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The role of maintenance in improving companies’ productivity and profitability
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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.
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... In order to deal with the group sorting conflict of the proposed GELECTRE-SORT, we further explore the consensual GELECTRE-SORT model, which can effectively utilize group evaluations for handling incomparable complex classes. (2) For measuring the consensus of sorting results, we firstly design the agreeing the credibility matrix of central profiles to depict the consensus of hierarchical structure of the classes. Meanwhile, we construct the 0-1 matrix for simplifying the cred-ibility matrix of central profiles. ...
... With respect to these two assignment rules, there exists 3 different outranking relations when comparing x t and cp j : (1) x t is indifferent to at least one central profile of a class. (2) x t is incomparable to at least one central profile of a class. (3) x t is neither indifferent nor incomparable to any central profiles. ...
... As the automation level and equipment intelligence rise, machines play an increasingly prominent role in the production. Then, providing a suitable maintenance management strategy for the machines can ensure the safe steady-state operation of the company, fulfill orders in time, and improve the production efficiency [2] . Therefore, the machine maintenance management strategy has become the core problem in enterprise production and operation management. ...
... The importance of the maintenance function has increased, due to its role in keeping and improving availability, performance efficiency and product quality. Therefore, equipment care has become very important [3][4][5]. In principle, maintenance simply consists of keeping equipment in working condition. ...
... The era after World War II saw increased mechanization due to industrial labour shortages and a rise in demand for different products. Availability, reliability, longevity of machines and cost, therefore became significant considerations for achieving business goals (Alsyouf, 2007). Losing a day's output due to unplanned stoppages can only be recovered by incurring extra costs such as overtime working, rework, and sometimes loosing valued clients to competitors. ...
The need to manage machine maintenance effectively has gained more importance due to the high rate of
changing operational technologies, changing market demands, increased emphasis on employee safety, and new environmental
legislation. To demonstrate the purpose of maintenance in the manufacturing value chain, the study sought to investigate the
relationship between machine maintenance type and quality of output as well as to establish whether machine maintenance
contributes to quality of output among Ghanaian manufacturing firms. Data was collected from 150 manufacturing firms in Tema
and Accra Metropolis by using questionnaire and analyzed with SPSS and SmartPLS software. The findings showed significantly
direct relationship between all the maintenance types, except corrective maintenance, and quality of output. Therefore, if a company
minimizes breakdown maintenance, quality defects are also minimized. Hence, adopting preventive maintenance help reduce cost
of repairs and unplanned stoppages in the production process.
... Since software maintenance is an ongoing process with the aim to keep software useful, the imperative in software maintenance is to reach managed process that will reduce errors through the software life cycle (Banker et al., 2002). In addition, managed maintenance process increases credibility and viability of software organization that provides maintenance, and also has impact on business performance aspects such as productivity and profitability (Alsyouf, 2007). Because of high costs of maintenance, maintenance processes are promising area for gaining competitive advantage. ...
... For example, a Swedish paper mill company was saved about $0.975 million per year by having an efficient maintenance strategy. The maintenance strategy avoids all unplanned shutdowns and poor quality products [13]. The challenges of maintenance equipment are still the main issues due to several factors including competition, complexity, and cost [14]. ...
Predictive Maintenance (PM) is a major part of smart manufacturing in the fourth industrial revolution. The classical fault diagnosis approach for complex systems such as an electromechanical system is not effective. Taking the advantage of the successful implementations of PM together with Deep Learning (DL) methods replaces the conventional diagnosis methods with modern diagnosis methods. This study intends to aid experts, engineers, and technicians in different electromechanical systems in comprehending how the PM used DL methods to find the multi-fault diagnosis. In this direction, this paper presents a comprehensive review of recent works of DL techniques that are applied to PM for electromechanical systems by classifying the research according to equipment, fault, parameters, and method. To perform the review, 30 papers that are published in proceedings and journals are reviewed within a time window between the years 2016 to 2022. In the context of the electromechanical system, it is observed that motors are the most equipment selected for PM. Moreover, stator winding faults are found to be less selected than bearing for diagnosis of the unhealthy status of the motor. In terms of DL methods, the study reveals that AE, LSTM, and CNN are mostly used. In addition, poorly mixed models of DL methods are also noticed. Finally, finding the optimal design variable of the DL architecture was not widely explored.
... Since software maintenance is an ongoing process with the aim to keep software useful, the imperative in software maintenance is to reach managed process that will reduce errors through the software life cycle (Banker et al., 2002). In addition, managed maintenance process increases credibility and viability of software organization that provides maintenance, and also has impact on business performance aspects such as productivity and profitability (Alsyouf, 2007). Because of high costs of maintenance, maintenance processes are promising area for gaining competitive advantage. ...
... Further, the authors highlighted that the use of sensor-networked dynamic systems in maintenance can lead to changes in FM decision-making processes and knowledge management. Maintenance has progressed from failure-based maintenance to predictive maintenance (PdM), and it is now realized as the essence of a process-oriented "holistic" approach (Alsyouf, 2007). Over the last few years, there has been a significant shift in the approach to maintenance management, with a strong emphasis on the value of innovation (Goyal & Pitt, 2007). ...
Maintenance management is an important function in Facilities Management (FM). Industries moved to preventive maintenance to counteract the inefficiencies of reactive maintenance, and further evolved into predictive maintenance (PdM). The demand for Industry 4.0-enabled PdM for FM has risen as a result of the industrial revolution and the dynamic nature of the FM industry. There are technology, investment, data, employees, integration, standardization, communication and security-related challenges in applying the Industry 4.0 concept for carrying out effective PdM under FM, which needs proper solutions. Thus, the study aimed at identifying strategies to successfully implement the Industry 4.0 concept for effective PdM in FM. The qualitative research approach was undertaken to accomplish the aim. A comprehensive literature review followed by 15 semi-structured interviews was carried out with experts in the maintenance sector who have Industry 4.0 knowledge. The data was collected from experts in Australia, Qatar, Dubai, Singapore, and Sri Lanka, and analyzed through code-based content analysis using NVivo 12. The research identified strategies to overcome technology, investment, data, employees, integration, standardization, communication and security-related challenges faced by facilities managers in applying the Industry 4.0 concept for carrying out PdM. Integrating Industry 4.0 along with PdM could be a game-changer for maintenance practitioners in the FM sector, allowing them to implement a real-time and failure-free maintenance approach that improves overall maintenance effectiveness and retains them ahead of the competition.
Complex data requires advanced analytics methods. In both science and industry, with the ever-increasing amounts of rich and large datasets available, advanced data analytics capabilities are required. Depending on the task at hand, several different techniques and methods can be used to analyze complex data (e.g., multivariate time series, log data, multimodal sensor data). In this chapter, we introduce approaches and methods for advanced analytics on complex industrial data. In particular, we focus on three exemplary methods for modeling and analyzing complex data, i.e., analytics for fault diagnosis, graph signal processing, and pattern mining on networks and graphs. We introduce the general approaches and methods and discuss their implementation in detail for an extended context. From a data perspective, we cover both sequential, i.e., time series, and relational, i.e., graph and network data, also bridging between both by analyzing signals on graphs. Besides setting the stage for the important theoretical background and concepts, we outline, in particular, the perspective on industrial applications and provide specific examples of the application of the presented methods in real-world industrial contexts, i.e., using complex industrial data.KeywordsDeep learningGraph miningLocal pattern miningComplex network analysisTime series analysisMultivariate signals
Penelitian ini bertujuan untuk menganalisis faktor-faktor yang menyebabkanpemeliharaan mesin di P.G Madukismo belum optimal. Pemeliharaan mesin yang dilakukanP.G Madukismo selama 6 bulan belum dapat menekan jam berhenti mesin. Tahun 2016 jamberhenti mesin P.G Madukismo yang direncanakan sebesar 88,8 jam, namun kenyataannyajam berhenti mesin P.G Madukismo mencapai 179,44 jam selama musim giling.Penelitian ini merupakan penelitian kualitatif dengan pendekatan studi kasus.Pengumpulan data dilakukan dengan wawancara, observasi dan dokumentasi. Data yangdikumpulkan kemudian dianalisis menggunakan tahap reduksi, penyajian data dan penarikankesimpula. Hasil penelitian ini menunjukkan bahwa faktor utama penyebab pemeliharaanmesin belum optimal karena umur manfaat mesin telah habis dan preventive maintenanceyang dilakukan tidak dapat mengganti seluruh komponen mesin yang mengalami kerusakanatau aus. Selain itu, P.G Madukismo juga belum memiliki SOP terkait pemeliharaan mesin.Upaya yang telah dilakukan untuk mengoptimalkan pemeliharaan mesin yaitu preventivemaintenance yang dilakukan tidak hanya diluar musim giling tetapi juga saat musim gilingdan memberikan pelatihan kepada karyawan untuk meningkatkan kemampuan karyawan.
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).
Shovel maintenance for enhanced productivity in mining operations is discussed. Improved reliability and reduced maintenance requirement of shovels are attributed to improved design elements. Availability of enterprise resource planning (ERP) software packages that offer maintenance and logistics modules allow equipment related planning, costing, and scheduling activities throughout the mining industry. Specialized jumbo-sized mechanical tools to assist maintenance on massive machines is also presented as an essential element of an effective maintenance program.
This article provides a bridge across the information and communication gaps that currently exist between cost-conscious business managers and technically oriented maintenance personnel. The concepts provided here are intended both to give business managers a crash course in 'maintenance thinking' and to provide maintenance personnel with some insights into the process of managerial decision making. A real-world example of the approach applied to automobile manufacturing is included.
The maintenance function in many manufacturing companies is often regarded as merely an inevitable money-spending cost center, first of all subjected to an effective cost reduction. But this is in many cases a substantial underestimation of the role and real influence of maintenance in the overall company results. A better understanding of the true relationship between maintenance efforts and the economic results of a firm is often the first step toward giving maintenance and availability performance their proper roles in the hierarchy of management activities. This paper proposes some simple models to ease the communication between top management and the maintenance people. Not only the inner but also the outer effectiveness of the maintenance function is taken into account.
Purpose
– This paper, originally published in 1995, aims to focus on the importance of performance measurement.
Design/methodology/approach
– Focuses on the process of performance measurement system design, rather than the detail of specific measures. Following a comprehensive review of the literature, proposes a research agenda.
Findings
– The importance of performance measurement has long been recognized by academics and practitioners from a variety of functional disciplines.
Originality/value
– Brings together this diverse body of knowledge into a coherent whole.