erdoğan et al., 2019). The MCDM has been utilised in different fields, such as risk visualisation (Kimiagari and Keivanpour, 2018), strategic management (KianiMavi et al., 2019), maintenance policy selection (Chan and Prakash, 2012), green manufacturing practices (Govindan et al., 2015), green suppliers (Tsui et al., 2015), quality function deployment (Wu et al., 2017), outsourcing adoption (Yadav et al., 2018), creative tourism (KianiMavi et al., 2020). The step-by-step weight ratio analysis (SWARA) is one of the new MCDM methods that are much simpler than other existing methods. ...
This study aims to evaluate and prioritise the decision-making factors in construction project management to select the best constructor. The step-by-step weight ratio analysis (SWARA) method was used to prioritise the decision-making factors of construction project management to select the best contractors in Rasht City Municipality, Iran. Ten experts participated in this research to make decisions with the SWARA, and data were collected in 2022. Results show that the most significant sub-criteria among 28 sub-criteria of decision making in construction project management is the experience of the manager, and the least sub-criteria is resource planning. The present study helps construction managers to enhance their knowledge and have the best performance to choose the best contractor for construction projects and improve their weaknesses by influencing factors. Also, managers can significantly enhance the success of construction projects by focusing on the most significant decision-making factors.
... The multi-criterion-based model for selecting maintenance strategies can be divided into two types. The first types is the single MCDM method, which mainly includes AHP (Wang et al. 2007;Tan et al. 2011;Goossens and Basten 2015;Meshram et al. 2019;Gholami et al. 2022), ANP (Sadeghi and Manesh 2012;Hemmati et al. 2018;Carpitella et al. 2021;Hayati and Abdollahzadeh 2021;Jamali et al. 2021;Gholami et al. 2022), TOPSIS (Shyjith et al. 2008;Chan and Prakash 2012;Ding et al. 2014a, b), VIKOR (Vahdani et al. 2010), ELECTRE (Vahdani and Hadipour 2011), etc. The second type is hybrid MCDM method, which includes AHP-TOPSIS (Kirubakaran and Ilangkumaran 2016;Özcan et al. 2017;Karatuğ et al. 2022;Mathew et al. 2022;Gedikli and Ervural 2023), AHP-PROMETHRE (Emovon et al. 2018;Animah and Shafiee 2021), BWM-TOPSIS (Avakh Darestani et al. 2022), DEMATEL-ANP (Aghaee and Fazli 2012;Arjomandi et al. 2021), etc. ...
Maintenance strategy selection is an important step in maintenance management, which is the basis for implementing maintenance optimization and formulating specific maintenance schemes. This paper takes the meta-action unit (MU) as the research object, considers the randomness and fuzziness of expert evaluation and the interaction between evaluation criteria in the selection process of maintenance strategy, and proposes a maintenance strategy selection method based on cloud DEMATEL-ANP. Firstly, DEMATEL based on cloud model is used to establish the interaction model between the main criteria, determine the weighted cloud weight of the super matrix and the inner dependencies of the sub-criteria under the same main criteria. Then, the cloud-ANP model is used to determine the outer dependencies relationship and construct the cloud super matrix, so as to obtain the cloud weight of each evaluation criteria in maintenance strategy selection. By using the subjective and objective weighting method, the evaluation of different experts on different maintenance strategy criteria is integrated, and the priority of alternative maintenance strategies of MU is obtained. Finally, different methods are used to sort and compare the alternative maintenance strategies of the rotating body rotation MU of the CNC turntable, which verifies the scientificity and effectiveness of the maintenance strategy selection method based on cloud DEMATEL-ANP are verified.
... It was applied to select the optimal maintenance plan for military equipment [94], manufacturing plants [70] and aeronautical systems [161]. In [113] and [72], a FL/TOPSIS-based approach was proposed to deal with the selection of the most suitable maintenance strategy. ELECTRE is based on the concept of outranking relations between alternatives [208]. ...
This work reviews maintenance optimization from different and complementary points of view. Specifically, we systematically analyze the knowledge, information and data that can be exploited for maintenance optimization within the Industry 4.0 paradigm. Then, the possible objectives of the optimization are critically discussed, together with the maintenance features to be optimized, such as maintenance periods and degradation thresholds. The main challenges and trends of maintenance optimization are, then, highlighted and the need is identified for methods that do not require a-priori selection of a predefined maintenance strategy, are able to deal with large amounts of heterogeneous data collected from different sources, can properly treat all the uncertainties affecting the behavior of the systems and the environment, and can jointly consider multiple optimization objectives, including the emerging ones related to sustainability and resilience.
... Then each linguistic variable is corresponded to a fuzzy number defined by its membership function like those presented in Fig. 2, where a the fuzzy performance x ij = (l ij , m ij , u ij ) of each alternative i to the j th criterion is obtained using a three-level scale of Triangular Fuzzy Number TFN j = (tf 1j , tf 2j , tf 3j ) = (x 1j ,x 2j ,x 3j ) . In case where different fuzzy scales are selected among the analysis criteria scale-free attributes are obtained via fuzzy normalization using Eqs. 4 and 5 for ascend and descend criteria respectively (Chan and Prakash 2012). As a result, the anti-ideal and the ideal solution are formed by the zero and the unit vector respectively (Eqs. ...
Renewable-energy sector and especially wind energy exploitation gained a lot of attention during the last decades. However renewable sector investments' selection is constrained by a variety of spatially and non-spatially related factors. Moreover, citizens' susceptibility often resulted to call of promising investment plans, which were considered to be contradictory in terms of environmental and development aspects. Thus decision frameworks are needed to ensure transparency and consistency to the decision-making process. Such frameworks must consider multiple stakeholders’ opinions and preferences associated with both financial and sustainability issues capable of dealing with uncertainties derived from the inherent ambiguity related to the analysis data that estimated future conditions and Decision Makers' knowledge and preferences. The current research paper presents such a framework that combines a fuzzy extension of TOPSIS method and Monte Carlo Simulation to analyze the robustness of the selected solution avoiding average operator performance used in Group Decision-Making processes, which results to loss of information. The framework uses linguistic variables to estimate criterion weights and to rate alternatives provided by the decision makers. Then, Monte Carlo Simulation applied to the linguistic terms of the model, based on the distributions produced according to decision maker's preferences. The framework is implemented in a case study for the evaluation and selection of a wind-energy investment in Rhodope region range in Greece.
... Industrial¯rms are realising that there is a critical need for proper maintenance of production facilities and systems [Meulen et al. (2008); Chan and Prakash (2012)]. ...
Abstract and figures
In food manufacturing, maintenance of manufacturing equipment is one of the most important essentials for an efficient manufacturing as this sector continuously face challenges that makes maintenance very critical due to the nature of manufacturing, thus as a result food manufacturing companies must add or modify their maintenance strategies in order to keep production running efficiently. The aim of this study is to carry out a maintenance performance evaluation and downtime analysis in a food manufacturing company and suggest areas for further improvement. In this study, an empirical case study was carried out in order to evaluate the maintenance performance and downtime analysis. Overall equipment effectiveness and Pareto analysis were used to carry out a maintenance performance evaluation and downtime analysis on the manufacturing equipment using three years historical data obtained from the food manufacturing company as an industrial case study. The study found that the average overall equipment effectiveness is 55.30% which is a low value when compared with Overall Equipment Effectiveness world standards, meaning that the manufacturing organization is operating in an average condition and there is a required urgent improvement of maintenance policies and strategies, otherwise it will be difficult for the manufacturing organization to sustain it. Thus it is necessary that in order to improve productivity, the manufacturing organization under study should look into its manufacturing strategies so that urgent improvement of maintenance policies and strategies can be implemented and adopted.
... A simulation-based optimization was finally conducted and prioritized for cost reduction with adjustable users' preference model. Chan and Prakash [39] employed a distance-based fuzzy multicriteria decision-making (MCDM) approach for selecting appropriate maintenance policy and provided means for integrating the economic figure of merit with strategic performance variables. They found that the MCDM approach was efficient in incorporating data in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. ...
A knowledge-based framework that exploits fuzzy logic to generate precise cost implication decisions from an optimal maintenance and replacement schedule is proposed. Using data from a locally fabricated 8HP-PML Gold engine cassava grinding machine whose failure distribution follows the Weibull distribution function with shape and scale parameters α=1.30 and β =1386, respectively; and cost input parameters namely, the cost of preventive maintenance (C p), cost of replacement maintenance (C r), and cost of minimal repair (C m), an analytical model was constructed to generate the corresponding optimal cost ratios (C r ⁄C p and C m ⁄C p), useful for deriving the required universe of discourse and membership functions for the respective linguistic variables or cost parameters ranges. Extensive simulation using MATLAB 2017a revealed three types of system performance demonstrating the effects of costs interaction on varying costs implication decisions. Results of simulation indicate that the machine functions optimally at all low costs (i.e., when C p , C r , and C m are 'low') and maintains delayed replacement frequencies but the machine becomes expensive to maintain when C p , and C m increases above acceptable thresholds (i.e., are either 'high' or 'v.high'). The scientific implication is that the proposed system efficiently models interaction between input parameters and can effectively guide operators/designers' decisions on the choice to weigh varying cost implication decisions of PM and replacement schedules for mechanically repairable systems whose failure rate may be characterized by other failure distribution functions.
... In many decision problems, the evaluation of alternatives is complicated by their performance in at least some attributes that are not known with certainty [48]. Regarding this uncertainty during decision-making, the fuzzy theory is combined with the main MCDM methods to solve this problem [63]. In other words, fuzzy decision-making is used where vague and incomplete data exist for the solution [64,65]. ...
The current global competitive scenario and the increase in complexity and automation of equipment and systems demand better results from maintenance management in organizations. As maintenance resources are limited, prioritizing maintenance activities is essential to allocate them properly and to meet maintenance management objectives. In the face of these challenges, multicriteria decision-making (MCDM) methods are commonly used in organizations to support decision-making. Nevertheless, selecting a suitable MCDM method for maintenance planning can be complicated given the diversity of methods and their strengths and weaknesses. In this context, this paper proposes a novel knowledge-based method for deciding a multicriteria decision-making (MCDM) method to prioritize maintenance work orders of hydroelectric plants. As the main novel contribution, it translates the intrinsic characteristics of the main MCDM methods into questions related to maintenance planning to guide the recommendation of a suitable MCDM method for organizations through a decision tree diagram. This approach was applied to a maintenance case study of a hydroelectric power plant in order to demonstrate its use and contribute to its understanding. These findings contribute to maintenance management in selecting an MCDM method aligned with the context of its maintenance planning for the prioritization of maintenance work orders.
... Selection criteria can be defined as the characteristics, skills, and abilities of a policy that can effectively perform a given task. ey are used to identify the right strategy [27]. Different categories of PM criteria are provided [11,28,29]. ...
The main purpose of this study is to present a new hybrid approach to select the appropriate maintenance policy (NET) of machines utilizing analytic network process (ANP), computer simulation, and the concept of virtual cellular manufacturing system (VCMS). Since conventional methods select only one NET policy for all machines or production lines, the performance of machines that do not conform to the selected policy is reduced. In the proposed method, the information of the functional parameters of the machines is extracted by means of computer simulation and there is no need for expert opinion. Next, the appropriate net policy for each machine is selected using the ANP method. To reduce the diversity and complexity of NET applications, machines are grouped using the concept of virtual cellular manufacturing system based on the similarity of NET policies. A NET program is prepared for each group of machines. The proposed approach is used in a production unit with three widely used NET policies, and its efficiency was proved by comparing the results with conventional methods.
... The decision-making criteria were same as those considered in Wang et al. 16 The results showed that RCM was the best strategy for unsatisfactory areas, PM for critical areas, and CM for tolerable areas. Chan and Prakash 22 This study developed a fuzzy MCDM approach to choose the most appropriate maintenance strategy in manufacturing firms. The evaluation criteria included: capital cost, running cost, maintenance downtime, reliability, capability, repair load, operator skills, flexibility, efficiency, facility utilization, and resource availability. ...
In most industries, such as aerospace, manufacturing, transport and energy sectors, maintenance plays a vital role in improving the performance of safety critical equipment and facilities. It also helps industries achieve the largest possible efficiency, ensure workplace and environmental safety, and reduce unnecessary breakdowns and costs. Therefore, it is crucial for industries to adopt an optimal maintenance strategy for their critical systems and infrastructure. In this study, we aim to propose a novel analytical multi-criteria decision-making (MCDM) methodology for selecting the most suitable maintenance strategy in distillation units of oil refinery plants. The alternative maintenance strategies include run-to-failure (RTF), preventive maintenance (PM), condition-based maintenance (CBM), and reliability centered maintenance (RCM), which are evaluated with respect to 12 sub-criteria in three categories of economical, safety, and sustainability issues. The MCDM methodology consists of a DEMATEL-based analytic network process (ANP) method to determine the importance weights of decision criteria and a VIKOR method to rank the maintenance strategies. Also, interval type-2 fuzzy sets are used to capture uncertainty in experts’ individual judgments. Finally, a real case study is provided to show the applicability of the proposed methodology to an oil refinery plant. The results show that, thanks to advances in degradation modeling, sensor technology, and data analytics platforms, the RCM and CBM are the superior maintenance strategy for crude oil distillation systems.
... As many factors influence the selection of an optimistic maintenance strategy, MCDM techniques are widely preferred. MCDM approach is efficient in incorporating data and evaluating various factors impacting a problem ( Chan & Prakash, 2012 ). In general, the problem under consideration is divided into multiple clusters and is evaluated using MCDM methods.MCDM techniques, such as Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Decision-Making Trial and Evaluation Laboratory (DEMATEL), VlseKriterijumska Optimizcija Kaompromisno Resenje (VIKOR), and Stepwise weight assessment ratio analysis (SWARA), were developed and effectively used in many application areas (Kazimieras Zavadskas et al., 2019). ...
Poor maintenance practices lead to significant economic, environmental, and social problems and affect the sustainable manufacturing paradigm. The predictive maintenance (PdM) technique helps to minimise problems by forecasting the conditions of the machines. Hence, it is essential for industrial managers to have sustainable predictive maintenance (SPM) practices in place to achieve economic, environmental, and social objectives in their manufacturing environments. However, industrial managers face numerous barriers that may prevent the adoption of SPM practices, and this study aims to identify and evaluate barriers to SPM practices. Initially, by literature review, thirty barriers were identified, and then, using the Pareto analysis, twenty barriers were finalized for evaluation. This study uses an integrated Interpretive Structural Modeling (ISM) and Grey-Decision-making trial and evaluation laboratory (DEMATEL) technique to understand the hierarchies and interrelationships among the barriers to SPM practices. A sensitivity analysis was conducted to examine the robustness of the result. The study reveals that no independent barriers are present in the course of study. Results indicate that poor commitment from top management, lack of a standard performance analysis system, no synchronization among technologies, a lack of awareness on sustainable maintenance practice among stakeholders, and the organization's reluctance to change are the primary causal barriers to SPM practices. This study implies that SPM practices can be productive for industrial communities when industries enhance their technological capability and show interest in maintenance activity. The findings of this study help industrial managers and policymakers to better understand the nature of the barriers towards implementing SPM practices in a manufacturing environment.
... Based on their research, a preventive maintenance strategy was the best choice for the investigated company. Chan and Prakash (2012) employed a distance-based Fuzzy MCDM approach to select a suitable maintenance strategy. They believed that choosing a proper maintenance strategy could promote manufacturing companies' efficiency. ...
In this paper, a new methodology for prioritizing strategies using an integrated approach of fuzzy Multiple Criteria Decision Making (MCDM) is proposed. A case study in an aircraft maintenance unit showed that the "Financial" criterion and the sub-criterion of "Competitiveness and Improving Customer Satisfaction" (with weights of 0.3108 and 0.84, respectively) were the most critical ones. Due to the internal relations between the criteria and sub-criteria in the fuzzy MCDM and the opinions of the experts of the aircraft maintenance unit, the weights of the main criteria obtained were closer to the actual conditions.
... Momeni et al. (2011) and Ding and Kamaruddin (2012) examined the selection of a maintenance policy using fuzzy TOPSIS to account for uncertainty in judgment. Chan and Prakash (2012) evaluated the maintenance policy selection at the level of the firm using the distance-based fuzzy MCDM approach. The selection criteria are capital cost, running cost, reliability, maintenance downtime, capability, repair load, operator skills, flexibility, efficiency, facility utilization and resource availability. ...
Purpose
This paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.
Design/methodology/approach
The critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.
Findings
For a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.
Research limitations/implications
Only three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.
Practical implications
The proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.
Originality/value
This research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.
... Some more advanced maintenance strategies are also included in the decision models, including, for example, reliability-centered maintenance (RCM), proactive maintenance, or total productive maintenance (TPM). The use of fuzzy MCDM techniques is increasing in the literature, for example in [21][22][23][24][25][26][27][28][29][30]. ...
Systems that supply medicinal gases—oxygen, nitrous oxide and medical air—serve all care units of a hospital; for example, they feed distribution systems for operating theatres, neonatal and pediatric units, dialysis, X-ray, casualty, special tests, outpatients, etc. Systems for the provision of medicinal gases are therefore critical in guaranteeing hospital sustainability, since the functionality or availability of other hospital systems depends on them. Availability of 100% in these systems would avoid the need to reschedule patient appointments. It would also eliminate repeat testing, which poses risk to staff and patients, and could avoid affecting people’s lives through unavailability of, for example, operating theatres or intensive care units. All this contributes to a more rational resource consumption and an increase in quality of care both for the hospital itself and for patients and visitors. Although these systems are of vital importance to health care organizations, no previous work has been found in the literature that optimizes the technical decisions on supply in these systems. This research describes a model for these systems via continuous-time Markov chains. The results obtained are used in a multicriteria model constructed with the measuring attractiveness by a categorical-based evaluation technique (MACBETH) approach. In order to assess reliability when incorporating doubt or uncertainty via the MACBETH approach, the model has been validated by means of the fuzzy analytic hierarchy process. The aim is to obtain the best objective decision, with respect to the design of these systems, by analyzing the use of economic resources, the risks, and the impact on hospital activity, all with the aim of guaranteeing the best quality of care. The models constructed by means of MACBETH and the fuzzy analytic hierarchy process give, as the most suitable alternatives, duplicate the external supply in medical oxygen systems and maintain the original design conditions for supply systems of nitrous oxide and medicinal air.
... In this regard, selecting an appropriate maintenance tactic (Chan and Prakash, 2012) is essential for companies to maintain their competitiveness (Maletič et al., 2014). Selecting and determining appropriate maintenance tactic based on the failure frequency of machines is one of the ways of reducing unnecessary activities and costs. ...
Purpose
Decision-Making Grid (DMG) is used for determining maintenance tactics and is associated with the reliability and risk management of assets. In this grid, decision making is performed based on two indicators of Mean Time to Repair (MTTR) and frequency of failures. The purpose of this paper is to improve DMG by recognizing interdependence among failures.
Design/methodology/approach
Fault Tree Analysis and Reliability Block Diagram have been applied for improving DMG. The proposed approach has been examined on eight equipment of the steel making and continuous casting plant of Mobarakeh Steel Company.
Findings
Findings indicate different positions of equipment in the cells of the new grid compared to the basic grid.
Research limitations/implications
DMG is limited to two criteria of frequency of failures and MTTR values. In both basic and new DMGs, cost analysis has not been performed. The application of the proposed approach will help the reliability/maintenance engineers/analysts/managers to allocate more suitable maintenance tactics to equipment. This, in turn, will enhance the equipment life cycle and availability as the main objectives of physical asset management.
Originality/value
A major limitation of basic DMG is that the determined tactic based on these two indicators might not be an appropriate solution in all conditions, particularly when failures are interdependent. This has been resolved in this paper.
... Principal component analysis (PCA) and Criteria Importance through Intercriteria Correlation (CRITIC) are some techniques used in such cases [2,12]. MCDM techniques have wide range of applicability in operations research, manufacturing, and management [7,13,14]. Supply chain, quality and production management are the major areas of where MCDM has been applied in manufacturing systems [4]. ...
Unpredictability of performance under the influence of various uncertainties makes decision-making a complex task on the shop floor. A measure which can indicate the expected shop floor scenario over a projected timeline can be an effective hands-on tool for a shop floor decision maker. The current work proposes three measures, namely complexity, penalty, and desirability of a shop floor situation and aggregates them into a single unified index (UI). Given an indicative list of uncertainties and the prevailing shop floor situation, a periodic simulation approach is presented to observe the changes in the UI. The extent of change in the UI, both in terms of magnitude and direction, is used to identify those significant environmental variables which need intervention. Developing a proactive control measure from the perspective of a decision maker on the shop floor, demonstration of CRITIC (Criteria Importance through Intercriteria Correlation)-based automated decision-making mechanism in a manufacturing setup and a simulation approach to aid the decision-making process are the highlights of the current work. The results reported are with reference to a high-pressure die casting unit.
... Industrial¯rms are realising that there is a critical need for proper maintenance of production facilities and systems [Meulen et al. (2008); Chan and Prakash (2012)]. ...
Nothing lasts forever and all the equipment in a plant has associated with it some predefined life expectancy or operational life. Maintenance practices are the works of keeping the equipment of the plant in good condition for operation. However, the equipment that does not receive adequate maintenance tends to deviate from optimal performance. This can lead to non-control of degraded processes and product volatility, affecting in turn the dynamics of many business issues in industrial organizations. Given the importance of the foregoing, the current study tried to investigate the role of the set of maintenance practices in the poor uptime of operating equipment toward the dynamics of business issues in industrial companies. To achieve this end, the study was performed by conducting a questionnaire survey within the firms of the Kurdistan region of Iraq that have at least 100 employees. The results of the study revealed that improper maintenance practices play a great role in the poor uptime of operating equipment toward the negative dynamic of many business issues such as low customer satisfaction due to production schedules absent from customer shipment commitments, increased safety risks quantitatively and the high cost health losses, especially with the occurrence of major malfunction in operating equipment.
... These performance attributes are then applied to predict the PUV of a manufactured product with recovery settings. Use of fuzzy sets provides a natural and logical framework to conceptualise uncertainty (Zadeh, 1983) and they have been used successfully in many operation management problems (Ilgin and Gupta, 2010), which may not have been possibly solved with mathematical-based approaches (Chan et al., 2008;Chan and Prakash, 2012;Gungor and Gupta, 1999;Gupta and Lambert, 2008). The process flow of six key stages for the performance evaluation model in our integrated approach is provided in Figure 1. ...
Purpose
The purpose of this paper is to propose an approach to evaluate product performance of returned products, using four key performance attributes as the basis for improving sustainability through product recovery.
Design/methodology/approach
A fuzzy logic approach is developed to account a trade-off scenario for a manufactured product with recovery options. This approach is demonstrated using a numerical example and is validated using a case study in the automotive parts and components industry.
Findings
Product utilisation value (PUV) is found to be a useful index that manufacturers can use to assess product recovery options, as it brings together a number of conflicting parameters into a rationalised value for decision making. In addition, PUV provides a rationalised approach for comparing and selecting the most appropriate recovery configuration option.
Research limitations/implications
The authors only utilise four key performance measures to derive PUV. Further research is needed to modify and incorporate other measures that are important to decision makers to improve sustainability in manufacturing supply chains.
Practical implications
The proposed approach may motivate decision makers to consider sustainable recovery options by comparing PUVs of products for primary and secondary markets. The case study demonstrated the conflict and complexity organisations face in a global supply chain of a competitive industry.
Originality/value
The authors propose an approach to optimise trade-off considerations of selected performance attributes through PUV. This PUV as a benchmark can help improve recovery of the returned products and reduce landfill.
... The third group named "human resources development" include the teamwork culture (Willmott 1994) and the motivation of maintenance staff. Finally, the forth group "strategy and development policies" concerns an appropriate maintenance strategy and policy (Chan & Prakash 2012), implementation of technical tools like ERP (Kłos & Patalas-Maliszewska 2013), … etc. ...
In this paper a decision-making tool for maintenance management process in a real-life case
study is proposed, in order to improve maintenance performance. The proposed approach is based on an
effective and optimal assignment process of human resources characterized by their competence and
availability.
A discrete event simulation model based on Pareto multiobjectif optimization method is introduced. The
proposed approach finds good solutions in a reasonable amount of time, and provides significant gains of
maintenance performance extending up to 20%.
... In this context, the application of multicriteria decision making (MCDM) methods is essential for optimization of the overall performance of resources' utilization and means to work in the development, design, production and all other activities (Rao, 2007). The selection of manufacturing technology, machine tools, manufacturing process conditions, cutting tools, material selection for tool -145 -holder, machining coolant and lubrication agents, maintenance policy selection, evaluation of environmentally conscious manufacturing practices, flexible management support and so on, are only some of the examples that require the application of different MCDM methods in real and laboratory conditions (Karsak & Ahiska, 2008;Chan & Prakash, 2012;Ic et al., 2012;Hasan Aghdaie et al., 2013;Calışkan et al., 2013;Chatterjee & Chakraborty, 2013;Gadakh et al., 2013;Temucin et al., 2013;Thirumalai & Senthilkumaar, 2013;Chakraborty & Zavadskas, 2014;Govindan et al., 2014;Hajdasz, 2014;Petkovic et al., 2015). ...
Manufacturing is a primary generator of wealth of the country and is essential for economic growth. Determination of the most suitable manufacturing process conditions for a given application is very complex task and requires consideration of a number of conflicting and diverse process performance characteristics (criteria). In this paper the application of a recent multi-criteria decision making (MCDM) method, i.e. weighted aggregated sum product assessment (WASPAS) for determination of manufacturing process conditions in laser cutting was discussed. Laser cutting experiment was conducted based on Taguchi’s L9 experimental design by varying the laser power, cutting speed, assist gas pressure and focus position at three levels. Based on obtained experimental results, a MCDM model consisting of nine alternatives and six criteria was defined. In order to determine the relative significance of considered criteria a pair-wise comparison matrix of the AHP method was used. Stability of the obtained ranking of alternatives was checked by varying values of coefficient of linear combination and by the application of operational competitiveness ratings analysis (OCRA) method. © 2016, Kauno Technologijos Universitetas. All rights reserved.
... The literature shows how multicriteria techniques have been successfully applied to choosing maintenance policies or strategies for the oil and gas industries [15][16][17], paper mills and pumping stations [18], the weapons system of the Norwegian Army [19], in manufacturing companies [20][21][22], an urban waste water treatment plant [23], a petrochemical plant and the food industry [24], a thermal power plant [25], the textile industry [26,27], aircraft systems [28], a chemical plant [29], a processing plant [30], the railway industry [31], a newspaper printing facility [32], a mining company [33], a dump truck [34], a steel company [35], and a cogeneration system for an ethanol and sugar plant [36]. ...
Background:
Healthcare organizations have far greater maintenance needs for their medical equipment than other organization, as many are used directly with patients. However, the literature on asset management in healthcare organizations is very limited. The aim of this research is to provide more rational application of maintenance policies, leading to an increase in quality of care.
Methods:
This article describes a multicriteria decision-making approach which integrates Markov chains with the multicriteria Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), to facilitate the best choice of combination of maintenance policies by using the judgements of a multi-disciplinary decision group. The proposed approach takes into account the level of acceptance that a given alternative would have among professionals. It also takes into account criteria related to cost, quality of care and impact of care cover.
Results:
This multicriteria approach is applied to four dialysis subsystems: patients infected with hepatitis C, infected with hepatitis B, acute and chronic; in all cases, the maintenance strategy obtained consists of applying corrective and preventive maintenance plus two reserve machines.
Conclusions:
The added value in decision-making practices from this research comes from: (i) integrating the use of Markov chains to obtain the alternatives to be assessed by a multicriteria methodology; (ii) proposing the use of MACBETH to make rational decisions on asset management in healthcare organizations; (iii) applying the multicriteria approach to select a set or combination of maintenance policies in four dialysis subsystems of a health care organization. In the multicriteria decision making approach proposed, economic criteria have been used, related to the quality of care which is desired for patients (availability), and the acceptance that each alternative would have considering the maintenance and healthcare resources which exist in the organization, with the inclusion of a decision-making group. This approach is better suited to actual health care organization practice and depending on the subsystem analysed, improvements are introduced that are not included in normal maintenance policies; in this way, not only have different maintenance policies been suggested, but also alternatives that, in each case and according to viability, provide a more complete decision tool for the maintenance manager.
... Many MCDM approaches have been proposed in the literature. Some of these include the simple additive weighting (SAW), weighted product method (WPM), the technique for order preference by similarity to ideal solution (TOPSIS), and the analytic hierarchy process (AHP) [5]. ...
In the last 20 years, rapid and significant developments have occurred in communication and information technologies. In parallel with these developments, the importance of smartphones has increased. In addition, many smartphone manufacturers have launched and continue to launch a number of new models with many features. People who want to buy a new smartphone have difficulties selecting the best smartphone among the numerous models available on the technology markets. Therefore, smartphone selection has become a complex multi-criteria decision-making (MCDM) problem for people. Hence, decision-making processes will be facilitated by using MCDM methods, and these will provide the most appropriate decision. In this paper, the best smartphone among the 28 alternatives determined by the person who will buy them are selected by using three main criteria and 17 sub-criteria with the help of a two-phased MCDM approach. In the first phase, 28 smartphone alternatives are ranked using the analytic network process (ANP). In the second phase, a model that includes the best four alternatives of ANP is created. Afterwards, the best smartphone is selected using the generalised Choquet integral (GCI) method according to this model. Finally, the findings and the results are given. © 2015, South African Institute of Industrial Engineering, All rights reserved.
Effective maintenance operations are crucial for upholding the productivity of production sites and, consequently, the competitiveness of manufacturing companies. This article introduces a decision-making methodology for maintenance management, incorporating a real case study, aimed at enhancing various maintenance performance metrics. The proposed approach revolves around optimizing the allocation of human resources, considering factors such as their availability, the types of breakdowns, and the level of urgency associated with each issue. A discrete event simulation model is performed to simulate the maintenance process within a manufacturing shop floor. Additionally, to further refine our model, we propose integrating an emergency intervention module with the simulation model to handle intervention requests. The outcomes of this study offer reliable insights into enhancing the maintenance function's performance
In increasingly complex production environments, tremendous efforts are being made to optimize the efficiency of a production system. An important efficiency factor is industrial maintenance, both influencing the cost and securing the technical availability of machines and components. Maintenance managers are required to deliver the necessary availability of the production system while minimizing the resources needed to do so. To make this possible, a method to evaluate the dependency between the technical availability of an entire production system and maintenance resources is necessary. This paper presents a systematic literature review of such methods is presented. In order to assess the methods proposed in the literature, first, requirements are developed, including a necessary focus on maintenance strategies within these methods. Including maintenance strategies is necessary since they provide the foundation for both the availability of a component and the maintenance resources needed. In total, 13 requirements are developed, and 21 different methods are evaluated. Only one of the proposed methods addresses all requirements, with others lacking possible combinations of maintenance strategies and the resulting influences on the production system.
The variety of different malfunctions and breakdowns can significantly impact the performance of a company. Gaining an understanding of the impact of individual components and associated failure mechanisms have on a system is crucial for its overall performance. In order to define the best mix of maintenance strategies for system components, this paper presents a systematic approach, how failure modes and maintenance parameters can be analyzed in order to derive the appropriate strategy and measures for efficient production. Not only the reliability of the components is examined, but also their influence on safety, downtime and quality.
Increasing complexity in manufacturing processes poses new challenges for industrial maintenance. In addition, advanced machine monitoring and lifetime forecasting options expand the tools and maintenance strategies available. Today, maintenance strategy selection is performed sequentially usually based on prioritised machines and components. These selections are optimized locally for each machine isolated, not considering the context of other machines within the value-adding network. To overcome these challenges, this paper presents an approach for an integrated maintenance strategy selection in one-step by an integrated model considering possible machine failures and the context of other machines within the value-adding network in parallel.
The aim of this chapter is to select the most suitable combination of maintenance policies in the different systems that make up an operating theatre: air conditioning, sterile water, power supply, medicinal gases, and operating theatre lighting. To do so, a multicriteria model will be developed using the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) approach considering multiple decision centres. The model uses functional, safety, and technical-economic criteria, amongst which is availability. Mean availability for repairable systems has been measured to assess this criterion, using Markov chains from the data obtained over three years from the subsystems of a hospital operating theatre. The alternatives considered are corrective maintenance; preventive maintenance together with corrective maintenance by means of daily, weekly, monthly, and yearly programmes; periodical predictive maintenance together with corrective maintenance; and corrective together with preventive and predictive maintenance.
This article deals with an Economic Production Quantity (EPQ) deteriorating inventory model for non-random uncertain environment. It includes rework process, screening of imperfect items and partial backlogging. The items are partially serviceable, because at the time of production some items are found to be defective which cannot be recoverable or serviceable. At first, we develop a cost minimization problem under several assumptions related to imperfect items and rework process under certain linear constraints. We solve the crisp model (primal nonlinear problem) first, and then we convert this model into equivalent game problem taking the help of the theories related to strong and weak duality theorem. However, this game problem consists of the Lagrangian function that correspond a nonlinear objective function subject to some linear constraints. The main objective of the study is to develop a solution procedure of the problem associated to an imperfect process where all unit cost components might increase or decrease neutrosophically. Thus, according to the experiences gained by the decision maker (DM) we fuzzify all cost components as sub-neutrosophic offset. To defuzzify the model we have utilized the sine cuts of neutrosophic fuzzy numbers followed by a solution procedure developed in solving the matrix game exclusively. To validate the model, a numerical example is studied then we have compared the optimal results among the original problem, the equivalent game problem and the game problem under neutrosophic environment explicitly. Our findings reveal that under negative α-cuts the value of the objective function assumes lower and higher values. Finally, sensitivity analysis, graphical illustrations, conclusions and scope of future works have been discussed.
Purpose
The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) models.
Design/methodology/approach
The decision hierarchy of this research includes three levels. The first level aims to choose the best maintenance policy for different types of equipment of an acid manufacturer. These equipment pieces include molten sulfur ponds, boiler, absorption tower, cooling towers, converter, heat exchanger and sulfur fuel furnace. The second level includes decision criteria of added-value, risk level and the cost. Lastly, the third level comprises time-based maintenance (TBM), corrective maintenance (CM), shutdown maintenance and condition-based maintenance (CBM) as four maintenance policies.
Findings
The best maintenance policy for different types of equipment of a manufacturer is the main finding of this research. Based on the obtained results, CBM policy is suggested for absorption tower, boiler, cooling tower and molten sulfur ponds, TBM policy is suggested for converters and heat exchanger and CM policy is suggested for a sulfur fuel furnace.
Originality/value
This research develops a novel model by integrating FAHP and an interval TOPSIS with concurrent consideration of added-value, risk level and cost to select the best maintenance policy. According to the highlights of the previous studies conducted on maintenance policy selection and related tools and techniques, an operative integrated approach to combine risk, added-value and cost with integrated fuzzy models is not developed yet. The majority of the previous studies have considered classic fuzzy approaches such as FAHP, FANP, Fuzzy TOPSIS, etc., which are not completely capable to reflect the decision makers’ viewpoints.
The engine rooms of ships accommodate different machinery systems that are critical to ship operations. For these critical machinery systems to continue delivering the high level of service, operators are required to select and apply the best maintenance interventions. Currently, the selection of appropriate maintenance strategies for different engine room’s machinery systems is handled in a traditional way, regardless of in what condition such systems are. The aim of this paper is to propose a semi-qualitative model integrating AHP and PROMETHEE to select appropriate maintenance strategies for different critical machinery found in the engine rooms of ships. The proposed model consists of three maintenance alternatives among which decision-makers must select the best strategy according to four comparison criteria. The model is applied to select the best maintenance strategies for 17 different shipboard machinery systems in the engine room of a barge operating within West African waters. Finally, the results are compared with those obtained from a cost-benefit analysis approach (quantitative) as well as a survey of the experienced marine engineers who operate these machinery in the engine rooms of ships (qualitative). The results of the case study indicate that the proposed semi-qualitative method is a more robust approach for selecting maintenance strategies of shipboard machinery systems.
Cross entropy is an important index for determining the divergence between two sets or distributions. Most existing cross entropy are proposed in a fuzzy environment and undefined in some uncertain situations (e.g., Dempster–Shafer theory). This study proposes an extended cross entropy measure of belief values based on a belief degree using available evidence. Thus, a new aspect of belief functions represents in the name of a belief set. Then, a new cross entropy measure between two belief sets is defined. Furthermore, the application of the cross-entropy measure in multi-criteria decision making (MCDM) is provided with belief valued information.
Selection of an appropriate maintenance strategy for multi-component systems is a very complex task due to diversity of components and their different failure modes, existence of various dependencies among components and a large number of competing criteria that need to be taken into consideration. This study presents a combined analytic network process and cost-risk criticality analysis model to select a cost-effective, low-risk maintenance strategy for different sets of components of a complex system. The proposed model consists of four maintenance alternatives (i.e. failure-based, time-based, risk-based and condition-based), among which the most appropriate strategy, on the basis of two criteria of maintenance implementation costs and failure criticality, is to be chosen. The former criterion includes the annual maintenance expenditure required for hardware, software and personnel training, while the latter criterion focuses on the capability of maintenance in reducing the failure vulnerability and enhancing the reliability and resilience. The possible dependencies among selection criteria as well as the failure interactions between components are taken into account to evaluate the maintenance alternatives. Finally, the model is applied to determine a suitable maintenance strategy for a new wind turbine configuration consisting of several mechanical, electrical and auxiliary components at the design stage. The results are compared with practices of maintenance over the first year of system operation as well as with the results obtained from an analytic hierarchy process model.
Implementation of the megaprojects with large-scale engineering and construction projects are risky in nature and evaluating the associated risks of those large projects is a critical success factor. The systematic approaches and empirical studies related to the visualisation and communicating risks of these projects remain missing. This paper aims to develop a systematic approach to managing and visualising the risk of these mega-projects using joint application of fuzzy group decision-making, analytic network process and mapping the resulting network of dependencies together with proximity information, graph theory, and mutual information theory. We have applied the model in a real case study of megaprojects in the oil and gas industry. The methodology proposed in this study could be used in the other large-scale engineering and construction projects considering the contracts features and the contextual factors.
This paper investigates the performance of condition-based maintenance (CBM), age-based maintenance (ABM) and failure-based maintenance (FBM) policies in series and parallel multi-resource systems. Condition-based maintenance is mainly taken into account as a significant maintenance policy that makes use of the component operating circumstances to predict failure occurrence. The advantage of implementing CBM is that the component is preventively maintained only when necessary and as a result, the entity can benefit saving resources and system availability. Since implementing CBM seems to be impossible in some situations, ABM and FBM are considered as two alternatives for CBM. In this paper, these three policies are compared with each other using simulation. To evaluate and analyze these three maintenance policies in parallel and series configurations, three performance indicators including efficiency (E), total maintenance costs (TMC) and average queue (AQ) are introduced for all scenarios. An explanatory case study is applied to investigate the performance of these policies in various conditions. The results demonstrate that in general, CBM performs better than ABM, and on the other hand, ABM shows better results in comparison to FBM. This is the first study which compares CBM, ABM and FBM policies in series and parallel configurations considering efficiency, maintenance cost and queue length as criteria.
This paper presents a joint optimization model of production lot sizing and condition-based maintenance for a multi-component production system which produces the products to meet the demand in a finite time horizon. The components in the system deteriorate gradually with usage and age. To evaluate the conditions of components, inspections are carried out after each production run. The condition-based maintenance decision-making rules are based not only on the predictive reliability but also on the structural importance of each component. Moreover, the economic dependency among components is also considered when performing corrective maintenance actions. The preventive maintenance cost, the corrective maintenance cost, the setup cost, the inspection cost, the inventory holding cost and the shortage cost are considered in this paper. The aim is to minimize the total cost by jointly optimizing two decision variables: the production lot size and the preventive maintenance threshold. The optimal joint policy is obtained by coupling simulation model and genetic algorithm. Finally, the use and advantages of our model are illustrated through a case study of a cluster tool.
Maintenance is carried out to prevent the occurrence of events that lead to malfunction and interruption of the production process or the operation of the concerned equipment. One of the main approaches in maintenance is to identify the risk of equipment failure mode. Whereas by reducing the high risk of failure mode the reliability and availability of equipment enhanced and the cost of shutdown reduced, identifying the risk of failure is important. In this paper, a fuzzy hybrid approach, including failure mode and effective analysis (FMEA), decision-making trial and evaluation laboratory technique (DEMATEL), and analytic network process (ANP), is presented to select an appropriate maintenance policy through identifying the risk of failures. The authors aim to develop a risk-based method for selecting a proper maintenance strategy to have available and reliable tamping equipment in railway of Iran. Because of considering the same weight of risk factors, failure occurrence, failure severity, and failure detection ability in FMEA, the traditional FMEA method cannot correctly predict the system’s behavior. So, in this paper, the risk factors as fuzzy variables are proposed and evaluated using fuzzy linguistic terms and fuzzy ratings. In a case study, the present approach is utilized for evaluation and determination of the risk of failure modes for a railway company. At first, fuzzy FMEA is used to identify the main risk and sub-risk of failure modes. Second, fuzzy DEMATEL method is used in order to put forward the interrelationship among the main risks which are determined through fuzzy FMEA. Then, the weights of the sub-risks are calculated by fuzzy ANP approach on the basis of cause–effect relationships that are exposed through DEMATEL method. Finally, the weights of sub-risks are determined by multiplying the weights which have been obtained from fuzzy FMEA to the weights of ANP supermatrix. The weights of sub-risks were determined on the basis of these examined dependencies, and these weights were used for a tamping machine to determine maintenance policy. Finally, some strategies and suggestions have been drawn concerning the needs to reduce the risks and improve the equipment’s availability.
The aim of this article is to select the most suitable combination of maintenance policies in the different subsystems that make up an operating theatre. To do so a multicriteria model will be developed using the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) technique considering multiple decision centres: The Hospital's technical services, environment and occupational risk prevention managers, healthcare managers (operating theatres and health activity programming) healthcare staff, technicians, purchasing service managers and Hospital executives. The model uses functional, safety and technical-economical criteria, amongst which is availability. Mean availability for repairable systems has been measured to assess this criterion, using Markov chains from the data obtained over three years from the subsystems of a Hospital operating theatre. All this is aimed at increasing the operating theatre's availability and, consequently, increasing physical safety in patient operations and reducing the number of delayed operations due to technical malfunctions.
A framework for reliability and maintenance analysis of job shop manufacturing systems is proposed in this paper. An efficient preventive maintenance (PM) policy in terms of failure effects analysis (FEA) is proposed. Subsequently, reliability evaluation and component importance measure based on FEA are performed under the PM policy. A job shop manufacturing system is applied to validate the reliability evaluation and dynamic maintenance policy. Obtained results are compared with existed methods and the effectiveness is validated. Some vague understandings for issues such as network modelling, vulnerabilities identification, the evaluation criteria of repairable systems, as well as PM policy during manufacturing system reliability analysis are elaborated. This framework can help for reliability optimisation and rational maintenance resources allocation of job shop manufacturing systems.
Reliability, flexibility and speed belong among particularly valued parameters of contractor. In manufacturing companies, the achievement thereof is significantly limited by the reliability of production equipment. The aim of the article is to analyze an applied production equipment maintenance system with heavily utilized production equipment, and to define guidelines for its improvement. A content analysis of information obtained in a primary qualitative research and a comparison with theoretical approaches made it possible to define an adequate combination of various types of maintenance, including methods and tools that are not primarily intended for the examined type of manufacturing processes.
This paper studies an integrated control strategy of production and maintenance for a machining system which produces a single type of product to meet the constant demand. Different from previous research, we assume in this study that during the production, the production rate not only influences the life of cutting tool, but also the reliability of the machine. Both the replacement of cutting tool and the preventive maintenance (PM) of machine are considered in this paper. The machine is preventively maintained at the Nth tool replacement or correctively repaired at the machine failure, whichever occurs first. PM and corrective repair may cause shortage which can be reduced by controlling inventory. There are two decision variables p and N, where p denotes the production rate and N denotes the number of cutting tool replacement before the PM is performed. An integrated model is developed to simultaneously determine the optimal production rate and PM policy that minimise the total expected cost per unit item produced. Finally, an illustrative example and sensitivity analysis are given to demonstrate the proposed model.
This study covers new trends and techniques in the field of predictive maintenance, which has been superseding traditional management policies, at least in part. It also presents suggestions for how to implement a predictive maintenance programme in a factory/premise and so on. Predictive maintenance primarily involves foreseeing breakdown of the system to be maintained by detecting early signs of failure in order to make maintenance work more proactive. In addition to the aim of acting before failure, it also aims to attend to any fault, even if there is no immediate danger of failure, to ensure smooth operation and reduce energy consumption. Predictive maintenance has been adopted by various sectors in manufacturing and service industries in order to improve reliability, safety, availability, efficiency and quality as well as to protect the environment. It also has created a separate sector, which specializes in developing predictive maintenance instruments, offering dedicated predictive maintenance solutions and training predictive maintenance experts. Predictive maintenance techniques are closely associated with sensor technologies but for efficient predictive maintenance applications, a comprehensive approach, which integrates sensing with subsequent maintenance activities, is needed to be adapted in accordance with the needs of the particular organization. Recent advances in information, communication and computer technologies, such as Internet of Things and radio-frequency identifications, have been enabling predictive maintenance applications to be more efficient, applicable, affordable, and consequently more common and available for all sorts of industries. Researches on remote maintenance and e-maintenance have been supporting predictive maintenance activities especially in unsafe working environments and scattered locations.
It is apparent that there is a need for integrated criteria in the performance measurement of modern organisations when dealing with the performance measurement of manufacturing businesses. This paper addresses this issue in the context of measuring the performance of the 2nd Air Supply and Maintenance Center Command manufacturing/maintenance jobshops of Turkey by using a new framework which combines fuzzy TOPSIS (technique for order preference by similarity to ideal solution) for measuring qualitative performance with DEA (data envelopment analysis) for measuring quantitative performance. This proposed approach provides a comprehensive measure of performance incorporating both quantitative and qualitative attributes, which in general reflect efficiency and effectiveness of the manufacturing jobshops respectively.
We develop an economic model for the optimization of maintenance procedures in a production process with two quality states. In addition to deteriorating with age, the equipment may experience a jump to an out-of-control state (quality shift), which is characterized by lower production revenues and higher tendency to failure. The times to quality shift and failure are allowed to be generally distributed random variables. We consider two types of maintenance: minimal maintenance (MM) that upgrades the quality state of the equipment without affecting its age and perfect preventive maintenance (PM) that fully upgrades the equipment to the as-good-as-new condition. We derive the expression for the expected profit per time unit and we investigate, through a large number of numerical examples, the type of the optimal solution. It is concluded that in practically every case the optimal maintenance policy is an extreme one: it either calls for immediate MM as soon as a quality shift occurs (active policy) or it allows operation in the out-of-control state until the time of a scheduled PM action (passive policy).
We consider the single machine total flow time problem in which the jobs are non-resumable and the machine is subject to preventive maintenance activities of known starting times and durations. We propose a branch-and-bound algorithm that employs powerful optimality properties and bounding procedures. Our extensive computational studies show that our algorithm can solve large-sized problem instances with up to 80 jobs in reasonable times. We also study a two-alternative maintenance planning problem with minor and major maintenances. We give a polynomial-time algorithm to find the optimal maintenance times when the job sequence is fixed.
In this study we propose an operating conditions-based preventive maintenance (PM) approach for computer numerical control (CNC) turning machines. A CNC machine wears according to how much it is used and the conditions under which it is used. Higher power or production rates result in more wear and higher failure rates. This relationship between the operating conditions and maintenance requirements is usually overlooked in the literature. On CNC turning machines we can control the machining conditions such as cutting speed and feed rate, which in turn affect the PM requirements of the CNC machine. We provide a new model to link the PM decisions to the machining conditions selection decisions, so that these two decision-making problems can be solved together by considering their impact on each other. We establish that our proposed geometric programming model captures the related cost terms along with the technological restrictions of CNC machines. The proposed preventive maintenance index function can be used to provide an intelligent CNC machine degradation assessment.
This paper illustrates how an effective maintenance policy could influence the productivity and profitability of a manufacturing process. It was possible to show how changes in the productivity affect profit, separately from the effects of changes in the uncontrollable factors, i.e. price recovery. The main results of the case study performed at a Swedish paper-mill showed that a paper-mill machine could, ideally, generate extra profit of at least 7.8 million Swedish kronor (SEK) (approximately US$ 0.975 million) per year, i.e. 12.5% of its yearly maintenance budget, if it avoids all unplanned stoppages and bad quality production due to maintenance-related causes. Thus, maintenance is not a cost centre, but a profit generating function.
The purpose of this paper is to investigate the maintenance practices that are used in Swedish industry. The study was performed by conducting a cross-sectional survey within Swedish firms that have at least 100 employees. The main results achieved from the study show that the role of maintenance is not highly recognised. There is a need to spend and invest more in maintenance, which is considered by the majority of Swedish industries as a necessary expense. Although about 13% of the maintenance department time is spent on planning maintenance tasks, nevertheless, about one third of the time is spent on unplanned tasks. There is a need for more adoption of maintenance concepts such as total productive maintenance (TPM) and reliability-centred maintenance (RCM). The lack or ineffectiveness of planning and scheduling can significantly restrict the maintenance department in achieving its objectives and can thus prevent the company from maximising business profits and offering competitive advantages.
It is a PhD thesis.
In this thesis we focus on the technical, economic, managerial and probabilistic topics which can be used to select and improve vibration-based maintenance policy. The management aspect of maintenance in its overall concept received less attention in this thesis. In order to reduce the scope of the study, the work presented in this research focuses on the aspects essential to maintenance, which are:
1. Maintenance technical, probabilistic and economical aspects, such as failure analysis, maintenance cost equation, component condition-dependent failure rate, maintenance effectiveness, accuracy and cost-effectiveness, and the selection of the most cost-effective maintenance policy.
2. Condition monitoring, e.g. CM parameters and techniques, the most informative parameter, relating vibration frequencies to damage in the replaced rolling element bearings, alarming and alarm levels and the selection of the most cost-effective VBM system.
3. Condition-based maintenance, including assessment of the time to action, a new maintenance approach, (TQMain), to sustain and improve continuously the technical and economic effectiveness of the essential manufacturing process elements and improvement of vibration-based maintenance policy.
4. Information Technology; including integration of maintenance software program with plant IT-System to improve diagnosis, prognosis and decision making.
5. Co-ordination between these subjects in order to improve the selected vibration-based maintenance policy and maintenance staff in the sense of the new maintenance approach, (TQMain).
The main objective of this research is to develop a model for selection of a cost-effective vibration-based maintenance policy and then for utilising experience and knowledge to improve the selected policy continuously. This is in order to make use of as much as possible of a component’s mean effective life and to offer better economics. This objective was achieved through accomplishment of the following sub-objectives:
1. Development of a maintenance approach to sustain and improve continuously the effectiveness of the essential elements constituting a manufacturing process such as machinery, operation, environmental condition, quality control.
2. Development of criteria for the selection of the most informative CM parameter(s) and most cost-effective condition-based maintenance policy.
3. Theoretical basis to improve the selected cost-effective condition-based maintenance policy based on experience.
4. Case studies to analyse real situations, explore the possibilities of making improvements in the maintenance policy and applying some of the research result(s).
This paper presents a logical procedure to evaluate alternative flexible manufacturing systems for a given industrial application. The procedure is based on a combined multiple attribute decision making method using TOPSIS and AHP methods together. A ’flexible manufacturing system suitability index’ is proposed that evaluates and ranks flexible manufacturing systems for the given industrial application. The methodology is illustrated by means of an example.
Various approaches to and techniques for facilities lay-out problems are reviewed and a fuzzy set theory based ‘construction’ type heuristic for a block lay-out design problem, formulated using the linguistic variables representing flow, control, process, organization personnel and environmental relationships between facility pairs, is presented. The problem-solving strategy, which consists of procedures for aggregating experts' opinions, the location, selection and placement of facilities, and for evaluating layout, is illustrated with a numerical example. The performance of the ‘fuzzy’ heuristic compares well with the established procedures ALDEP and CORELAP. Areas for further investigation for making the present implementation more effective in dealing with real problems are identified.
Manufacturing systems are subject to a degradation process that leads to machine failure if no action is taken. Machine failures reduce the performance of the manufacturing system with loss of profits. The research proposed here concerns the evaluation of the manufacturing system performance in dynamic conditions when different maintenance policies are implemented in a multi-machine manufacturing system controlled by multi-agent-architecture. There are two extreme maintenance policies that can be applied: no preventive maintenance, where action is taken on the failure state, and intensive preventive maintenance, which can eliminate unforeseen failures, but at a high cost. Dynamic policy maintenance is proposed to reduce the number of maintenance operations of the preventive policy. A discrete simulation environment has been developed in order to investigate the performance measures and the indexes of the costs of maintenance policies. The simulations have been conducted for several levels of mix, product demand and working time uncertainty. The simulation results show that the proposed approach leads to better performance for the manufacturing system and reduces the number of maintenance operations (cost index of the maintenance policy), except in the case of the mean time between failure, which is characterised by a very low standard deviation.
Purpose
In this paper, an optimal periodic replacement strategy is proposed. This strategy suggests new items to perform replacements at failure. Preventive replacements, scheduled at instants kT ( k =1, 2,…) are carried out only if the item's age exceeds a threshold to be determined. Parameters T and b are derived from an optimization model aiming to maximize the steady state availability under budgetary constraints or to minimize the expected total cost per unit of time over an infinite horizon, while the steady state availability must be higher than some given threshold. Costs and durations associated with replacement actions are supposed to be known.
Design/methodology/approach
Employs mathematical models to investigate the expected cost rate and the steady state availability with illustrative examples.
Findings
Analytical and numerical results have been obtained for a system whose lifetime is distributed according to an Erlang distribution.
Practical implications
The proposed strategy seems more efficient than the basic block replacement strategy aiming to maximize the steady state availability. It is also easy to implement.
Originality/value
This new strategy would appear to be more efficient than the previous basic block replacement strategy.
Modern manufacturing requires that to be successful organisations must be supported by both effective and efficient maintenance. One approach to improving the performance of maintenance activities is to implement and develop a total productive maintenance (TPM) strategy. However, it is well documented that a number of organisations are failing to successfully implement such strategies. This paper outlines research carried out by the Aeronautical, Mechanical and Manufacturing Engineering Department at Salford University aimed at discovering the factors affecting the successful implementation of TPM. This research has led to the development of a generic model indicating factors affecting the successful implementation of TPM. The validity of the generic model has been tested in a UK manufacturing small- to medium-size enterprise (SME) and the case study research findings further triangulated through a review of documented case study evidence. This research has also led to the development of recommendations to improve the TPM development and implementation program of the case study organisation. Further development of the research has resulted in a step-wise program or generic roadmap for UK SMEs which is proposed as a tool for the implementation or rejuvenation of an organisation’s TPM program.
The paper describes a scheme in which a fuzzy algorithm is used to control plant, in this case, a laboratory-built steam engine. The algorithm is implemented as an interpreter of a set of rules expressed as fuzzy conditional statements. This implementation on a digital computer is used online, to control the plant. The merit of such a controller is discussed in the light of the results obtained.
Partner selection in virtual enterprises (VE) can be viewed as a multi-criteria decision making problem that involves assessing trade-offs between conflicting tangible and intangible criteria. In general, this is a very complex problem due to the dynamic topology of the network, the large number of alternatives and the different types of criteria. In this paper we propose an exploratory process to help the decision-maker obtain knowledge about the network in order to identify the criteria and the companies that best suit the needs of each particular project. This process involves a multi-objective tabu search metaheuristic designed to find a good approximation of the Pareto front, and a fuzzy TOPSIS algorithm to rank the alternative VE configurations. In the exploratory phase we apply clustering analysis to confine the search according to the decision-maker beliefs, and case base reasoning, an artificial intelligence approach, to totally or partially construct VEs by reusing past experiences. Preliminary computational results clearly demonstrate the potential of the approach for practical application.
In this paper, a framework of integrating preventive maintenance (PM) and manufacturing control system is proposed. Fuzzy-logic control is used to enable an intelligent approach of integrating PM and a manufacturing control system. This will contribute to the novel development of an integrated and intelligent framework in those two fields that are sometimes difficult to achieve. This idea is based on combining work on an intelligent real-time controller for a failure-prone manufacturing system using a fuzzy-logic approach (Yuniarto, M.N. and Labib, A.W., Optimal control system of an unreliable machine using fuzzy logic control: from design to implementation. Int. J. Prod. Res. (in press a); Yuniarto, M.N. and Labib, A.W., Intelligent real time control of disturbances in manufacturing systems. Integr. Manuf. Syst.: Int. J. Manuf. Technol. Manage. (in press b) and the work on PM proposed by Labib et al. (Labib, A.W., Williams, G.B. and O’Connor, R.F., An intelligent maintenance model (system): an application of analytic hierarchy process and a fuzzy logic rule-based controller. J. Oper. Res. Soc., 1998, 49, 745–757)). The aim of the research is to control a failure-prone manufacturing system and at the same time propose which PM method is applicable to a specific failure-prone manufacturing system. The mean time to repair and mean time between failures of the system are used as integrator agents, by using them to couple the two areas to be integrated (i.e. a maintenance system and manufacturing system).
This paper aims to develop a performance measurement model (PMM) that can be used to obtain an overall performance score by measuring the success of a manufacturing company in its operational activities. The developed PMM measures a company's level of performance in critical dimensions and combines these performance scores to obtain a ranking score. A set of critical dimensions and their sub-components is fully defined, and performance scorecards are developed to guide the assignment of performance scores. Performance scores are assigned according to the level of intensity of a manufacturing company's investments, practices, actions or infrastructures in the critical dimensions. The Analytic Hierarchy Process (AHP) approach is used to weight (relative importance) the dimensions and their sub-components. The weights and performance scores are combined by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. An example is provided to illustrate the application of the proposed PMM.
In this paper, we present a fuzzy multiple criteria decision making (FMCDM) model known as fuzzy balancing and ranking. In contrast to other MCDM models, our proposed model does not require the weights of decision making criteria. First, we appraise the performance of alternatives against criteria via linguistic variables which are expressed as triangular fuzzy numbers. The foregoing model obtains the alternative rankings through a four-stage process. Second, an outranking matrix is derived indicating that the frequency with which one alternative is superior to all other alternatives based on each criterion. Third, the outranking matrix is triangularised to obtain an implicit pre-ordering or provisional order of alternatives. Fourth, the provisional order of alternatives is subjected to various screening and balancing operations that require sequential application of a balancing principle to the so-called advantages–disadvantages table that combines the criteria with the pair-wise comparisons of alternatives. Additionally, to demonstrate the procedural implementation of the proposed model and its effectiveness, we apply it on a case study regarding the problem of supplier selection.
Considering the high required capital outlay and moderate risk of a flexible manufacturing system (FMS) investment, economic justification techniques are insufficient by themselves since they cannot cope with the benefits such as flexibility and enhanced quality offered by advanced manufacturing technologies. A robust decision-making procedure for evaluating FMS requires the consideration of both economic and strategic investment measures. A distance-based fuzzy multicriteria decision-making (MCDM) framework based on the concepts of ideal and anti-ideal solutions is presented for the selection of an FMS from a set of mutually exclusive alternatives. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The multicriteria decision approach presented here enables us to incorporate data in the forms of linguistic variables, triangular fuzzy numbers and crisp numbers into the evaluation process of FMS alternatives. Linguistic variables are also used to indicate the criteria's importance weights assigned by the decisionmakers. A comprehensive example illustrates the application of the multicriteria decision analysis.
Various models and heuristic procedures for a multiple criteria facility layout planning problem are reviewed and the problem is formulated based on a ‘linguistic pattern’ approach. A heuristic procedure is proposed to generate a set of efficient alternative layouts. The problem of selection of the facility layout from the set of alternatives, which satisfy different objectives and restrictions to known degrees, is considered as a multiple criteria decision making (MCDM) problem and various MCDM approaches are reviewed. An ELECTRE method based on ‘outranking relations’ approach, is proposed for the multiple criteria evaluation and ranking of efficient layout alternatives. The problem-solving methodology is illustrated with a numerical example and directions for further investigation are identified.
Approaches maintenance management in a systematic way so as to achieve its business objectives. From a managerial point of view, this so-called object/objective-oriented maintenance management (OOMM) is an integral process of asset (equipment) management with behavior-based maintenance (BBM) as a major element. Within the OOMM concept, the objective-approach focuses on the managing of the maintenance processes so as to achieve the business objectives, and the object-approach emphasizes the object (asset or equipment) and the behavioral failures. Furthermore, combined together, the two approaches reflect the basic characteristics of the maintenance process. Also, both sides affect and influence each other, and are inseparable within OOMM. BBM addresses the monitoring and controlling of the technical and economic behavior of a piece of equipment in two ways.
The importance of the facility maintenance management in the manufacturing environment has increased rapidly as many organisations aim to become world class. For many organisations it is important to respond to the global competitive pressure by seeking to increase their productivity, maximising the overall equipment effectiveness and pursing an effective and efficient maintenance programme. By creating a set of key ingredients for effective maintenance management and success, this paper analyses the current status of these components in the UK manufacturing organisations through a pilot survey of 18 UK manufacturing respondents. A radar diagram was generated showing the current status of maintenance management in the UK. The chart shows that only one-third of the organisations seriously consider good maintenance management practices and realise the full benefits. Any preparation of adequate reports on performance and cost is visibly lagging behind. The paper also explores the opportunities for improving maintenance management in UK manufacturing organisations. The crucial involvement of the management is fundamental to give the guidance and direction to the maintenance function.
Reviews overall models for maintenance management from the viewpoint of one who believes that improvements can be made by regarding maintenance as a “contributor to profits” rather than “a necessary evil”. The reasons why maintenance is such a “Cinderella function” are largely historical and can mostly be overcome by new information technology (IT) and its falling cost. Progress is now being held up by outdated notions of what is economically possible in data acquisition and analysis, and failure to revise basic maintenance and reliability concepts, some of which are now 30 years out-of-date. Integrated IT permits mathematical optimisation of supra-departmental management decisions, e.g. co-planning of production with maintenance, overhaul/renewal of machinery and improvement of product performance/quality. Life-cycle profit (LCP) is a fair measure of overall effectiveness that emphasises the value rather than the cost of terotechnological activities.
In a Just-in-Time production environment, due to the limited amount of in-process inventory, machine failures have a greater impact on the productivity. In this paper, we explore some characteristic factors of several classes of JIT systems that could play a role in selection of a suitable maintenance policy for each class. The study is also extended to assessment of the changes in the performance of a system under a given policy as a function of the changes in the values of these factors. In order to accomplish this, production and maintenance functions were considered as two inter-related components of the total system. Furthermore, sixteen simple and composite factors were identified as the characteristic factors defining JIT systems. An extensive experimentation on various systems defined by these factors revealed that these factors can be categorized into three relatively distinct classes. The first class includes those factors that play a major role in how effective a particular maintenance policy is for a system. The second class of factors consists of those that affect the selection of the policy only if they are within a certain range. The third class of factors are those that show no significant effect on the effectiveness of a maintenance policy.
This paper discusses various techniques for layout planning and outlines an application of fuzzy set techniques to the block layout design problem. In particular, a fuzzy linguistic heuristic for the location of the departments within a facility is proposed. This heuristic utilizes imprecise descriptors for two distinct design categories: closeness and importance, expressed in the form of fuzzy relations for every pair of departments. A numerical example is given to illustrate the proposed approach and directions for further research are discussed.
TOPSIS is a multiple criteria method to identify solutions from a finite set of alter-natives based upon simultaneous minimization of distance from an ideal point and maximization of distance from a nadir point. TOPSIS can incorporate relative weights of criterion importance. This paper reviews several applications of TOPSIS using different weighting schemes and different distance metrics, and compares results of different sets of weights applied to a previously used set of multiple criteria data. Comparison is also made against SMART and centroid weighting schemes. TOPSIS was not found to be more accurate, but was quite close in accuracy. Using first-order and second-order metrics were found to be quite good, but the infinite order (Tchebycheff norm, L-∞) was found to decline in accuracy.
The approach described in this paper represents a substantive departure from the conventional quantitative techniques of system analysis. It has three main distinguishing features: 1) use of so-called ``linguistic'' variables in place of or in addition to numerical variables; 2) characterization of simple relations between variables by fuzzy conditional statements; and 3) characterization of complex relations by fuzzy algorithms. A linguistic variable is defined as a variable whose values are sentences in a natural or artificial language. Thus, if tall, not tall, very tall, very very tall, etc. are values of height, then height is a linguistic variable. Fuzzy conditional statements are expressions of the form IF A THEN B, where A and B have fuzzy meaning, e.g., IF x is small THEN y is large, where small and large are viewed as labels of fuzzy sets. A fuzzy algorithm is an ordered sequence of instructions which may contain fuzzy assignment and conditional statements, e.g., x = very small, IF x is small THEN Y is large. The execution of such instructions is governed by the compositional rule of inference and the rule of the preponderant alternative. By relying on the use of linguistic variables and fuzzy algorithms, the approach provides an approximate and yet effective means of describing the behavior of systems which are too complex or too ill-defined to admit of precise mathematical analysis.
The evolution of system reliability depends on its structure as well as on the evolution of its components reliability. The latter is a function of component age during a system's operating life. Component aging is strongly affected by maintenance activities performed on the system. In this work, we consider two categories of maintenance activities: corrective maintenance (CM) and preventive maintenance (PM). Maintenance actions are characterized by their ability to reduce this age. PM consists of actions applied on components while they are operating, whereas CM actions occur when the component breaks down. In this paper, we expound a new method to integrate the effect of CM while planning for the PM policy. The proportional hazard function was used as a modeling tool for that purpose. Interesting results were obtained when comparison between policies that take into consideration the CM effect and those that do not is established.
We assess the most popular maintenance approaches, i.e. strategies, policies, or philosophies, using a fuzzy multiple criteria decision making (MCDM) evaluation methodology. We illustrate with two examples how the suggested evaluation methodology identifies the most informative approach. Using the fuzzy MCDM, it would be possible to select in advance, the most informative (efficient) maintenance approach. Consequently, this leads to less planned replacements, and failures would be reduced to approximately zero and higher utilization of component life can be achieved. Thus, the maintenance department could contribute more to the business objectives throughout participating effectively in adding value to the production activities.
In this paper a model is developed for identifying, monitoring and improving the economic impact of vibration-based maintenance (VBM). This model provides an additional possibility of identifying where, why and how much capital should be invested, and judges whether or not the investment was cost-effective. The model is further utilised to develop relevant maintenance performance measures. When the model was tested in a Swedish paper mill, the main results were: the average yearly maintenance profit achieved using integrated VBM was at least 3.58 million Swedish kronor (SEK) (approximately US3 million). Furthermore, the model facilitated identification of problem areas and recognition of where investments should be made. The major conclusion is that the better the data coverage and quality, the greater control is possible over direct maintenance costs, savings and further profits in maintenance. Moreover, using the model it would be easier and more reliable to detect deviations in the maintenance performance and eliminate their causes at an early stage.
The problem of robot selection has been of concern to manufacturers for many years. This problem has become more difficult in recent years due to increasing complexity, available features, and facilities offered by different robotic products. The objective of this research is to generate and maintain reliable and exhaustive database of robot manipulators based on their different pertinent attributes. This database can be used to standardize the robot selection procedure when the manufacturing firm has decided to use the robot for a particular operation. This will help the robot user to save time by providing him a tool for selecting the robot system most suited for his operational needs. The robot selection procedure allows rapid convergence from a very large number of candidate robots to a manageable shortlist of potentially suitable robots using ‘elimination search’ based on the few critical selection attributes. Subsequently, the selection procedure proceeds to rank the alternatives in the shortlist by employing different attributes based specification methods and graphical methods. The ranks of the candidate robots are calculated with respect to the best possible robot, say +ve benchmark robot, for particular application. This ranking will provide a good guidance for the robot user to select the robot. It will also provide a good insight to the robot manufacturer so that he can improve his product or introduce new product to fulfill the need of customer. It will help the designer at various design stages, while the maintenance people can plan maintenance strategy to reduce the down time and maintenance efforts. This is an attempt to create exhaustive database by identifying maximum possible number of attributes for robot manipulators. The coding scheme and the selection procedures, mathematical and graphical, are illustrated with example.
Preventive maintenance is applied to improve the device availability or decrease the repair costs when the device failures are in deterioration (or aging) phase. Preventive maintenance can be made more efficient by periodic monitoring wherein the state of deterioration can be assessed. This leads to the notion of condition-based maintenance. In this paper, we study the condition-based maintenance, and derive closed-form expressions of system availability when the device undergoes both deterioration as well as Poisson type failures. These closed-form solutions enable us to find faster algorithms to determine the optimal inspection policy.
A study on the steps to follow in linguistic decision analysis is presented in a context of multi-criteria/multi-person decision making. Three steps are established for solving a multi-criteria decision making problem under linguistic information: (i) the choice of the linguistic term set with its semantic in order to express the linguistic performance values according to all the criteria, (ii) the choice of the aggregation operator of linguistic information in order to aggregate the linguistic performance values, and (iii) the choice of the best alternatives, which is made up by two phases: (a) the aggregation of linguistic information for obtaining a collective linguistic performance value on the alternatives, and (b) the exploitation of the collective linguistic performance value in order to establish a rank ordering among the alternatives for choosing the best alternatives. Finally, an example is shown.
By a linguistic variable we mean a variable whose values are words or sentences in a natural or artificial language. For example, Age is a linguistic variable if its values are linguistic rather than numerical, i.e.,young, not young, very young, quite young, old, not very old and not very young, etc., rather than 20, 21,22, 23, In more specific terms, a linguistic variable is characterized by a quintuple (L>, T(L), U,G,M) in which L is the name of the variable; T(L) is the term-set of L, that is, the collection of its linguistic values; U is a universe of discourse; G is a syntactic rule which generates the terms in T(L); and M is a semantic rule which associates with each linguistic value X its meaning, M(X), where M(X) denotes a fuzzy subset of U. The meaning of a linguistic value X is characterized by a compatibility function, c: U → [0,1], which associates with each u in U its compatibility with X. Thus, the compatibility of age 27 with young might be 0.7, while that of 35 might be 0.2. The function of the semantic rule is to relate the compatibilities of the so-called primary terms in a composite linguistic value-e.g., young and old in not very young and not very old-to the compatibility of the composite value. To this end, the hedges such as very, quite, extremely, etc., as well as the connectives and and or are treated as nonlinear operators which modify the meaning of their operands in a specified fashion. The concept of a linguistic variable provides a means of approximate characterization of phenomena which are too complex or too ill-defined to be amenable to description in conventional quantitative terms. In particular, treating Truth as a linguistic variable with values such as true, very true, completely true, not very true, untrue, etc., leads to what is called fuzzy logic. By providing a basis for approximate reasoning, that is, a mode of reasoning which is not exact nor very inexact, such logic may offer a more realistic framework for human reasoning than the traditional two-valued logic. It is shown that probabilities, too, can be treated as linguistic variables with values such as likely, very likely, unlikely, etc. Computation with linguistic probabilities requires the solution of nonlinear programs and leads to results which are imprecise to the same degree as the underlying probabilities. The main applications of the linguistic approach lie in the realm of humanistic systems-especially in the fields of artificial intelligence, linguistics, human decision processes, pattern recognition, psychology, law, medical diagnosis, information retrieval, economics and related areas.
PRUF - an acronym for Possibilistic Relational Universal Fuzzy - is a meaning representation language for natural languages which departs from the conventional approaches to the theory of meaning in several important respects. First, a basic assumption underlying PRUF is that the imprecision that is intrinsic in natural languages is, for the most part, possibilistic rather than probabilistic in nature. Second, the logic underlying PRUF is not a two-valued or multivalued logic, but a fuzzy logic, FL, in which the truth-values are linguistic, that is, are of the form true, not true, very true, more or less true, not very true, etc. , with each such truth-value representing a fuzzy subset of the unit interval. Third, the quantifiers in PRUF - like the truth-values - are allowed to be linguistic, i. e. may be expressed as most, many, few, some, not very many, almost all, etc. Based on the concept of the cardinality of a fuzzy set, such quantifiers are given a concrete interpretation which makes it possible to translate into PRUF propositions exemplified by ″Many tall men are much taller than most men,″ ″All tall women are blonde is not very true,″ etc.
A fuzzy set is a class of objects with a continuum of grades of membership. Such a set is characterized by a membership (characteristic) function which assigns to each object a grade of membership ranging between zero and one. The notions of inclusion, union, intersection, complement, relation, convexity, etc., are extended to such sets, and various properties of these notions in the context of fuzzy sets are established. In particular, a separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
This paper deals with the problem of scheduling imperfect preventive maintenance (PM) of some equipment. It uses a model due to Kijima in which each application of PM reduces the equipment's effective age (but without making it as good as new). The approach presented here involves minimizing a performance function which allows for the costs of minimal repair and eventual system replacement as well as for the costs of PM during the equipment's operating lifetime. The paper describes a numerical investigation into the sensitivity of optimum schedules to different aspects of an age-reduction model (including the situation when parts of a system are non-maintainable—i.e., unaffected by PM).
Maintenance management of industrial equipment is an important but still relatively neglected business function. This paper identifies and discusses the most important elements of its decision making environment. As such the paper contributes to the structuring of the maintenance management area and it provides a frame of reference for further research in maintenance policy optimization. The paper starts with a brief description of maintenance management in a business context. In the remainder of the paper three parts may be distinguished. The first addresses the system design aspects of maintenance management in the broader operations management environment, the second examines the most important issues in maintenance decision making and the last part reviews the managerial tools available for decision making in this area. An extensive list of references is provided.
Efficient maintenance policies are of fundamental importance in system engineering because of their fallbacks into the safety and economics of plants operation. When the condition of a system, such as its degradation level, can be continuously monitored, a Condition-Based Maintenance (CBM) policy can be implemented, according to which the decision of maintaining the system is taken dynamically on the basis of the observed condition of the system.In this paper, we consider a continuously monitored multi-component system and use a Genetic Algorithm (GA) for determining the optimal degradation level beyond which preventive maintenance has to be performed. The problem is framed as a multi-objective search aiming at simultaneously optimizing two typical objectives of interest, profit and availability. For a closer adherence to reality, the predictive model describing the evolution of the degrading system is based on the use of Monte Carlo (MC) simulation. More precisely, the flexibility offered by the simulation scheme is exploited to model the dynamics of a stress-dependent degradation process in load-sharing components and to account for limitations in the number of maintenance technicians available. The coupled (GA[plus ]MC) approach is rendered particularly efficient by the use of the ‘drop-by-drop’ technique, previously introduced by some of the authors, which allows to effectively drive the combinatorial search towards the most promising solutions.
All manufacturing companies choose to compete in the market based on some competitive priorities like cost, quality, flexibility and other priorities, depending upon their manufacturing capabilities. Equipment maintenance being an integral part of manufacturing, can influence these competitive priorities and hence the business strategy directly in a negative or positive way. Over a period of time, there had been significant developments in the field of manufacturing and maintenance. These are in the areas of technology, concepts, methodologies, and philosophies. Examples are Advanced Manufacturing Technologies (AMT), JIT, Total Productive Maintenance (TPM), and Outsourcing. Maintenance, directly influenced by these developments, has risen from a mere tactical to a more strategic level. Hence, there is a growing need to study the relationship between business and maintenance strategies. The paper is supported by a survey conducted in a sample of about 150 companies within Belgium and to some extent in the Netherlands. In this paper, our empirical study investigates whether companies with different competitive priorities pursue different maintenance strategies. The results indicate that quality competitors have more pro-active maintenance policies, better planning and control systems, decentralized maintenance organization structures when compared to others. They manage maintenance much more effectively when compared to others. There is also a difference in the distribution of AMT usage, automation, maintenance personnel (management/supervision and technicians), expenses and budget figures. Quality competitors have more AMT usage, automation, maintenance personnel and spend more on budget, followed by cost and flexibility competitors.
Best maintenance practices in communications networks management are benchmarking standards that, if carefully implemented, will enhance the integrity, reliability and maintenance costs of communications networks. This paper defines best maintenance practices in communications network management within a concise framework encompassing measurable performance-level goals as well as methods and procedures needed to achieve these goals. The best maintenance practice recommendations of this paper cover many segments of communications networks and services, including wireline and wireless networks as well as multiple network spaces and technologies. The paper also outlines certain recent trends in network maintenance and provides specific recommendations for action to be taken to ensure that best network maintenance practices are implemented and maintained.