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Maintainability analysis in shaving blades industry: a case study
Abstract
Purpose
The purpose of this paper is to provide results for a complete maintainability analysis utilizing data sets from a production system in a shaving blades division of a large high-tech razor manufacturer. Through the illustrated case study, the authors demonstrate how to spot improvement points for enhancing availability by carrying out an equipment effectiveness analysis.
Design/methodology/approach
Descriptive statistics of the repair data and the best fitness index parameters were computed. Repair data were collected from departmental logs, and a preliminary screening analysis was conducted to validate their usefulness for the indicated period of 11 months. Next, the maintainability and repair rate modes for all the machines of the production system were calculated. Maintainability and availability estimations for different time periods that took in account the overall system were obtained by trying out and selecting an optimum statistical model after considering of several popular distributions.
Findings
Out of the five considered machines in the system, two particular units received about half of the repairs (M2 and M3). The time to repair follows a loglogistic distribution and subsequently the mean time to repair is estimated at 25 minutes at the machine level. Repair time performance is approximated at 55 minutes if the availability of the system is to attain a 90 percent maintainability.
Originality/value
This study is anticipated to serve as an illuminating effort in conducting a complete maintainability analysis in the much advertised field of shavers, for which on the contrary so little has been published on operational availability and equipment effectiveness. The case study augments the available pool of sources where executing maintainability studies is highlighted usually under the direction of combined total quality management and total productive maintenance programs.
... Kadyan and Kumar [29] studied the operational behavior of B-Pan crystallization system in sugar industry based on system availability using Markovian approach. Tsarouhas and Besseris [30] carried out maintainability analysis in shaving blades industry. Tsarouhas and Makrygianni [31] developed a framework for maintenance and combat readiness management of a jet fighter aircraft. ...
... Using the initial conditions and taking t → ∞ , Eqs. (30)(31)(32)(33) get reduced as follows: ...
The main aim of this study is to analyze the application of reliability, availability, maintainability and dependability in identification of most sensitive subsystem of evaporation system in sugar plant. For this analysis, transition diagram of all subsystems is drawn and respective Chapman–Kolmogorov differential equations are derived using Markov birth–death process. All failure and repair rates of each subsystem are exponentially distributed. Various measures of system effectiveness like mean time between failures, mean time to repair and dependability ratio for all the three subsystems are also computed. Sensitivity analysis of system reliability is also performed. The reliability and maintainability are estimated at various time instants. Analysis of all the subsystems shows that sulphited syrup is highly sensitive from reliability point of view. The derived measures are shared with system designers for their active deliberation.
... Tsarouhas and Besseris [6] developed a methodology based on TTR data to conduct the maintainability analysis in the shaving blades industry. Pandey et al. [7] conducted a reliability analysis and failure rate evaluation for critical subsystems of the dragline. ...
The present study is designed to develop an efficient stochastic model to optimize the performance of paper manufacturing plants (PMP) using nature-inspired algorithms. The paper manufacturing plant is a very complex entity configured using several subsystems. All the subsystems configured in the series structure and the failure of anyone causes the complete system failure. To achieve the objective of the proposed study, initially RAMD investigation of each subsystem and a complete power plant is performed and later a stochastic model is developed for performance prediction of the paper plant using nature-inspired algorithms. The Markov birth–death process is used to develop the Chapman–Kolmogorov differential-difference equations. Simple probabilistic arguments are used to simplify the proposed stochastic model. All the failure and repair rates are considered exponentially distributed random variables. The random variables are statistically independent. The repairs are perfect and sufficient repair facilities are available in the plant. Various system effectiveness measures are derived for a particular case at various population sizes at several iterations. The numerical results highlight the importance of the proposed model.
... Tsarouhas and Arvanitoyannis (2010), applied the normal distribution to determine the failure times and the logistic distribution for the repair times, with the aim of identifying the best fit of failure data in a reliability study for the packaging of beer production. Tsarouhas and Besseris (2017), tested and selected an optimal statistical model after considering several distributions, allowing them to make estimates of availability for different periods of time. Later, Tsarouhas (2018) conducted an investigation to determine which probability distribution provides the best fit to characterize the failure pattern at the levels of machinery and production line. ...
Purpose: This article seeks to establish a statistical analysis to estimate the time of stoppages in a stamping line, which have a high variability that generates an unreliable scenario for the production program. Likewise, this document shows the methodological sequence to carry out a statistical analysis in a case study at an industrial level, considering variables of a real scenario.Design/methodology/approach: The methodological sequence is divided into five stages. Initially, the information of the stamping process was collected, later the types of stoppage were categorized according to the characteristics of the process. A collection of historical data information on stoppage times was carried out. With the information collected, the percentage frequency of occurrence of stops due to tool changes and incidents in the process was determined, and they were characterized by a Weibull distribution. Finally, to verify the effectiveness of the downtime behavior, a model was developed to simulate the availability of the stamping line in the Vensim Ple ® program.Findings: The model showed that the frequency analysis and the Weibull distribution obtained a similar behavior to reality. The study verified that it is necessary to establish a categorization of the characteristics of the downtimes, according to the characteristics of the pieces produced to evaluate the information, in this way, the times of change by tooling were established through a frequency of use and the stoppages by additional incidences to the process were better.Research limitations/implications: The basis for this study is the reliability of the information, especially in the data record. It has the disadvantage that the bias of the analyst is present when the information is recorded and analyzed.Practical implications: The methodology presented in this article is a reference for industrial applications in which it is required to establish improvement scenarios based on the reduction of stoppages present in the production lines.Originality/value: The importance of this study is that it was possible to establish a suitable workload allocation in the presses to optimize production.
... Tsarouhas [10] statistically analysed the reliability and availability of food production line. Tsarouhas [11] used FMEA methodology along with statistical analysis in RAM investigation of wine packaging plant. Dahiya et al. [12] proposed a numerical method approach for reliability analysis of complex industrial systems. ...
The purpose of this paper is to provide results for reliability, availability and maintainability (RAM) measures to improve the operational performance of a soft water treatment and supply plant (SWTS-Plant) through the illustrative case study. RAM analysis of SWTS plant installed in a high-rise society ABC, Jaipur was performed. The descriptive analysis of time to failure and repair has been made along with trend analysis and goodness-of-fit test. The best fitted distributed and parameters have been identified from the existing theoretical distributions using the maintenance data of ABC plant. Reliability and maintainability measures also calculated for the entire plant. It is observed that (i) the plant availability decline from 97.96% to 92.67% (ii) failures of five subsystems dominant with 81.5 % failures and (iii) average failure rate is 937.4 minutes. This study will be supportive to identify the occurring complications in the plant.
... Taj et al. [19] have studied a probabilistic model of a cable plant subsystem with priority to repair over preventive maintenance. Tsarouhas and Besseris [20] have studied maintainability analysis in shaving blades industry: a case study. ...
The present paper discuss the reliability characteristics of computer network system consisting of the devices load balancer, distributed database servers and a centralized server configured as series parallel system containing three subsystems. Subsystem 1: load balancer (LB) a device that act as a medium of channeling request to servers and receiving request or response from servers. Subsystem 2: identical distributed database servers (DDS) I, II and III connected in parallel, working under 2-out-of-3: G: policy, which manages and store some part of application data and Subsystem 3: centralized distributed database server (CDDS), which takes care of all the application data in DDS. Through the transition diagram, system of first-order partial differential equations are derived and solved using supplementary variable techniques, Laplace transforms and copula method. All failures are assumed to be exponentially distributed, whereas repairs follow two types of distributions; general distribution and Gumbel–Hougaard family copula, partial failures are repaired by general distribution while complete failures are repaired by copula distribution. The objective is to obtain the expressions for availability, reliability, mean time to failure (MTTF) and cost function. Computations for reliability measures are taken as particular case by evaluating: reliability, availability, MTTF and cost analysis, so as to capture the effect of both failure and repair rates to reliability measures. The results of the computations are presented in tables and graphs. The analysis of the results obtained with respect to the availability and expected profit indicates that copula repair policy is reliable than general repair policy.
... Modern manufacturing systems consist of advanced engineering schemes with elevated technology that ought to operate for 24 h in a day, 7 days in a week and 365 days in a year (Gupta et al., 1988;Windmark et al. (2012); Peng and Zhu, 2017;Tsarouhas and Besseris, 2017). By emphasising the significance of bottleneck machines in production lines, authors have called for more attention to the mean downtime per year of equipment in engineered systems (see also Fuerst et al., 1991;Fox et al., 2008;Al-Chalabi et al., 2014;Koussaimi et al., 2016;Ossai et al., 2016;Nwanya et al., 2017). ...
Purpose
Downtime is a process parameter that substantially impacts on the operating hours and results in production losses, thus motivating maintenance engineers to control process plants. Notwithstanding, the impacting nature of process equipment failure on the operating hours in bottling plants remains inadequately examined. In this paper, the cause-and-effect analysis was used to establish the root cause of the downtime problem and Pareto analysis employed to justify the greatest opportunities for improvement in reducing downtime and increasing reliability levels. Weibull analysis is then conducted on the industrial setting. Novel aspect ratios are proposed.
Design/methodology/approach
Using the Weibull failure function of machines as a principal facilitator to produce failure predictions, the downtime behaviour of a process plant was modelled and tested with practical data from a bottling process plant. This research was conducted in a Nigerian process bottling plant where historical data were examined.
Findings
The analysis of the results shows the following principal outcome: First, the machines with the highest and least downtime values are 2 and 5, respectively, with correspondingly mean values of 22.83 and 4.39 h monthly. Second, the total downtime 92.05 and 142.14 h for the observed and target downtime, with a coefficient of determination of 0.5848 was recorded. Third, as month 1 was taken as the base period (target), all the machines, except M5 had accepted performance, indicating proper preventive maintenance plan execution for the bottling process plant. Availability shows a direct relationship between the failure and uptime of the machines and the downtime impacts on production. Two machines had random failure pattern and five machines exhibited a wear-out failure pattern and probably due to old age and wear of components in the machines.
Originality/value
The major contribution of the paper is the Weibull modelling in a unique application to a bottling plant to avoid current practices that use reliability software that is not easily accessible.
The prominent objective of present study is to develop an efficient mathematical model for performance optimization of stock preparation unit of paper plants using the concept of redundancy. Stock preparation in paper manufacturing involves converting raw stock into finished stock for the paper machine. This process involves several subsystems like storage tanks, repulping/Slushing, deflaking, storage and mixing chests, and the paper machine itself in various redundancy strategies. For the system performance analysis, a mathematical model is developed using Markov birth death process along with reliability, availability, maintainability and dependability (RAMD) investigation of components. The Chapman-Kolmogorov differential-difference equations derived under the exponential behavior of failure and repair rates. The prediction of prominent system effectiveness measure is made using genetic algorithm and particle swarm optimization at various population sizes. Decision matrices are derived for a particular value of parameters. It is observed that predicted optimal availability of stock preparation unit is 0.9207 at a population size of 2500 after 80 iterations. It is revealed that genetic algorithm outperformed over particle swarm optimization in availability prediction of stock preparation unit. The derived results are helpful for system designers and maintenance personnel for effective decision-making for plant operations.
The main objective of the present study is to investigate the reliability and maintainability of a piston manufacturing plant. For this analysis, data on time to repair and the number of failures have been collected for 2 years. The descriptive analysis of the subsystems has been done along with trend and serial correlation testing. The best‐fitted repair and failure time distributions among Weibull, normal exponential, and lognormal distributions have been investigated. The useful parameters corresponding to best‐fitted distribution have been estimated using U‐statistics methodology and NHPP‐PLP. The reliability, availability, and hazard rates of the entire plant were calculated. The results are stored numerical and graphical concerning time to highlight the importance of the study. The model is useful to assess the anticipated time for planning a maintenance schedule of the plant. This study will be very helpful in terms of identifying the occurrence of failures in plants and solving them.
A sugar manufacturing plant is a complex industrial system having five subsystems arranged in a series configuration and each subsystem followed a different failure rate. Upon ensues of a random failure, the failed subsystem stops working and forces the complete system to stop and results in a downstate of the plant. The impact of downstate directly influences the production of plant and its reliability. Here, a reliability and maintainability analysis of the sugar manufacturing plant has been carried out at the subsystem and plant level. Data collection has been performed for six months from the sugar plant and descriptive statistical analysis has been made for time to repair and time between failures. The best-fitted distribution and parameters were determined along with trend and serial correlation analysis to attain the best performance of the plant. Additionally, graphs for reliability and hazard rate modes for five subsystems and the entire plant were depicted. The suggested models might be a suitable tool towards (a) considering the recent conditions, and (b) forecasting reliability for refining the sugar manufacturing plant by applying proper maintenance policy.
The competitive global scenario faces the corresponding impacts such as difficulties in scheduling and loading, high tooling and equipment investment, enormous scrap availability, complex to control the quality, and extensive setup time. So, a higher level of connectivity is required in between the design and manufacturing activities to raise the profitability of the firms and enrich the product support design. In any manufacturing firm, poor reliability causes failure availability in all stages, namely, design, construction, planning, and maintenance, etc. In this research work, RAM is analyzed from the Weibull distribution based Mean time to repair (MTTR) and mean time to failure rates (MTTF) for the ten different industries. The measured RAM performances are optimized by the Imperialist competitive algorithm (ICA) by the application of the rank order clustering (ROC) method. The failure rates are clustered and ranked by using the rank order clustering method. Besides, the cost and RAM performance values are predicted by ICA and hybrid ROC method, and such a proposed algorithm is mathematically modeled in the Mat Lab platform. Hence from the evaluation, the proposed method scores better industrial performances than the actual and other implemented methods
The aim of the present study is to offer results of reliability, availability, maintainability and dependability analysis of a microprocessor system. A microprocessor is designed with the help of seven subsystems including input, terminal, processor, main memory disk, addressing modes, disk controller and disk drives. Reliability, availability, maintainability and dependability analysis has been performed for all the subsystems. For analysis purpose, state transition diagram has been designed for all subsystems and using Markov birth–death process governing equations has been derived. All random variables are exponentially distributed, i.e., follows constant failure rate. Mean time between failures, mean time to repair, availability, reliability, maintainability and dependability ratio parameters for all the subsystems are computed. The reliability and maintainability are estimated at various time instants.
Purpose
The demand of cement in India is expected to increase rapidly as the government has been giving immense boost to various housing facilities, infrastructure projects, road networks and railway corridors. One of the ways to meet this rise in the demand of cement is to increase the capacity utilization of the existing cement plants by improving their availability. The availability of a cement plant can be improved by avoiding failures and reducing maintenance time through reliability, availability and maintainability (RAM) analysis of its subsystems. The paper aims to discuss this issue.
Design/methodology/approach
The data related to time between failure (TBF) and time to repair (TTR) of all the critical subsystems of a cement plant were collected over a period of two years for carrying out RAM analysis. Trend test and serial correlation test were performed on TBF and TTR data to verify whether these data are independent and identically distributed or not. Afterwards, the authors use EasyFit 5.6 professional software to find best-fit distribution of TBF and TTR data and their parameters. The effectiveness of a preventive maintenance policy was evaluated by simulating the real and proposed systems.
Findings
The results of the analysis show that the raw mill and the coal mill are critical subsystems of a cement plant from a reliability point of view, whereas the kiln is a critical subsystem from an availability point of view. The analysis shows that the repair time of the cement mill should be reduced for improving the availability of the cement plant. The RAM analysis showed that the capacity of the case study company is 17 percent underutilized due to maintenance-related problems and 15 percent underutilized because of management-related problems.
Practical implications
The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Thus, it would serve as a reference for reliability and maintenance managers in deciding maintenance strategies of cement plants as well as in improving their capacity utilization.
Originality/value
The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Even more, using a simulation study, the authors show that preventive maintenance of the cement plant beyond a certain level can be disadvantageous as it leads to an increase in downtime and decrease in availability.
Purpose
The purpose of this paper is to provide results for a complete reliability, availability, and maintainability (RAM) analysis utilizing data sets from a production system in a wine packaging line. Through the illustrated case study, the author demonstrates how RAM analysis is very useful for deciding maintenance intervals, and for planning and organizing the adequate maintenance strategy.
Design/methodology/approach
RAM analysis has been done for each machine by using failures data. The parameters of some common probability distributions, such as Weibull, exponential, lognormal, and normal distributions, have been estimated by using the Minitab software package. An investigation to determine which of these distributions provide the best fit for characterizing the failure pattern at machine and line level has been made. Reliability and maintainability of both wine packaging and its machines has been estimated at different mission times with their best fit distribution. High maintainability issues and potential factors with their potential failure modes were presented, through failure mode and effect analysis process.
Findings
Analysis of the total downtime, breakdown frequency, reliability, and maintainability characteristics of different machines shows that: first, the availability for the wine packaging line was 91.80 percent, and for the remaining 8.2 percent the line is under repair. Second, about two failures per shift are displayed on the line, whereas for the mean time-to-repair (TTR) a failure is 24 minutes. Third, there is no correlation between the time-between-failures and the TTRs for the wine packaging line. Fourth, the main three factors affecting the maintainability process in the production line are: resources availability, manpower management, and maintenance planning procedures.
Originality/value
This study is anticipated to serve as an illuminating effort in conducting a complete RAM analysis in the much advertised field of wine packaging production line which on the other hand so little has been published on operational availability and equipment effectiveness. It can also be useful to serve as a valid data source for winery product manufacturers, who wish to improve the design and operation of their production lines.
Purpose
– Reliability analysis is required to identify the components or subsystems with low reliability for a given designed performance. Life cycle cost analysis helps understand the cost implications over the entire life span of a product. The purpose of this paper is to present a case study describing reliability analysis and life cycle cost optimization of a band saw cutting machine manufactured and used in India.
Design/methodology/approach
– The data required for reliability analysis is collected from the manufacturer and users of band saw cutting machine. The parameters of failure distribution have been estimated by using ReliaSoft’s Weibull++6 software. The life cycle cost is divided into various cost elements such as acquisition cost, operation cost, failure cost, support cost and net salvage value.
Findings
– The results of the analysis show that the components such as band wheel bearing, guide roller bearing, limit switch, carbide pad, hydraulic cylinder oil seal, control panel dial, control panel and solenoid valve are critical from reliability and life cycle cost analysis perspective.
Originality/value
– With certain design changes it is found that the reliability of the system is increased by 15.85 percent while the life cycle cost is reduced by 22.09 percent. The study also shows that the reliability analysis is useful for deciding maintenance intervals.
In this study, the analytical
probability models for an automated serial production system, bufferless that consists of n-machines in series with common transfer mechanism and control system was developed. Both time to failure and time to repair a failure are assumed to follow exponential distribution. Applying those models, the effect of system parameters on system performance in actual croissant production line was studied. The production line consists of six workstations with different numbers of reparable machines in series. Mathematical models of the croissant production line have been developed using Markov process. The strength of this study is in the classification of the whole system in states, representing failures of different machines. Failure and repair data from the actual production environment have been used to estimate reliability and maintainability for each machine, workstation, and the entire line is based on analytical models. The analysis provides a useful insight into the system’s behaviour, helps to find design inherent faults and suggests optimal modifications to upgrade the system and improve its performance.
The Handbook of Maintenance Management and Engineering covers a wide range of topics in maintenance management and engineering. It includes extensive references to the theoretical foundations, recent research and future directions of this important subject. Using applications and examples which reflect the growing importance of maintenance, this book presents readers with an inter-disciplinary perspective on topical issues which affect any organization engaged in manufacturing, process, or service industry, no matter how large or small. Contributors to the book are maintenance experts with both academic and industrial backgrounds, who are able to offer a comprehensive analysis of the subject matter, including both quantitative treatment and discussion of management issues. The Handbook of Maintenance Management and Engineering features both fundamental and applied works from across the whole maintenance spectrum. It will provide professionals with the solutions and management skills needed to evaluate and to continuously improve maintenance systems. This handbook will also be an invaluable resource for researchers and graduate students working in this area.
Purpose
The purpose of this paper is to review the literature on Total Productive Maintenance (TPM) and to present an overview of TPM implementation practices adopted by the manufacturing organizations. It also seeks to highlight appropriate enablers and success factors for eliminating barriers in successful TPM implementation.
Design/methodology/approach
The paper systematically categorizes the published literature and then analyzes and reviews it methodically.
Findings
The paper reveals the important issues in Total Productive Maintenance ranging from maintenance techniques, framework of TPM, overall equipment effectiveness (OEE), TPM implementation practices, barriers and success factors in TPM implementation, etc. The contributions of strategic TPM programmes towards improving manufacturing competencies of the organizations have also been highlighted here.
Practical implications
The literature on classification of Total Productive Maintenance has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of various TPM implementation practices demonstrated by manufacturing organizations globally. It also highlights the approaches suggested by various researchers and practitioners and critically evaluates the reasons behind failure of TPM programmes in the organizations. Further, the enablers and success factors for TPM implementation have also been highlighted for ensuring smooth and effective TPM implementation in the organizations.
Originality/value
The paper contains a comprehensive listing of publications on the field in question and their classification according to various attributes. It will be useful to researchers, maintenance professionals and others concerned with maintenance to understand the significance of TPM.
Purpose
– The purpose of this paper is to provide an overview of RAMS engineering in industry and research.
Design/methodology/approach
– A range of research articles (1988‐2005) covering RAMS engineering is discussed to provide a practical and theoretical overview of RAMS engineering in industry and research.
Findings
– The paper provides information about the current scenario and also about the past scenario of RAMS engineering in research and industry. Research limitations/implications – This paper reviews much of the literature on RAMS engineering. The literature is collected from major journals and conference proceedings, the period covered is from 1988 to 2005. The authors have tried to make it reasonably comprehensive, but those papers which are not included were either inadvertently overlooked or considered peripheral to this survey. In the present work the authors have only considered those articles which have included two or more aspects of RAMS. Practical implications – The paper is a very useful source of information for researchers working in the area of RAMS engineering. Originality/value – This paper offers help to researchers in understanding the current and past status of RAMS.
Purpose – To study the strategic implications of TQM and TPM in an Indian manufacturing set-up and to detail literature reviews to highlight gap areas. To examine the relationship between factors influencing the implementation of TQM and TPM and business performance for the following three approaches in an Indian context: TQM alone; TPM alone; both TQM and TPM together. This is done to extract significant factors for the above three approaches. Design/methodology/approach – Empirical survey-based research on a sample size of 108 manufacturing companies. Uses bivariate correlation and multiple regression analysis techniques to extract significant factors using SPSS. Findings – The research identifies two sets of factors which are critical for the effectiveness of TQM and TPM: universally significant factors for all the three approaches like leadership, process management and strategic planning; and approach-specific factors like equipment management and focus on customer satisfaction. The study also highlights the complexities involved in implementing TQM and TPM together. Practical implications – The emphasis on extracted factors will help companies in realizing greater benefits through TQM and TPM. This study is equally important in a global context also, as companies across the globe are striving to achieve synergy of TQM and TPM. Originality/value – The preparedness/status of Indian manufacturing industry for TQM and TPM implementation, as India is becoming a major sourcing base for the world and there is a paucity of such studies. The study of TQM and TPM in all the three modes simultaneously has not been investigated in the context of developing countries. Such studies are equally important in a global context.
Purpose
The purpose of this paper is to compute reliability, availability, and mean time before failure of the process of a plastic‐pipe manufacturing plant consisting of a ( K, N ) system for various choices of failure and repair rates of sub‐systems. This plant consists of eight sub‐systems.
Design/methodology/approach
In this paper the Chapman‐Kolmogorov differential equations are formed using mnemonic rule from the transition diagram of the plastic‐pipe manufacturing plant. The governing differential equations are solved using matrix method in order to find the reliability of the system with the help of MATLAB software. The same system of differential equations is solved numerically using Runge‐Kutta fourth order method to validate the results obtain by MATLAB.
Findings
The findings in the paper are an analysis of reliability, availability and mean time before failure of plastic‐pipe manufacturing plant has been carried out.
Practical implications
This paper proposes matrix calculus method using MATLAB software to find out the reliability of the plastic‐pipe manufacturing plant. This approach can be implemented to find reliability of other manufacturing plants as well.
Originality/value
The findings suggest that the management of the plastic‐pipe manufacturing plant 's sensitive sub‐system is important to improve its performance.
The evaluation of maintenance strategies is a problem which has been widely tackled. However, it remains a topic worthy of consideration since the economic stakes peculiar to this activity are huge. The work presented in this paper deals with this problem under the point of view of data feedback. A statistical analysis is made from the examination of the forms of the failure rate distribution. The laws resulting from the implementation of a given maintenance strategy inform us about the relevance of the choices representative of this strategy. The construction of these laws from a raw time of repair is a global approach which tends to hide the induced phenomenon. A decomposition of the repair process into phases allows us to better identify the influence of the strategy parameters. The analysis of each elementary phase distribution is interesting since it givesinformation about the performance of the implemented maintenance strategy. Copyright © 2003 John Wiley & Sons, Ltd.
Purpose
– The main aim of this paper is to improve reliability characteristics namely availability, mean time to failure (MTTF), and expected profit of a complex system.
Design/methodology/approach
– The paper discusses the availability of a complex system, which consists of two independent repairable subsystems A and B in (1‐out‐of‐2: F) and (1‐out‐of‐n: F) arrangement respectively. Subsystem A has two identical units arranged in parallel redundancy (1‐out‐of‐2: G), subsystem B has n units in series (1‐out‐of‐n: F) with two types of failure, namely, partial and catastrophic. Except at two transitions where there are two types of repair namely exponential and general possible. The failure and repair time for both subsystems follow exponential and general distributions respectively. The model is analysed under “preemptive‐repeat repair discipline” where A is a priority and B is non‐priority.
Findings
– By employing supplementary variable technique, Laplace transformation and Gumbel‐Hougaard family copula various transition state probabilities, availability, MTTF and cost analysis (expected profit) are obtained along with steady‐state behaviour of the system. Inversions have also been carried out so as to obtain time dependent probabilities, which determine availability of the system at any instant.
Originality/value
– This paper, through a systematic view, presents a mathematical model of a complex system from which the reliability characteristics namely availability, MTTF, and expected profit of a complex system can be improved.
Purpose
– The purpose of this paper is to propose a practical method of performing maintenance in the offshore industry where engineers have to manage problems such as the high cost of operations, assuring an high availability of the plant, safety on board and environmental protection. Indeed an efficient maintenance method it is necessary in order to offer methods and criteria to select the rights maintenance strategies keeping in to account the environmental, safety and production constrains.
Design/methodology/approach
– The paper provides an overview of reliability centered maintenance (RCM) and reliability, availability, maintainability methodologies and an integration of the two methodologies in a particular case study in the oil and gas sector.
Findings
– This paper suggests an improvement of the well-established RCM methodology applicable to industries with high priority level. It is proposed an integration between a reliability analysis and an availability analysis and an application on the offshore oil and gas industry.
Practical implications
– The methodology provides an excellent tool that can be utilized in industries, where safety, regulations and the availability of the plant play a fundamental role.
Originality/value
– The proposed methodology provides a practical method for selecting the best maintenance strategy considering the equipment redundancy and sparing, the asset’s performance over long time scales, and the system uptime, downtime and slowdowns.
Purpose
– The purpose of this paper is to evaluate performance of mobile communication system with reliability measures.
Design/methodology/approach
– The mobile communication system consists of a mobile station (MS), base transceiver station (BTS), base station controller (BSC) and the mobile switching center. The MS is connected to BTS, BTS is connected to BSC and BSC is connected with the mobile switching system. With the help of these stations working, the authors have developed a mathematical model using Markovian approach.
Findings
– Using the supplementary variable technique, the Laplace transformations and Markov process theory, the reliability indices of the mobile communication system are determined.
Originality/value
– In the present work, the authors have developed a mathematical model based on a mobile communication system.
Reliability analysis of a mobile robot system over a period of 34 months was carried out. Most of the failure modes were identified and the descriptive statistics at component level were calculated. Several theoretical distributions were applied and the best fit of failure data was identified. Furthermore, the reliability, probability density functions and hazard rate modes for all components and the entire system were calculated. It was found out that, (a) the encoder and the tires stand for 73.8 % of all the failures of the mobile robot system, (b) for the mobile robot the time-between-failure ranges from 5 to 2128 h, and (c) the highest reliability is observed at the battery, whereas the lowest reliability is observed at the encoder. The proposed method could be a useful tool towards assessing the current conditions, and predicting reliability for improving the mobile robot maintenance policy, and for helping robot manufacturers to improve the design and operation of the system that they manufacture and operate.
?he polypropylene (PP) industry is an important branch of industry with rapid growth and prospects. The production process is complex and requires the continuous operation of the line without failure of equipment to avoid quality problems and maintain the performance of the system. In this study, reliability and maintainability analysis was conducted for PP industry by applying statistical techniques on field failure data. Data collection from the line and their analysis were valid over a long time of 12 months. It was found out that (a) the real operating time of the PP production line (PL) is 92.21%, whereas the rest 7.79% is under repair, (b) the line reliability can be improved if it is focused firstly on workstation auxiliary supplies (WS.8), and then on packing (WS.6), and (c) the maintainability can be improved on the reactor (WS.2), extruder (WS.5), and the entire production line as well.
Purpose
– The purpose of this paper is to provide a literature review of the performance measurement (PM) in maintenance. The authors aim to discuss the background and development of the PM for maintenance, besides defining the concept of performance measures for maintenance and the frameworks developed.
Design/methodology/approach
– A detailed and extensive literature search and study was undertaken by the authors on the concept and definition of PM, performance indicators (PIs), maintenance performance indicators and various performance frameworks. The history and theory of PM over different phases of business and technological developments have been critically examined and analysed in this review paper.
Findings
– This paper reviews and presents the different PIs and PM frameworks like; balanced scorecard (BSC), performance prism, performance pyramid and performance matrix, etc., and identifies their characteristics and shortcomings. After considering related issues and challenges, frameworks and approaches for the maintenance performance measurement (MPM) are also presented, where the emerging techniques like; emaintenance have also been discussed amongst others. More and more industries are applying the balanced and integrated MPM frameworks for their competitive survivability and sustainability.
Practical implications
– The concept, issues and approaches considered for the MPM frameworks can be adapted by the practicing managers, while trying to define and develop an MPM framework for the operation and maintenance activities. The considerations of the advantages and limitations of different frameworks can provide insights to the managers for implementation.
Originality/value
– Some literature reviews on MPM and MPM frameworks are available today. This paper makes an attempt to provide a detailed and relevant literature review, besides adding value in this new and emerging area.
Maintainability is used to improve the performance of the system based on the adequate maintenance activities. In this paper, the maintainability characteristics and the critical machines of the yogurt production line with respect to repair frequency and duration were identified. Descriptive statistics of the repair data were carried out and the best fitness index parameters were determined. Data collection from the production line and their analysis were valid for a period of thirty months. Furthermore, the maintainability and repair rate modes for the entire production line were calculated. Moreover, maintainability for different time periods for all the machines and the line have been estimated on the basis of fitted distribution models. This study is anticipated to serve as a valid data source for yogurt product machinery manufacturers, who wish to improve the design and operation of their production lines.
The scope of this study is to review reliability, availability and maintainability (RAM) analysis in the food industry and aims to identify the critical points of the production systems that should be improved by the operational performance and the maintenance effectiveness. RAM is an engineering tool that addresses operations and safety issues of production lines and aims to identify areas within the system or process where significant improvement can be achieved. Food production lines consist of several machines supplied with a common transfer mechanism and control system that have different failure modes. When a random failure occurs, the failed machine stops and forces most of the line upstream of the failure to operate without processing, whereas the material (raw, intermediate or end‐product) of the line downstream may have to be scrapped because of quality deterioration during the stoppage. The negative failure impact is the drop of line reliability and production rate.
Purpose
– The purpose of this paper is to develop a new approach for computing various performance measures such as reliability, availability, MTBF, ENOF, etc. for any industrial system.
Design/methodology/approach
– Pulping system, the main functionary part of paper industry, is the subject of the study. The interactions among the working components are shown using Petri nets (PNs). Failure and repair rates are represented using triangular fuzzy numbers (TFNs), as they allow expert opinion, linguistic variables, operating conditions, uncertainty and imprecision in reliability information, to be incorporated into system model. The failure rates and repair times of all constituent components are obtained using genetic algorithms (GAs) and then various performance measures are computed using fuzzy Lambda-Tau methodology (FLTM).
Findings
– The proposed methodology provides a better understanding about the behavior of any repairable system through its graphical representation.
Originality/value
– A new approach has been given to compute various performance measures and based on calculated reliability parameters, a structured framework has been developed that may help the maintenance engineers to analyze and predict the system behavior.
Purpose
– Asset intensive process industries are under immense pressure to achieve promised return on investments and production targets. This can be accomplished by ensuring the highest level of availability, reliability and utilization of the critical equipment in processing facilities. In order to achieve designed availability, asset characterization and maintainability play a vital role. The most appropriate and effective way to characterize the assets in a processing facility is based on risk and consequence of failure. The paper aims to discuss these issues.
Design/methodology/approach
– In this research, a risk-based stochastic modeling approach using a Markov decision process is investigated to assess a processing unit's availability, which is referred as the risk-based availability Markov model (RBAMM). RBAMM will not only provide a realistic and effective way to identify critical assets in a plant but also a method to estimate availability for efficient planning purposes and resource optimization.
Findings
– A unique risk matrix and methodology is proposed to determine the critical equipment with direct impact on the availability, reliability and safety of the process. A functional block diagram is then developed using critical equipment to perform efficient modeling. A Markov process is utilized to establish state diagrams and create steady-state equations to calculate the availability of the process. RBAMM is applied to natural gas absorption process to validate the proposed methodology. In the conclusion, other benefits and limitations of the proposed methodology are discussed.
Originality/value
– A new risk-based methodology integrated with Markov model application of the methodology is demonstrated using a real-life application.
Purpose ‐ The purpose of this paper is to make a performance model of a shoe upper manufacturing unit of a shoe manufacturing industry by computing both the availabilities, i.e. time dependent system availability (TDSA) and the long-term availability. Design/methodology/approach ‐ The present work is carried out by developing performance model based on Markov birth-death process. The unit consists of four subsystems. The first order governing differential equations are derived using the mnemonic rule and further solved by adaptive step-size control Runge-Kutta method to calculate the TDSA, while the long-term availability is calculated using normalizing condition, initial boundary conditions and recursive method. Both the availabilities are considered for system's performance criterion. Findings ‐ The subsystem A, i.e. sewing machine is the most critical from maintenance point of view, which has more impact on the system's performance as compare to other subsystems. The repair priorities of other subsystems have also been proposed. Practical implications ‐ These methods can also be used to find out the performance of other manufacturing industries. Originality/value ‐ The results of the present work are very useful for finding the critical subsystem and its effect on the system performance in terms of availability. Further, based on findings the maintenance priorities of various subsystems can be decided.
Today's trend of replacing manually operated vehicles with automated ones will have an impact not only on machine design, working environment and procedures but also on machine breakdown and maintenance procedures. In the harsh environment of underground mines, the transition from manual to automatic operation is believed to fundamentally change the basis for break downs, maintenance and machine design. In this paper, differences and similarities between manual and automatic underground loading equipment is analysed from a reliability point of view. The analysis is based on a case study performed at a Swedish underground mine. In the contrary of common thoughts, this paper proves that there is a difference between the manual and semi-automatic machines and in particular for the transmission, in favour of the manual one. This paper also shows a path for detailed reliability analysis, and the results may be used for improving maintenance programmes for other types of mobile equipment. Copyright © 2013 John Wiley & Sons, Ltd.
Underground mines possess a wide variety of mobile capital intensive equipment. Equipment failures and the associated down time contribute significantly to the overall maintenance, operating and production costs of the mine. With the introduction of computerized maintenance records and data logging, the collection and analysis of accurate and reliable data are much simplified. Hence, a more in-depth reliability and maintenance analysis can be performed.This paper presents a methodology by which maintenance data is quantified using graphical, analytical and statistical tools. Two approaches for analyzing maintenance data are presented. The first approach describes a basic maintenance analysis to determine equipment failure trends. The second approach is a more rigorous procedure which can be used to predict failure trends using statistical based reliability models.This paper illustrates how a basic maintenance analysis can be used to determine equipment availability as well as trends in the equipment operating characteristics. It also discusses how a reliability based maintenance analysis can enhance the basic failure analysis.The data used in this paper is from Load-Haul-Dump (LHD) vehicles operating in a typical underground hardrock mine in the Sudbury mining region in Ontario, Canada. The data is used as an example to describe the maintenance methodology presented in this paper.
Traditional parametric methods for assessing maintainability most often only consider time to repair (TTR) as a single explanatory variable. However, to predict availability more precisely for high availability systems, a better model is needed to quantify the effect of operational environment on maintainability. The proportional repair model (PRM), which is developed based on proportional hazard model (PHM), may be used to analyze maintainability in the present of covariates. In the PRM, the effect of covariates is considered to be time independent. However this assumption may not be valid for some situations. The aim of this paper is to develop the Cox regression model and its extension in the presence of time-dependent covariates for determining maintainability. A simple case study is used to demonstrate how the model can be applied in a real case.
The quantitative analysis, including reliability and maintainability which are of the fundamental issues for the operation management of an automated peach production line, was developed. Descriptive statistics of all the failures at machine and line level were shown, and the most critical machines under failures according to several criteria were determined. The best fit of the failure data between the common theoretical distributions was found and the respective parameters were identified. Moreover, the reliability and hazard rate models for the entire production line were calculated. They both proved to be useful tools to assess the current situation, and to predict reliability, mainly in short term, for upgrading the operation management of the peach production line. It was pointed out that (a) the mean time-to-failure (TTF) is approximately 650min whereas the mean time-to-repair (TTR) a failure amounts to approximately 70min. (b) The failure times follow the logistic distribution whereas the repair times comply with the Weibull distribution, and (c) the repair rate of failure is increasing, thereby implying that the maintenance staff expertise increases with time.
This paper presents a framework to optimise reliability and maintainability (R&M) of a product through modular design. A structured process is developed for incorporating three types of R&M metrics into the modular design. These metrics are failure potential and simplicity of module architecture, maintainability and maintenance commonality between the components, and serviceability of the module. In addition to reliability and maintainability, cost of modularisation is also taken into account for modules selection purpose. The metrics of modularisation costs are cost of interface to join the components, assembly resources requirements, and cost of reusability of modules. We use fuzzy logic and the goal programming models for developing the modular design. An example is presented to demonstrate the application of the proposed methodology.
Purpose
This paper aims to examine the strategic value of reliability and maintainability management in achieving competitiveness and customer satisfaction. It looks into performance metrics for organizational performance and associates reliability and maintainability with such metrics.
Design/methodology/approach
The design strategy is based on using models for reliability and profitability assessment as well as total quality management models to illustrate how performance metrics for organizational performance can be enhanced.
Findings
It shows there is a need to associate models of profitability assessment to reliability and maintainability management. This will help top management to see the strategic value of reliability and maintainability management and, therefore, adopt necessary organizational transformations to support reliability and maintainability goals.
Research limitations/implications
It is important that the role of reliability and maintainability as important strategic variables be recognized and considered in future research that evaluates organizational performance and successes.
Practical implications
The importance of organizational cultural transformation is noted and a transformation of organizational information system to link reliability management to a central information system such as in an enterprise resource planning (ERP) framework is suggested as a process of improving system availability and reliability.
Originality/value
The aim is to have top management perceive reliability and maintainability issues as part of their strategic initiatives. While the value of total quality management in achieving organizational success is well accepted, reliability and maintainability issues are often viewed at the operational level. Yet, they are critical to achieving quality and organizational success.
Purpose – Overall equipment effectiveness (OEE) and process capability (PC) are commonly used and well-accepted measures of performance in industry. These measures, however, are traditionally applied separately and with different purposes. The purpose of this paper is to investigate the relationship between OEE and PC, how they interact and impact each other, and the possible effect that this relationship may have on decision making. Design/methodology/approach – The paper reviews the OEE and PC background. Then, a discrete-event simulation model of a bottling line is developed. Using the model, a set of experiments are run and the results interpreted using graphical trend and impact analyses. Findings – The paper demonstrates the relationship between OEE and PC and suggests the existence of a “cut-off point” beyond which improvements in PC have little impact on OEE. Practical implications – PC uses the capability indices (CI) to help in determining the suitability of a process to meet the required quality standards. Although statistically a Cp/Cpk equal to 1.0 indicates a capable process, the generally accepted minimum value in manufacturing industry is 1.33. The results of this investigation challenge the traditional and prevailing knowledge of considering this value as the best PC target in terms of OEE. Originality/value – This paper presents a study where the relationship between two highly used measures of manufacturing performance is established. This provides a useful perspective and guide to understand the interaction of different elements of performance and help managers to take better decisions about how to run and improve their processes more efficiently and effectively.
Reliability analysis for packaging of beer production over a period of 9-month was carried out. The most important failure modes were identified and the descriptive statistics at failure and machine level were calculated. Several theoretical distributions were applied and best fit of failure data was identified. The reliability and hazard rate models of the failure data were determined to provide an estimate of the current operation management (i.e. maintenance policy, training, spare parts) and improve the line efficiency. It was found out that (a) the availability of the beer filling/capping machine is 94.80%, (b) the failures due to mechanical and pneumatic causes amount to 57.1% of all the failures of the machine, (c) the time-between-failure (TBF) was drastically decreased thereby suggesting that the probability to fail increased and the current maintenance policy should be revised, and (d) the failure times follow the normal distribution whereas the times-to-repair (TTR) a failure comply with the logistic distribution.
The reliability and maintainability of electrical system of drum shearer at Parvade.1 Coal Mine in central Iran was analyzed.
The maintenance and failure data were collected during 19 months of shearer operation. According to trend and serial correlation
tests, the data were independent and identically distributed (iid) and therefore the statistical techniques were used for
modeling. The data analysis show that the time between failures (TBF) and time to repair (TTR) data obey the lognormal and
Weibull 3 parameters distribution respectively. Reliability-based preventive maintenance time intervals for electrical system
of the drum shearer were calculated with regard to reliability plot. The reliability-based maintenance intervals for 90%,
80%, 70% and 50% reliability level are respectively 9.91, 17.96, 27.56 and 56.1 h. Also the calculations show that time to
repair (TTR) of this system varies in range 0.17∼4 h with 1.002 h as mean time to repair (MTTR). There is a 80% chance that
the electrical system of shearer of Parvade.1 mine repair will be accomplished within 1.45 h.
Keywordsdrum shearer–electrical system–reliability–maintenance
The significance of reliability, availability and maintainability (RAM) in recent years increased due to rising energy cost
and the competitive market. These issues have a considerable effect on the energy generation and potential saving as well.
RAM can be assessed by implementing effective software tools generating adequate models. They also provide results visualization
via a tabular and/or graphical representation. Various software tools have been selected, tested and a brief overview drawn.
It has been a wide selection; however, most of the information available has been driven by marketing and sales features.
This work focuses on the main features of several promising complex reliability packages and its target is a balanced assessment
of their main features.
KeywordsReliability-Availability-RAM-Software package
Reliability, availability and maintainability (RAM) analysis of the cheese production line over a period of 17 months was investigated. The best fit of the failure and repair data between the common theoretical distributions was found and the respective parameters were computed. The reliability and hazard rate modes at the entire production line were calculated as well. The models are anticipated to be a useful tool to assess the current conditions, and to predict the reliability for upgrading the maintenance strategies of the production line. It was found out that (a) the availability of the cheese production line is 91.20% and went down to 87.03%, (b) the dominant four failure modes have the 62.2% of all the failures of the cheese production line, and (c) the average of a failure is every 12.5 operation hours and the mean time to repair is 66 min. This analysis will be very useful in terms of identifying both the occurring and latent problems in cheese manufacturing process of and, eventually, solve them.
The reliability and maintainability analysis of an automated mechanical equipment of juice bottling industry for a period of forty-five months at machine, workstation and entire line level was made. The descriptive statistics of failure and repair data, the identification of the most important failure modes, and the determination of the theoretical distributions parameters that best fit to failures data was carried out. Furthermore, the reliability, maintainability, failure rate, and repair rate models of the production line for all workstations and the entire production line were developed. The models could prove to be a useful tool both to assess the current conditions and to predict the reliability for upgrading the operations management policies of the production line. It was pointed out that (a) the availability of the juice production line is 85.66% and the efficiency amounts to 82.10% because the equipment’s failures. (b) The WS1 and WS4 display the most frequent failures and the lowest availability with 94.54% and 96.13%, respectively. Moreover, they show the largest number of different failure modes of the production process due to the complexity of the equipment with 28 and 30 different failure modes respectively. (c) In the production line, a failure occurs every 12.5 h or equivalent to two-failures per day approximately, whereas the mean TTR a failure is approximately two hours per failure. (d) The production line for the TTF follows the Weibull distribution, while the TTR follows the lognormal distribution. This particular methodology can also be utilized in the bottling industry sector by the machinery manufacturers and the manufacturers of bottled products to improve the design and operation management of the juice bottling production line.
The statistical analysis of the bread production line of the failure and repair data at machine and line levels was displayed. The experiment covers a period of twenty-five months. The best fit of the failure data between the common theoretical distributions was found and its parameters were computed. The reliability and hazard rate modes for all machines and the entire production line were calculated as well. The models could prove to be a useful tool to assess the current conditions, and to predict the reliability for upgrading the maintenance policy of the production line. It was pointed out that (a) the availability of the bread production line is 90.74% and went down to 86.76% because the equipment's failures cause an additional production gap in the line, (b) the 53.5% of all failures occurred at the bread machine, cooling tower machine, and volumetric-divider machine, and (c) the machines of the bread production line that displayed increasing hazard rate functions were identified. This analysis will be very useful in terms of identifying the occurring and latent problems in manufacturing process of bread and improve it.
Reliability analysis in an industrial shaving blade unit”, MSc thesis
- V Spyropoulos