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Maintenance management is a vital strategic task given the increasing demand on sustained availability of machines. Machine performance depends primarily on frequency and downtime; therefore, ranking critical machines based on these two criteria is important to determine the appropriate maintenance strategy. The purpose of this paper is to compare two methods, using case studies, to allocate maintenance strategies while prioritising performance based on frequency and downtime or Mean Time to Repair: the Decision Making Grid (DMG) and Jack-Knife Diagram (JKD).

The literature indicates the need for an approach able to integrate maintenance performance and strategy in order to adapt existing data on equipment failures and to routinely adjust preventive measures. Maintenance strategies are incomparable; one strategy should not be applied to all machines, nor all strategies to the same machine.

Compared to the Pareto histogram, the DMG and JKD provide visual representations of the performance of the worst machines with respect to frequency and downtime, thus allowing maintenance technicians to apply the appropriate maintenance strategy. Each method has its own merits.

This work compares only two methods based on their original conceptualisation. This is due to their similarities in using same input data and their main features. However, there is a scope to compare to other methods or variations of these methods.

This paper highlights how the DMG and JKD can be incorporated in industrial applications to allocate appropriate maintenance strategy and track machine performance over time.

Neither DMG nor JKD have been compared in the literature. Currently, the JKD has been used to rank machines, and the DMG has been used to determine maintenance strategies.

The purpose of this paper is to develop an approach for estimating the remaining useful life (RUL) of metropolitan train wheels considering measurement error.

The paper proposes a wear model of a metropolitan train wheel based on a discrete state space model; the model considers the wheel’s stochastic degradation and measurement error simultaneously. The paper estimates the RUL on the basis of the estimated degradation state. Finally, it presents a case study to verify the proposed approach. The results indicate that the proposed method is superior to methods that do not consider measurement error and can improve the accuracy of the estimated RUL.

RUL estimation is a key issue in condition-based maintenance and prognostics and health management. With the rapid development of advanced sensor technologies and data acquisition facilities for the maintenance of metropolitan train wheels, condition monitoring (CM) is becoming more accurate and more affordable, creating the possibility of estimating the RUL of wheels using CM data. However, the measurements of the wheels, especially the wayside measurements, are not yet precise enough. On the other hand, few existing studies of the RUL estimation of train wheels consider measurement error.

The approach described in this paper will make the RUL estimation of metropolitan train wheels easier and more precise.

Hundreds of million yuan are wasted every year due to over re-profiling of rail wheels in China. The ability to precisely estimate RUL will reduce the number of re-profiling activities and achieve significant economic benefits. More generally, the paper could enrich the body of knowledge of RUL estimation for a slowly degrading system considering measurement error.

This paper aims to discuss and bring to the attention of researchers and practitioners the data management issues relating to condition‐based maintenance (CBM) optimization.

The common data quality problems encountered in CBM decision analyses are investigated with a view to suggesting methods to resolve these problems. In particular, the approaches for handling missing data in the decision analysis are reviewed.

This paper proposes a data structure for managing the asset‐related maintenance data that support CBM decision analysis. It also presents a procedure for data‐driven CBM optimization comprising the steps of data preparation, model construction and validation, decision‐making, and sensitivity analysis.

Analysis of condition monitoring data using the proportional hazards modeling (PHM) approach has been proved to be successful in optimizing CBM decisions relating to motor transmission equipment, power transformers and manufacturing processes. However, on many occasions, asset managers still make sub‐optimal decisions because of data quality problems. Thus, mathematical models by themselves do not guarantee that correct decisions will be made if the raw data do not have the required quality. This paper examines the significant issues of data management in CBM decision analysis. In particular, the requirements of data captured from two common condition monitoring techniques – namely vibration monitoring and oil analysis – are discussed.

This paper offers advice to asset managers on ways to avoid capturing poor data and the procedure for manipulating imperfect data, so that they can assess equipment conditions and predict failures more accurately. This way, the useful life of physical assets can be extended and the related maintenance costs minimized. It also proposes a research agenda on CBM optimization and associated data management issues.

The ongoing availability of existing industrial systems/machines depends to a great extent on the form and level of product support. Product support, or the after sale service of a product, is important because it assures the expected function of the product in its operational phase. Product support is affected by a number of factors, including system reliability and maintainability characteristics and the operating environment. The purpose of this paper is to analyze the influence of time independent external factors of industrial systems on product support requirements and spare parts need.

This paper, after discussing the factors influencing product support, describes a method to estimate spare part requirements based on estimation of the actual reliability of a product under the influence of the product‐operating environment using a proportional hazard model. A spare parts estimation software, Spare Management Software (SMS), is used to check the results. Then a case study addresses the management of the spare parts inventory based on the geographical location and required performance of the product.

The lack of good support and critical spare parts can cause the untimely stoppage of a machine/system. The forecasting of product support and spare parts requirements based on the reliability and maintainability characteristics of systems/components, along with influencing environmental factors, is one of the most effective strategies for preventing unplanned stoppages. The operating environment of a system/machine has a considerable influence on the performance of the system and its technical characteristics, such as its reliability, maintainability, and, consequently, availability. Therefore, the system operating environment should be considered when the required support and spare parts estimation is under review.

In this research, the focus is on the estimation of the number of spare parts required. Only non‐repairable components/parts in repairable systems are studied. In other words, the paper considers one‐component systems or a single component within a larger system. The operation and maintenance phases are dealt with in the study, along with the external operating environment and time independent influencing factors.

The introduced method for spare parts estimation will enable management to improve system availability and production line efficiency while minimizing total production costs. Consequently, the plant life cycle cost will be minimized by releasing the tied‐up costs incurred when stocking extra parts for a long time.

The paper provides a new outlook on product support and spare parts forecasting by taking the actual system operating environment into consideration. It helps managers and engineers to be realistic and act pragmatically while running and analyzing technical/industrial systems.

Performance measures should be linked to an organization’s strategy in order to provide useful information for making effective decisions and shaping desirable employee behaviour. The pitfalls relating to the indiscriminate use of common maintenance performance indicators are discussed in this paper. It also reviews four approaches to maintenance performance measures. The value‐based performance measure evaluates the impact of maintenance activities on the future value of the organization. The Balanced Scorecard (BSC) provides a framework for translating strategy into operational measures that collectively capture the critical requirements for sustaining the organization’s success. System audits are the tool for measuring organizational culture, which in turn determines the appropriate approach to the organization of maintenance functions. The operational efficiency of an organization’s maintenance function can be benchmarked with those of its counterparts in other organizations by using Data Envelopment Analysis (DEA). Among these approaches, the one which builds on the BSC embraces the design principles of a good performance measurement system. To smooth the adoption of the BSC approach to managing maintenance operations, a related research agenda is proposed in the concluding section.

The importance of physical assets has been increasingly recognized in recent decades. The significant returns on small improvements in overall equipment effectiveness (OEE) justify investment in the management of physical assets, but the wide variation of OEE across firms raises a question: “Why do these differences persist despite a high return on investments to maximize OEE?”. To address this question the dynamic processes that control the evolution of OEE through time need to be better understood. This paper aims to answer this question.

Building on insights from system dynamics and strategy literature, the paper maps the reinforcing feedback loops governing the maintenance function and its interactions with various elements in a firm. Building on strategy literature it hypothesizes that these loops can explain wide variations in observed persistent variations in OEE among otherwise similar firms. The paper draws on previous literature, extensive case studies and consulting projects to provide such mapping using the qualitative mapping tools from system dynamics.

The research outlines several reinforcing loops; once active, any of them could lead a firm towards a problematic mode of operation where reactive maintenance, poor morale, and a culture of fire‐fighting dominate. Actions taken to fix problems in the short‐run often activate vicious cycles, erode the capability of the organization over the long run, and lead to a lower OEE.

Knowing the factors affecting the asset management function of a plant increases the plant's safety and limits its environmental hazards.

Some of the common dynamics of organizations' asset management practices are illustrated and modeled. The strategic importance of OEE and its effect on companies' market capitalization is demonstrated.

In today's competitive industries, the selection of best suitable maintenance strategy is dependent on large number of quantitative and qualitative factors, and it becomes an extensively difficult problem for maintenance engineers. Over the years, a diverse range of solution methodologies have been developed for solving this multi-criteria decision-making (MCDM) problem. In this paper, the authors have presented a comprehensive review of latest maintenance strategy paradigms and solution approaches proposed for the selection of an appropriate strategy in various industries. It would provide a systematic mapping of developments in this field and identify some research gaps to explore further studies.

A systematic state-of-the-art comprehensive literature review on maintenance strategy paradigms and selection approaches is presented in this study. In this study, 87 research articles published in peer-reviewed journals, since year 2012, are reviewed.

For the selection of a suitable maintenance strategy, a variety of criteria are considered to better evaluate the alternatives. In this study, contemporary strategies are discussed, and their applications in different industries are also depicted. Moreover, through the analysis of extant literature, critical criteria are selected and classified in six major categories (namely, economic, technical, safety, environmental, feasibility and social) and further sub-categorized in quantitative and qualitative classes. These clusters of criteria can be helpful as an initial set of criteria for survey and then case- or industry-specific criteria can be shortlisted for further alternative evaluation.

From the perspective of maintenance managers, maintenance management can be a very difficult task, considering the numerous factors affecting the decision-making process. In order to help in the decision-making process, this study presents the contemporary maintenance strategies in a systematic manner. In a previous study (Kothamasu et al., 2006), these strategies were classified into repair and prevent classes only. With the developments of autonomous maintenance and design out maintenance (DOM), it was fair to include continuous improvement class. It will help managers and practitioners to identify, according to organization policy, appropriate maintenance strategy alternatives for the asset. A benchmark set of state-of-the-art maintenance strategies are laid out with their applications. The industrial case studies discussed in this study summarizes the optimal maintenance strategies for respective industries. Also, most critical criteria are identified from the existing studies for various industries that can help maintenance practitioners in acknowledging the critical factors and making appropriate decisions. Evaluation parameters for the maintenance strategy selection (MSS) generally conflict with each other, and considering the difficulty of quantifying the qualitative measures, it is a challenging task to determine the optimal trade-off. In order to overcome these challenges, popular MCDM approaches, demonstrating effective results across different industries are discussed with their limitations and applications. Decision-makers can refer this study to identify best suitable decision-making technique for the MSS problem in the industry of their choice. Maintenance managers and engineers can refer the case studies illustrated in Tables 1 and 2 to analyse the MSS techniques proposed by previous studies with industry-specific applications.

This study is an attempt to provide a reference point for research scholars interested in the field of maintenance management and/or development of maintenance strategy framework. This study provides a critical state-of-the-art review of efforts made in the field of MSS. The prominent maintenance strategies being implemented in contemporary industries are discussed with respective case studies. Interested researchers and academicians can familiarize themselves with these strategies and their distinct features in this study. In order to guide future studies and provide a reference point for academicians, MSS critical criteria used in extant literature are identified and classified into a comprehensive benchmark framework. Moreover, the industrial case studies are discussed with the most critical criteria of MSS for different industries and which strategy is most suitable for the respective industries based on these criteria. Table 1 presents different MCDM techniques and their hybrid applications for solving MSS problem that can help researchers in identifying research gaps. Future research can be directed at addressing the limitation of MCDM approach employed in existing studies and comparing the differences in results obtained by the proposed approach. Different industrial case studies with considered maintenance strategy alternatives are presented in Table 2, which can help researchers in identifying the industries that have not been studied yet. Moreover, not all of the existing studies are carried out by considering all the presented benchmark strategies, which can be addressed in future studies by interested researchers. More detailed discussion on research gaps is presented in the following section.

From the analysis of the extant literature, the authors could observe that the decision-making process adopted in numerous studies was limited to the classical maintenance strategies and not inclusive of aggressive maintenance strategy alternatives. To overcome these limitations and help maintenance managers in the decision-making, this study depicts the contemporary maintenance strategies, critical evaluation criteria and MCDM frameworks (employed to solve the MSS problem with industrial case studies) in a structured manner.

The purpose of this paper is to review the literature on total productive maintenance (TPM) implementation practice to present an overview of TPM implementation practices adopted by various manufacturing organizations and suggest possible gaps from researchers and practitioner’s point of view. This study tries to identify the best strategy for improving competitiveness of small and medium enterprises (SMEs) in globalized market and evaluates TPM implementation practice in SMEs.

The objective of this paper is to study the role of TPM program in context of Indian industries either from SMEs to large-scale industries. The approach has been directed toward justification of TPM implementation practice for its support to competitive manufacturing in the context of Indian manufacturing industries.

TPM implementation improves productivity and working efficiency of employees and also improves equipment effectiveness and a positive inclination toward company is registered. Therefore, equipment maintenance is an indispensable function in a manufacturing enterprise. In this highly competitive environment, manufacturing organizations should consider maintenance function as a potential source for cost savings and competitive advantage. SMEs must be considered as an engine for economic growth all over the world (Singh et al., 2008). A total of 148 papers related to TPM implementation in large-scale industries and SMEs were collected, analyzed and classified on the basis of their applications, broadly into large industry and SMEs and further divided into Indian and Non-Indian, then case study, implementation, model, literature review, maintenance, service, etc. This classification has clearly shows that SMEs are in a need to adopt TPM implementation practice to compete in this global market and changing requirements of large industries. Maintenance is an indispensable function in a manufacturing enterprise. In this highly competitive environment, manufacturing organizations must be considered maintenance function as a potential source for cost savings and competitive advantage. Singh et al. (2008) have concluded that SMEs must be considered as an engine for economic growth of all over the world. Following are the objectives of this study: to suggest a classification of available literature on TPM implementation; to identify the need of TPM implementation in SMEs; to identify critical observations on each category of classification; to identify the potential of SMEs in India; to identify emerging trends of TPM implementation in India; to suggest directions for future researchers in the field of TPM implementation on the basis of above mention points; and to consolidate all available literature on TPM implementation practice.

The challenges of stiff competition and the drive for profits are forcing the organizations to implement various productivity improvement efforts to meet the challenges posed by ever-changing market demands. In the dynamic and highly challenging environment, reliable manufacturing equipment is regarded as the major contributor to the performance and profitability of manufacturing systems.

In this dynamic world, importance of SMEs in the growth of the nation needs more attention of researchers and industrialists. After the globalization of market, SMEs have got many opportunities to work in integration with large-scale organizations. All the organizations from SMEs to large-scale industries can adopt effective and efficient maintenance strategies such as condition-based maintenance, reliability-centered maintenance and TPM over the traditional firefighting reactive maintenance approaches (Sharma et al., 2005).

In our view, this paper clearly identifies implications for research which will be useful for society. The gap discussed by authors needs to be addressed by future researchers.

This implementation strategy can help to save huge amounts of time, money and other useful resources in dealing with reliability, availability, maintainability and performance issues. On the basis of available literature, it can be understood that SMEs should change their maintenance strategies to cope up with global competition so that a lot of resources can be utilized in a better direction.

This paper aims to address the often fragmented approach to performance issues to maximise services quality and returns. With the increased emphasis on corporate reforms, the research presents a model framework as logic to strategy viability and competitive advantage for better outsourcing services delivery and excellence. The global change requires models with logic and variability to practically see the reality and challenges of all times.

Based on comprehensive literature search on performance research, nine influence factors were deduced as models for performance measure. This model is used to evaluate the performance of outsourcing firms in Malaysia. Over 200 questionnaires were sent out to outsourcing services delivery firms in Malaysia by post or personal visits; 68 of them responded. The study applied multivariate analysis to ascertain strategy capability and perception about factors that influence performance in the firms.

The outsourcing strategy performance revealed by the principal component analysis has given the strategy capability of the firms to be above-average, however not in a state to guarantee achievement of sustaining quality and excellence in services delivery. Conversely, to remain at the edge requires strategy that is flexible, integrated and sustainable, which most firms do not have. The results have also shown that more than half of the sampled population opted for a high-performance delivery goal; however, this vision was not supported adequately by a viable strategy. This inflexibility in strategy by most firms gives rise to usurpation and sub-optimality, which failed to take the facilities management (FM) profession beyond the reactive maintenance culture of the past century.

This research paper is one of the few strategic models from Malaysia that holistically evaluates performance in outsourcing firms.

The paper provides a model that can integrate and sustain the workplace which is a valuable insight to the FM and research world.

This study introduced a paradigm using influence factors (timeless practice) to ensure excellency in outsourcing services delivery. Today savvy customers are looking for reliability and quality services with cost certainty, which is partly the reason for the expanding interests on outsourcing. The workplaces require strategic reforms to foster better facilities performance and value.