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This paper presents the results of a case/simulation study that evaluated a number of potential maintenance policies for a flexible manufacturing system (FMS). Empirical data were used to structure the operation of the FMS, and to simulate its failures and repairs on the shop floor. Five maintenance policies – corrective, 30‐day preventive, 90‐day preventive, on‐failure opportunistic, and 30‐day opportunistic – were compared on four performance criteria: equipment utilization, machine downtime, through‐put, and average flow time. The “30‐day opportunistic” policy performed best overall, although the “corrective” policy was a close second, outperformed only in the area of equipment utilization. The “on‐failure opportunistic” policy performed poorly on every measure of system performance.

This paper reviews the literature on opportunistic maintenance (OM) as new advance maintenance approach and policy. The purpose of this paper is to conceptually identify common principle and thereby provide absolute definition, concept and characteristics of this policy.

A conceptual analysis was conducted on various literatures to clarify a number of principle and concepts as a method for understanding information on OM. The analysis involves the process of separating the compound terms used in the literatures into a few parts, analyse them and then recombining them to have more clear understanding of the policy.

The paper discussed the maintenance approach, genealogy, principle, concept and applications of OM both in numerical analysis and real industry. OM policy is developed based on combination of age replacement policy and block replacement policy and in practical; OM is applied as the combination of corrective maintenance which is applied when any failure occurred, with preventive maintenance (PM) – a planned and scheduled maintenance approach to prevent failure to happen. Any machine shutdown or stoppages due to failure is the “opportunity” to conduct PM even though it is not as planned. The characterization of OM was provided in order to present its theoretical novelty for researchers and practical significance for industries.

To date, there is no publication that reviews the OM in-depth and provides clear understanding on the topic. Therefore, this paper aims to show lineage of OM and the current trend in researches. This discussion will pave the way of new research areas on this optimal maintenance policy. Clear definition and principle of OM provided in this paper will trigger interest in its practicality as well as aid industries to understand and conduct OM in operation plant.

This paper discussed the available literature about OM in various perspectives and scopes for further understanding of the topic by maintenance management professionals and researchers. Therefore, OM can be widely studied and applied in real industry as it is an effective and optimal maintenance policy.

The purpose of this study was to assess the readiness of the Swedish manufacturing industry to implement dynamic, data-driven preventive maintenance (PM) by identifying the gap between the state of the art and the state of practice.

An embedded multiple case study was performed in which some of the largest companies in the discrete manufacturing industry, that is, mechanical engineering, were surveyed regarding the design of their PM programmes.

The studied manufacturing companies make limited use of the existing scientific state of the art when designing their PM programmes. They seem to be aware of the possibilities for improvement, but they also see obstacles to changing their practices according to future requirements.

The results of this study will benefit both industry professionals and academicians, setting the initial stage for the development of data-driven, diversified and dynamic PM programmes.

First and foremost, this study maps the current state and practice in PM planning among some of the larger automotive manufacturing industries in Sweden. This work reveals a gap between the state of the art and the state of practice in the design of PM programmes. Insights regarding this gap show large improvement potentials which may prove important for academics as well as practitioners.

The purpose of this paper is to demonstrate the use of two general purpose decision‐making techniques in selecting the most appropriate maintenance strategy for organizations with critical production requirements.

The Analytical Hierarchical Process (AHP) and the Analytical Network Process (ANP) are used for the selection of the most appropriate maintenance strategy in a local newspaper printing facility in Turkey.

The two methods were shown to be effective in choosing a strategy for maintaining the printing machines. The two methods resulted in almost the same results. Both methods take into account the specific requirements of the organization through its own available expertise.

The techniques demonstrated in this paper can be used by all types of organizations for selecting and adopting maintenance strategies that have higher impact on maintenance performance and hence overall business productivity. The two methods are explained in a step‐by‐step approach for easier adaptation by practitioners in all types of organizations.

The value of the paper is in applying AHP and ANP decision‐making methodologies in maintenance strategy selection. These two methods are not very common in the area of maintenance, and hence add to the pool of techniques utilized in selecting maintenance strategies.

The purpose of this paper is to provide a comprehensive overview of technical integrity management (TIM) and propose a methodology for assessing to which extent the technical integrity (TI) performance is balanced in terms of goal awareness among the personnel responsible for TIM, and the degree to which high level goals are implemented in maintenance strategies.

The study involved a comprehensive literature survey as well as information and data collected in the Norwegian oil and gas (O&G) industry. Several discussion rounds were carried out with the industrial maintenance management experts to recognize the existing practices and to confirm the suggested model.

The literature review indicated that there is a need for a methodology for assessing to which extent the technical integrity (TI) performance is balanced in terms of goal awareness among the personnel responsible for TIM, and the degree to which high‐level goals are implemented in maintenance strategies. The suggested model can incorporate industrial data as well as intentions, intuitions and experiences of industrial experts who are making decisions sensitive to TI of a production installation.

The study has been conducted in relation to TIM of production installations on the Norwegian Continental Shelf (NCS). The study is limited to measuring TI performance in relations to experts' awareness.

The study stresses the need for improving synergy between the TI and maintenance management function. It proposes a methodology to measure to which extent organizational priorities are balanced, while addressing financial as well as health, safety and environmental (HSE) interests when selecting a maintenance strategy.

This paper addresses a problem that is not given enough attention in the currently available literature. Available approaches suggest models and frameworks for measuring integrity performance. However, the operationalization of most of the existing models and frameworks, remains vague. Instead a formal mechanism is needed to analyze the gap between the present performance and performance targets.

Maintenance strategy selection (MSS) is considered as a complex multiple-criteria decision-making (MCDM) problem. The purpose of this paper is to present a comprehensive review on the use and application of MCDM approach and its associated case studies in the field of MSS.

The paper systematically classifies the published literature of both researchers and practitioners and then analyzes and reviews it methodically.

This paper outlines the important issues relevant to the subject, including the techniques used for data collection, the quantitative and qualitative criteria taken into account in decision making, the maintenance strategies considered for evaluation, the methods applied to find the solution, and the type of industries being studied. In each category, the gaps are identified along with recommendations for the future research work.

Literature on classification of the MCDM models used to select the most appropriate maintenance strategy is very limited. The proposed classification scheme not only will be useful to researchers, but also assists maintenance professionals to find the models that fit their specific needs.

The paper provides many references in the field, including the articles published in academic journals, conference papers, master and doctoral dissertations, text books, and industrial reports, and suggests a classification scheme according to various attributes.

The great need for an optimum preventive maintenance strategy coupled with the fast‐developing condition‐monitoring techniques has given rise to the invention of relevant condition predictor (RCP)‐based maintenance approach. The main purpose of this approach is to prevent the failures due to gradual deterioration of mechanical items in order to improve system reliability and availability. This is done by monitoring relevant condition predictors of constituent maintenance significant items of the system, taking into account the availability and cost‐effectiveness of the monitoring techniques. A comprehensive review of all constituent items is carried out and a systematic approach is used to decide an optimum maintenance policy for each corresponding group of items. An optimum time to the examination of relevant condition predictors is derived mathematically with required reliability as the optimisation criterion in order to implement the RCP‐based maintenance activities.

The traditional maintenance scheduling strategies of multi-component systems may result in maintenance shortage or overage, while system degradation information is often ignored. The purpose of this paper is to propose a multi-phase model that better integrates degradation information, dependencies and maintenance at the tactical level.

This paper proposes first a maintenance optimization model for multi-component systems with economic dependence and structural dependence. The cost of combining maintenance activities is lower than that of performing maintenance on components separately, and the downtime cost can be reduced by considering structural dependence. Degradation information and multiple maintenance actions within scheduling horizon are considered. Moreover, the maintenance resources can be integrated into the optimization model. Then, the optimization model adopting one maintenance activity is extended to multi-phase optimization model of the whole system lifetime by taking into account the cost and the expected number of downtime.

The superiority of the proposed method compared with periodic maintenance is demonstrated. Thus, the values of both integrated degradation information and considering dependencies are testified. The advantage of the proposed method is highlighted in the cases of high system utilization, long maintenance durations and low maintenance costs.

Few studies have been carried out to integrate decisions on degradation, dependencies and maintenance. Their considerations are either incomplete or not realistic enough. A more comprehensive and realistic multi-phase model is proposed in this paper, along with an iterative solution algorithm for it.

The purpose of this paper is to investigate maintenance performance of a gasification process unit by identifying reliability, failure and hazard rate. The prediction on the number of preventive maintenance (PM) activities and size of labour are being analysed.

The study collects maintenance data for 4,000 hours operation to perform Weibull analysis in order to determine two key factors which are beta shape factor, β and characteristic life, η.

The results for estimation of failure, reliability and hazard rate show that the pump was most likely contributed to the biggest failure. On the other hand, reaction chamber was able to maintain the longest operation among other components. It is estimated that the total PM activities should be within 20-50 activities per month for whole processing plant. Meanwhile, the estimation of size of labour should be within the range of 60-130 numbers of workers per month for all components.

The method of Weibull analysis for investigating current maintenance performance has been analysed using real case study data. The data collection is obtained from a typical gasification process unit.

The purpose of this paper is to review maintenance practices, tools and parameters for marine mechanical systems that can be classified as plant, machinery and equipment (PME). It provides an insight for the maintenance crew on which maintenance parameters and practices are critical for a given PME systems.

The review paper characterizes the various maintenance parameters and maintenance practices used onshore and offshore for PME and identifies the possible gaps.

A variety of maintenance techniques are being used in the marine industry such as corrective maintenance, preventive maintenance and condition-based maintenance. As marine vehicles (MV) get older, the most important maintenance parameters become maintenance costs, reliability and safety. Maintenance models that have been developed in line with marine mechanical systems have been validated using a single system, whose outcome could be different if another PME system is used for validation.

There is a limited literature on MV maintenance parameters and maintenance characterization regarding mechanical systems. The maintenance practices or strategies of marine mechanical systems should be based on maintenance parameters that suit the marine industry for a given PME.

Based on the available literature, the paper provides a variety of maintenance framework, parameters and practices for marine mechanical systems. The paper further gives an insight on what maintenance parameters, strategies and platforms are given preference in the shipping industry.