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Journal of Quality in Maintenance Engineering Opportunistic maintenance (OM) as a new advancement in maintenance approaches: A review Hasnida Ab-Samat Shahrul Kamaruddin Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) Article information: To cite this document: Hasnida Ab-Samat Shahrul Kamaruddin , (2014),"Opportunistic maintenance (OM) as a new advancement in maintenance approaches", Journal of Quality in Maintenance Engineering, Vol. 20 Iss 2 pp. 98 - 121 Permanent link to this document: http://dx.doi.org/10.1108/JQME-04-2013-0018 Downloaded on: 08 February 2015, At: 00:21 (PT) References: this document contains references to 91 other documents. To copy this document: permissions@emeraldinsight.com The fulltext of this document has been downloaded 315 times since 2014* Users who downloaded this article also downloaded: Amik Garg, S.G. Deshmukh, (2006),"Maintenance management: literature review and directions", Journal of Quality in Maintenance Engineering, Vol. 12 Iss 3 pp. 205-238 http:// dx.doi.org/10.1108/13552510610685075 Professor Uday Kumar, Associate Professor Aditya Parida and Associate Professor Ramin Karim, Phillip Tretten, Ramin Karim, (2014),"Enhancing the usability of maintenance data management systems", Journal of Quality in Maintenance Engineering, Vol. 20 Iss 3 pp. 290-303 http://dx.doi.org/10.1108/ JQME-05-2014-0032 Eleonora Bottani, Gino Ferretti, Roberto Montanari, Giuseppe Vignali, (2014),"An empirical study on the relationships between maintenance policies and approaches among Italian companies", Journal of Quality in Maintenance Engineering, Vol. 20 Iss 2 pp. 135-162 http://dx.doi.org/10.1108/JQME-11-2012-0039 Access to this document was granted through an Emerald subscription provided by 448547 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. *Related content and download information correct at time of download. The current issue and full text archive of this journal is available at www.emeraldinsight.com/1355-2511.htm JQME 20,2 Opportunistic maintenance (OM) as a new advancement in maintenance approaches Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 98 Received 18 April 2013 Revised 27 November 2013 Accepted 7 March 2014 A review Hasnida Ab-Samat and Shahrul Kamaruddin School of Mechanical Engineering, University Science Malaysia (USM), Seberang Perai Selatan, Malaysia Abstract Purpose – 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. Design/methodology/approach – 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. Findings – 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. Practical implications – 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. Originality/value – 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. Keywords Preventive maintenance, Corrective maintenance, Maintenance policy, Opportunistic maintenance, Optimal maintenance Paper type Literature review Journal of Quality in Maintenance Engineering Vol. 20 No. 2, 2014 pp. 98-121 r Emerald Group Publishing Limited 1355-2511 DOI 10.1108/JQME-04-2013-0018 1. Maintenance system The role of maintenance in today’s manufacturing systems is becoming more important as companies start to adopt the system as one of their profit generating elements (Waeyenbergh and Pintelon, 2002; Sharma et al., 2011) and a supporting function (Samat et al., 2011). Maintenance is conducted to ensure that all the equipment within the company is repaired, replaced, adjusted and modified according to The authors would like to convey their appreciations to Ministry of Higher Education (MOHE) and Universiti Sains Malaysia (USM) for the funding provided in conducting this research. Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) production requirements. This way, the whole manufacturing processes are guaranteed to operate effectively and efficiently (Arts et al., 1998; Parida and Kumar, 2006). However, based on the research conducted by Mobley (1990), cited by Chan et al. (2005), 15-40 per cent of total production costs are spent on maintenance activities. On the other hand, Bevilacqua and Braglia (2000) stated that maintenance costs can reach 15-70 per cent of production costs, varying according to the type of industry. Consequently, further research by Wireman (2003) showed that up to 33 per cent of this maintenance cost is actually wasted or spent unnecessarily. These percentage show a lot of improvements could be carried out in order to achieve an effective and optimized maintenance system. Nowadays, the literatures on maintenance is centred on problems in the optimization of maintenance policies. The aim is to ensure a system has the ability to satisfy consumer demand with the minimal maintenance cost possible, without sacrificing component useful lifetime or reliability (Nourelfath and Ait-Kadi, 2007; Zhou et al., 2012). The focus of this paper is directed towards the various literatures that discuss the types of maintenance techniques applied in the industry. The aim is to investigate the lineage of opportunistic maintenance (OM) policy as a new maintenance concept which also widely relates to the optimal maintenance system. The origins and genealogy of OM principles in various published literature are critically analysed using the critical conceptual method. The first section of this paper reviews OM monikers, genealogy, principles and aims. Then, the categorization of literature based on system type, research classifications and optimal criteria adopted are presented in the second section. Subsequently, various applications of OM are presented in order to define its practicality in the industry. The fourth section consists of a discussion of issues, merits and also downsides of OM policy both in numerical analysis and real industry application. Lastly, conclusions are drawn in presenting the concept and application of OM for future research. 2. Conceptual analysis of OM policy A tremendous number of publications can be found discussing maintenance techniques since the maintenance technique transition from corrective maintenance (CM) in 1940 to various operation research models (Garg and Deshmukh, 2006). Each one is developed based on a variety of principles and to suit different situations. For Zheng (1995), the major objectives of maintenance policies are to increase system reliability and availability while at the same time to reduce system maintenance cost. Among the various maintenance policies, some are widely implemented as they have strong fundamental elements such as CM, preventive maintenance (PM), predictive maintenance, condition-based maintenance (CBM), total productive maintenance (TPM), reliability-centred maintenance (RCM) and computer maintenance management system. Aside from these policies, a maintenance policy termed as opportunistic replacement and inspection was introduced by McCall and Radner and Jorgenson (1963). It is based on research conducted by the RAND Corporation, situated in Santa Monica, CA, USA with the aim to find an optimal maintenance policy. It was first applied in a case study of a rocket engine (McCall, 1963) and a manned aircraft and ballistic missile system (Radner and Jorgenson, 1963). The concept of this “opportunistic” maintenance policy is the dependency of the components and equipment in a system. With this policy, maintenance is to be performed on a given part, at a given time, depending on the state of the rest of the system. The focus of Opportunistic maintenance 99 JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 100 Figure 1. Four elements in conceptual analysis for opportunistic maintenance (OM) policy implementation is to predict the relative frequencies of a variety of maintenance actions such as inspection and replacement of failed components in a system. This policy is intriguing as in current years researchers referred to this policy as an optimal maintenance system. However, advancement on this policy requires profound study to find its origin, principles and applications. Therefore, critical conceptual analysis was conducted in this paper as an effort to fully understand the opportunistic replacement and inspection policy or referred to as OM throughout the paper. Furner (2004) described the analysis as a technique of precisely defining the meaning of a concept using the process of identifying and also specifiying the concept within a classification of conditions or phenomena. For this paper, the technique is used by breaking down the issues to examine the major elements in OM policy. Since there is no one single book or manual published on the matter, the conceptual analysis were mainly focused on journal papers. The flow of conceptual analysis conducted on OM policy is shown in Figure 1. The analysis process starts with the literature published on opportunistic and optimal maintenance, which were scrutinized in order to find the policy moniker used to described OM. Even though OM was first described as opportunistic replacement and inspection in 1963, the same theory used by Rander and Jorgenson was applied to much research afterwards, yet named in many different terms. The various monikers used to discussed OM policy over the years reflected the applications as well as the principle used in the literature. The list of monikers used are stated in Section 2.1. In connection with the moniker, conceptual analysis was also conducted to study the origins and genealogy of OM. Since the advancement of application on maintance system in 1940s, various maintenance policies were developed from a basic principle of a “run, failed and repair” approach. This resulted with a grouping of approaches and techniques to cater to many types of equipment and system conditions in the industry. Further on, the principle and concept of OM in various literatures were revised in Section 2.3. Changes in technology and process due to high customer demand requires maintenance to be conducted as precisely and as effectively as possible. Because of that, optimization becomes the focus of much maintenance research, which then brought OM into the limelight. For that very reason, the simple approach of using the opportunity of a component failure to conduct maintenance tasks on other related components was tried and altered to satisfy numerous system conditions. The analysis on this paper brings forward some of the common OM principles and concepts used in the publications. The conceptual analysis ends with a study of focuses and aims of OM in the publised research. Relating to various principles and concepts introduced in the literature, the objectives of conducting OM policy also varies. Therefore, the objectives were gathered and discussed, as the process, to understand the advantages of OM policy. All the information gathered via this conceptual analysis was used to define the OM overall, as presented in Section 2.5 of this paper. Moniker Genealogy Principle and Concept Focus and Aim Opportunistic maintenance 101 Publications on Opportunistic Maintenance (1963-2012) 12 10 8 6 4 2 2011 2009 2007 2005 2003 2001 1999 1997 1993 1995 1989 Year 1991 1987 1985 1983 1981 1979 1977 1975 1973 1971 1969 1967 1965 0 1963 No. of Publication Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 2.1 Publications and monikers of OM policy The OM concept was first coined in 1963 as opportunistic replacement and inspection policy and the trend continued for a few years afterwards, before it changed to become OM, as is widely used today. In the project by Radner and Jorgenson (1963), the combination of PM action and CM were used to reduce the set-up costs of a maintenance action. The concept was then further reviewed as a new maintenance policy in a paper by McCall (1965). After the introduction of the OM concept, aside from a few publications, no other researchers further discussed the topic until early the 1980s. Nevertheless, OM returned to become a topic of interest by the 1990s and the trend shows the increase of publications on OM by the year 2000. The graph in Figure 2 shows the number of journal publications on OM from the years 1963 until 2012. Over 70 publications are found to directly or indirectly delve into the discussion and application of the OM policy issues. Even though it can be considered as a small number compared to other maintenance approaches and policies like RCM, TPM and CBM, it is a significant trend considering the short genealogy of OM. There is an encouraging and steady increment on the number of publication in recent years. From the number of publications it can be seen that there are also some trends in the naming of the OM policy. Conceptual analysis conducted on the publications shows that over the years, OM policy is widely studied and implemented, but with various monikers in order to suit the concept used in the research. The study of monikers in this paper is deemed important as the naming reflects the root of the principles used. The names also indicate the overall idea of the policy used in the publications. As listed in Table I most publications on OM in the 1970s and 1980s used the term “opportunistic replacement and inspection policy”. This is due to the fact that maintenance was first viewed as tasks involving only repair and replacement of components with the aim of restoring broken machinery and equipment into operational condition. It was only until after a few decades that the process of cleaning, lubricating, calibrating, etc., were considered as maintenance tasks. Then, the concept was also named as opportunistic-based maintenance and opportunity-based age replacement. Age-based maintenance can be defined as activities done based on the age renewal of a machine, which is preventively maintained until it reaches a certain Figure 2. Number of publications on opportunistic maintenance from 1963 to 2012 JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 102 Table I. List of monikers used in publications on opportunistic maintenance from 1963 till 2012 No 1. 2. 3. 4. 5. 6. 7. Reference Maintenance policy McCall (1963) Radner and Jorgenson (1963) McCall (1965) Duncan and Scholnick (1973) Sethi (1976) Vergin and Scriabin (1977) Day and George (1981) Opportunistic replacement and inspection Opportunistic replacement and inspection Opportunistic replacement and inspection Opportunistic replacement and interrupt strategies Optimal opportunistic replacement Opportunistic maintenance and preventive maintenance Opportunistic replacement, look-ahead-maintenance and stationary policies Preventive replacement Opportunistic replacement Piggyback preventive maintenance Opportunistic replacement Opportunistic replacement Optimal replacement Opportunity-based block replacement or one-opportunitylook-ahead Opportunistic hazard rate replacement Opportunistic replacement Opportunistic replacement Opportunity-based age replacement All opportunity-triggered replacement Condition-based preventive maintenance Opportunity-based maintenance Opportunity-based maintenance Optimal maintenance Opportunistic maintenance Opportunistic maintenance Opportunity-based age replacement Opportunistic maintenance Opportunity-based age replacement Opportunistic maintenance Opportunistic maintenance Opportunistic maintenance Opportunistic or on-condition maintenance Opportunistic maintenance Opportunistic maintenance Condition-based inspection/replacement Age replacement Opportunistic maintenance Opportunistic maintenance Opportunistic replacement Opportunistic replacement Opportunistic preventive maintenance Opportunistic-based age replacement Age replacement during delay time and opportunistic age replacement during delay time Opportunistic maintenance Condition-based maintenance Opportunistic replacement Opportunistic maintenance Opportunistic condition-based preventive maintenance 8. 9. 10. 11. 12. 13. 14. L’Ecuyer and Haurie (1983) Epstein and Wilamowsky (1985) Liang (1985) Thomas (1986) Pullen and Thomas (1986) Ozekici (1988) Dekker and Smeltink (1991) 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. Zheng and Fard (1991) Fard and Zheng (1991) Zheng and Fard (1992) Dekker and Dijkstra (1992) Zheng (1995) Mann et al. (1995) Savic et al. (1995a) Savic et al. (1995b) Dekker (1996) Tan and Kramer (1997) Mohamed-Salah et al. (1999) Jhang and Sheu (1999) Sherwin (1999) Satow et al. (2000) Rao and Bhadury (2000) Pham and Wang (2000) Bevilacqua and Braglia (2000) Crocker and Kumar (2000) Cassady et al. (2001) Scarf and Deara (2003) Grall et al. (2002) Jiang and Ji (2002) Wang (2002) Dekker and van Rijn (2003) Kaspi and Shabtay (2003) Haque et al. (2003) Degbotse and Nachlas (2003) Satow and Osaki (2003) Das and Acharya (2004) 44. 45. 46. 47. 48. Saranga (2004) Amari and McLaughlin (2004) Castanier et al. (2005) Cui and Li (2006) Zhou et al. (2006) (continued) Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) No Reference Maintenance policy 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. 63. 64. 65. 66. 67. 68. 69. 70. 71. 72. 73. 74. 75. 76. 77. Lai and Chen (2006) Iung et al. (2007) Wang et al. (2008) Nicolai and Dekker (2008) Zequeira et al. (2008) Almgren et al. (2008) Levrat et al. (2008) Derigent et al. (2009) Besnard et al. (2009) Chien (2009) Nilsson et al. (2009) Laggoune et al. (2009) Zhou et al. (2009) Samhouri (2009) Laggoune et al. (2010) Bedford et al. (2011) Khazraei and Deuse (2011) Sharma et al. (2011) Xiang et al. (2012) Ding and Tian (2012) Cheng et al. (2012) Xu et al. (2012) Hu et al. (2012) Taghipour and Banjevic (2012a) Taghipour and Banjevic (2012b) Koochaki et al. (2012) Vu et al. (2012) Almgren et al. (2012) Zhou et al. (2012) Periodic replacement Opportunistic preventive maintenance Condition-based order-replacement Opportunistic maintenance Opportunistic maintenance Opportunistic replacement Opportunistic preventive maintenance Opportunistic maintenance Opportunistic maintenance Preventive maintenance replacement Opportunistic maintenance Opportunistic replacement Opportunistic preventive maintenance Opportunistic maintenance Opportunistic replacement Opportunistic maintenance Opportunistic maintenance Opportunistic maintenance Condition-based and age-based preventive maintenance Opportunistic maintenance Opportunistic maintenance Group preventive maintenance Opportunistic predictive maintenance Opportunistic replacement Opportunistic replacement Opportunistic maintenance Opportunistic maintenance Opportunistic maintenance Opportunistic replacement number of time periods without a failure (Khazraei and Deuse, 2011). In the research using the name, the decisions regarding maintenance tasks conducted during failure are based on a calculation of the age or the remaining lifetime of a component. Interestingly, some researchers (Day and George, 1981; Dekker and Smeltink, 1991; Dekker and Dijkstra, 1992) also called this policy one-opportunity-look-ahead maintenance. It is to portray the process of replacement of parts or components if they reach their limited lifetime, and right before they experience failure. The concept is to look into the planning of maintenance for each component in a system and replace components that will reach their life limits. For Liang (1985), the term “piggyback preventive maintenance” was used for the OM concept. All parts in a system have their own PM intervals, yet the PM is not carried out until an unscheduled maintenance for another part occurs, thus the term piggyback. The research focuses on the planning of bringing forward any scheduled maintenance on non-failed components when a failure occurs on a component in the same system. Another fascinating term used for OM is “optimal replacement or optimal maintenance” (Ozekici, 1988; Fard and Zheng, 1991; Zheng and Fard, 1991, 1992; Zheng, 1995; Dekker, 1996). The terms used actually show the researchers’ agreement that OM policy has the potential to be used as an optimal maintenance system. In this Opportunistic maintenance 103 Table I. JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 104 research, OM is portrayed as an optimum or ideal maintenance policy for the reason that the concept will provide the best or most favourable maintenance schedule for the systems studied. Ozekici (1988)for example focuses on a complex system such as a jet engine or an electronic computer, which calls for maintenance to avoid any failures occurring during operation. The approach in this research is to use the stochastic dependency of components to one another in order to plan maintenance according to the component interactions. Any shutdown of the system will be used as the opportunity to conduct multiple maintenance tasks on multiple components based on their reliability. Aside from these, OM – which is the policy where PM activities are conducted during CM stoppages – is also called “CBM/PM” (Mann et al., 1995; Grall et al., 2002; Amari and McLaughlin, 2004; Castanier et al., 2005; Zhou et al., 2006; Wang et al., 2008; Xiang et al., 2012). This is to suit a scenario where CM and PM tasks are conducted at the same time. In the research, analysis is focused on the planning and combining of CM and PM tasks especially from an industry point of view. Most research uses the moniker to highlight the application as well as the practicality of OM policy. Nevertheless, gradually the terms changed to become OM as is widely used today. It can be observed that the existence of these many monikers for OM can be attributed to the fact that there is no literature that specifically discusses the policy. 2.2 Genealogy of OM policy From the monikers listed in Table I and analysed in previous section, it can be observed that the origins of OM policy can be attributed to age replacement policy (ARP) and block replacement policy (BRP). 2.2.1 ARP. Jiang and Ji (2002) defined ARP as preventive replacement activities performed after a given continuous operation time (noted as T) without experiencing any failure. A failure replacement is conducted if the system fails before the optimal time, T (Liang, 1985). The principle of ARP is that a component is replaced when it has achieved its lifetime. The advantage of implementing this policy is that it ensures maximum usage/lifetime of the component. Zheng and Fard (1991) stated that ARP is a traditional approach for a single-unit system or for equipment with a small number of components. This is because the replacement of components based on their age becomes a very complex maintenance activity if implemented in a multi-component system. When aiming for a cost-effective maintenance system, ARP becomes a tedious task of keeping track of all the components’ lifetimes and useful life. ARP is also not cost-effective when viewed from a maintenance perspective because various components in a system means myriad occasions of maintenance activities needing to be conducted, and the process will disturb production. Another issue is that components will possibly fail before their lifetime, caused by environmental and external conditions, as well as the failure of other integrated components. Multi-component systems also require complex maintenance planning and scheduling. 2.2.2 BRP. Another maintenance policy that initiates the growth of the OM concept is BRP. It is traditionally applied in multi-component systems where maintenance activities are done on more than one component at the same time (Zheng, 1995). Based on the fact that, most of the time, components in a system are dependent on one another, BRP suggested that maintenance or replacement activities are conducted on a block or a group of components. According to Wang (2002), it is a periodic maintenance policy where a component is preventively maintained at fixed time intervals and the activities are independent of the previous failures of the component. BRP is Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) implemented with the aim of having the minimum maintenance activities possible as an effort to maximize the production rate. Savic et al. (1995a) discussed BRP as a group replacement policy where it was assumed that when any component is replaced, the other components that belong to the same group will be replaced as well. However, the main concern with BRP is high possibility that newly replaced components will need to be replaced again. This will definitely increase maintenance costs and also create waste in the form of component lifetime. 2.3 Principles and concepts of opportunistic maintenance In the early literature, the general sources’ idea for OM is that component and equipment are assumed to fail stochastically, and that the failures are independent according to known probability distribution (Radner and Jorgenson, 1963). Similarly, the fundamental basis of OM by McCall (1963) divided the maintenance activities into inspection and replacement with components having a stochastic dependency on one another. According to Nicolai and Dekker (2008), the principle behind OM is stochastic dependency that implies that the state of components can influence the state of other components. The principle can also be referred to as failure interaction or probabilistic dependence of one component on another in a system. For the concept of OM, the abstract idea is about opportunities that may arise in a maintenance system. Dekker and van Rijn (2003) defined the word “opportunity” in OM as “any event at which a unit can be maintained preventively without incurring cost penalties for the shutdown of the unit”. The characteristic of the opportunity is that it occurs randomly and has a limited duration due to the fact that longer machine downtime will increase maintenance costs and disrupt the production flow. If this is happening, then the practicality and advantage of OM is void. On the other hand, as stated by Kaspi and Shabtay (2003), the opportunity to replace a component needs to be utilized as in any case of machine failure as the stoppage of production line has already occurred. The opportunity may arise during shutdown periods for particular equipment and/or due to failures of other components (Rao and Bhadury, 2000). It means that OM provides the maintenance worker an opportunity to repair or replace components which are found to be defective or need replacement in the immediate future, during the maintenance of a sub-system or module (Saranga, 2004). This way the cost of future maintenance or replacement activities can be avoided (Pullen and Thomas, 1986). 2.4 Focus and aims of opportunistic maintenance The ultimate objective of maintenance activity is to maintain the system functionality to the maximum lifetime possible, and with optimum trade-offs between machine downtime and maintenance costs, while at the same time avoiding any hazardous failures (Saranga, 2004). This is also the focus of OM policy. Overall, OM aims to reduce the amount of planned downtime for machines while at the same time maximizing the lifetime or reliability of components. All these are to ensure the best possible lifetime for the components in avoidance of costly and risky failures during operation. OM applications in literature lean towards an optimal maintenance system because OM use trade-off approaches between the reliability of a component with maintenance costs. Koochaki et al. (2012) pointed-out that the aim of OM is to group maintenance activities of two or more components in order to reduce maintenance costs. For Mohamed-Salah et al. (1999) the main objective of OM application is to reduce the total number of maintenance activities in the production line and consequently reduce the Opportunistic maintenance 105 JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 106 total maintenance cost. One or more components can be repaired or replaced through the application of one or more maintenance approaches in the system (Zheng and Fard, 1991). By conducting CM and PM simultaneously, more failures can be avoided, and the number of times equipment needs to be shut down for maintenance can be reduced. This is coupled with the assumption that replacing more than one component at the same time is cheaper than replacing the components separately (Zheng and Fard, 1992). 2.5 The OM concept defined Since the earliest publications in 1963, there is not a single paper that specifically states the original definition of OM policy. Radner and Jorgenson (1963) used the concept of optimal replacement policy on a unit of component during failure and maintenance of other components if the unit reached a certain age limit. The age limit is decided to be as close as possible to the end of the component’s lifetime. The concept tested is practical for a two-component system since it is easy to monitor and plan. Dekker and Smeltink (1991) described OM as a block replacement model in which a component can be replaced preventively at maintenance opportunities that appear randomly. Rao and Bhadury (2000) stated that in OM, PM of a component is conducted when opportunities arise due to failures of other components. It is similar with Mann et al. (1995) who stated that the intervals between PM activities on a component are no longer fixed, but are only performed “when needed”. For Tan and Kramer (1997), OM is part of general planning and scheduling in a manufacturing system where the flexibility of maintenance activities is optimized considering the stochastic and uncertain nature of equipment failures, quality rejects, batch times, batch sizes and also production targets. These factors are important for a production and manufacturing company. Samhouri (2009) described OM as a systematic method of collecting, investing, preplanning and publishing a set of proposed maintenance activities and then acting based on the plan whenever an opportunity arises caused by an unscheduled failure or repair. As maintenance is no longer traditional work of replacing and inspecting the condition of components, Samhouri captures the concept of maintenance planning and scheduling as well as stating the situation of opportunity arising for maintenance. From a practice point of view, Mohamed-Salah et al. (1999) defined OM as an opportunistic strategy which combines corrective and PM activities performed on different processors of a line. OM should be conducted when technical and economical conditions are satisfied in the effort to achieve optimal maintenance. The principle behind this policy is the dependency of a component on another component especially in multi-component system. The dependency trait is used to conduct PM on one component while conducting CM on the other. That way, it can be concluded that the fundamental concept is that machine downtime to repair a component is an “opportunity” to maintain other components in the system. Therefore, any production stoppages due to a component failure can be taken advantage of by conducting maintenance activities on other related components. From these various descriptions and definitions, the key points that could be extracted are that OM is the planning and scheduling of maintenance activities and opportunities in achieving an optimal maintenance system with a balanced trade-off between maintenance cost and component/system reliability. Taking the consideration of the dependency principle and the opportunity concept as discussed in previous sections of this paper, OM is best described as the planning and scheduling of Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) maintenance activities to repair a component, whilst at the same time opportunistically repair/replace other components in the system, with the aim to avoid future failures and reduce the amount of machine downtime. 3. Classification of literature on OM Once the genealogy, names, concepts and aims of OM are successfully analysed, the next step is to analyse the application of OM in various publications. As previously discussed, OM originates from ARP and BRP, where ARP is mostly implemented for single component systems while BRP is mostly used for multi-component systems. Therefore, as OM shares the threads from both policies, it was also implemented in both types of system. Additional discussion on the topic is prepared in the next subsection. Classification of the literature was also conducted in this paper. The aim is to show the research trend and interest in order that future research can be identified. 3.1 Classification from the type of system perspective Application of a concept is always the focal point in research. In doing so, applications are done in a set of dependent or independent elements or components that work together and form a system. In the early literature, McCall (1963) and Radner and Jorgenson (1963) used opportunistic replacement and an inspection policy on a system with only one part being monitored while several others were ignored. Opportunistic action taken on the non-monitored part depends on the state of other parts. The term “monitored” reflects the situation where other parts follow PM activities planned for them, while the lone part is only repaired or replaced when the opportunity arises caused by the failure of other parts. This will save maintenance time and cost. The part is assumed to have a stochastic failure rate. This similar approach was also used by Liang (1985) and Degbotse and Nachlas (2003). However, some researchers used a single-unit system or multiple unit systems with two components as the example of OM application. The principle behind OM is that all components in the equipment have the tendency to be dependent on one another. When one component fails, there is a high possibility one or more other components are affected and need to be maintained. A failure of one component will become an opportunity to fix the other component. While Rao and Bhadury (2000) and Levrat et al. (2008) opted for more versatile applications discussing the OM application for systems with multi-equipment and multi-components connected to the equipment in series. When components are connected in series they will be dependent on one another. The failure of one component will certainly affect the whole process of the equipment. Nevertheless, the research did not apply OM in a real case study system which makes it hard to comprehend the implementation processes and gauge its practicality. OM concept is mostly useful and easily practiced in continuously run systems that have high cost rate of downtime or failure (Sherwin, 1999). It is prudent to say that OM is effective for this type of system because the failure of a component provides an opportunity to replace the other components (Satow and Osaki, 2003). Regardless, application of OM in a multi-component context will required a complex system of maintenance planning and scheduling. 3.2 Classification from the type of research approach perspective To show the trend of research approaches conducted in OM, publications are categorized into four different types of approach, namely as numerical analysis, case Opportunistic maintenance 107 JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 108 study, simulation and review paper. The classification is based on the type of research conducted and discussed in the paper. A paper or manuscript is classified under numerical analysis if it provides an algorithm, theorem and mathematical model in OM research. As OM is a new maintenance policy, most publications in the numerical analysis approach linger around the mathematical analysis of maintenance opportunities and also optimization based on component lifetime, reliability and maintenance cost. For a case study, papers classified in this group are those that use data from a real environment or industry to solve OM issues from a practical point of view. Some papers which further tested and simulated the OM model or algorithm using computer software are grouped under the simulation type. The last type of paper is a review type where a survey of literature on maintenance was discussed. Figure 3 shows the percentage of papers based on their classification. It can be observed that close to 62 per cent of the publications focus on the numerical analysis aspect of OM. The numerical analyses make use of various theorems and mathematical methods to develop the OM schedule, and to evaluate the effectiveness of OM based on the age of the component/equipment replaced or repaired, and also the maintenance cost involved. Aside from that, some theorems and numerical methods like Monte-Carlo simulation (Tan and Kramer, 1997; Crocker and Kumar, 2000; Laggoune et al., 2010), genetic algorithm (GA) (Savic et al., 1995a, b; Haque et al., 2003; Saranga, 2004; Samhouri, 2009), Weibull distribution (Mann et al., 1995; Cassady et al., 2001; Laggoune et al., 2010; Xiang et al., 2012) and Poisson distribution (Satow et al., 2000) are utilized for formulating assumptions regarding the equipment’s age and reliability. While Fuzzy logic (Haque et al., 2003; Derigent et al., 2009) and Markov decision theory (Sethi, 1976; Ozekici, 1988; Amari and McLaughlin, 2004; Xiang et al., 2012) were used in deliberations on optimal maintenance activities and in choosing the best trade-off between age and cost during OM implementation. OM is rarely included in a review paper particularly when the review is discussing maintenance policies. It shows that there is little awareness of the OM concept. Aside from papers by McCall (1963) and Wang (2002), OM is only briefly mentioned in other reviews of maintenance policies. Reviews done by Thomas (1986) and Nicolai and Dekker (2008) do include a short discussion on the concept of OM, yet the authors did not directly use the term OM to define the policy being introduced in their papers. Both literatures discussed and used the concept of component dependency to one Research Approaches in Opportunistic Maintenance Review 10% Case Study 21% Figure 3. Percentage of publications on research approaches in OM research Simulation 7% Numerical Analysis 62% Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) another for deteriorating items in multi-components systems. The aim of the reviews is to find the optimal maintenance for the system. Similar to review papers, case studies and simulation papers discussing OM application are hard to find. Despite an abundance of papers conducting numerical analysis of OM, few or almost no real world applications have been done following the models or computational-based approaches presented. The main problem can be attributed to the complex equations and assumptions used in the studies. As hypotheses, assumptions and limitations are commonly applied in computation analysis; it still cannot be implemented in real industry without focusing only on the most promising possibilities or by using partial (incomplete) data for performance measures. More often, the publications presenting case studies in real industry are too specific for the company’s system and lack the flexibility for further improvement or implementation in another company or industry. Therefore, further analyses on the applications of these methods are very much required in order to provide a proper framework of OM policy. Opportunistic maintenance 109 3.3 Classification from the performances measures perspective The core issue in OM research concerns the technical and economical conditions of the components for conducting replacement or repair. Another factor analysed in this paper is type of performance measure or criteria used by researchers in order to calculate and analyse the practicality as well as the effectiveness of OM. From the conceptual analysis conducted on the publications of OM, age and cost are the basic standard or principle by which were used to measure the performance of the OM system. Figure 4 shows the pie chart of optimal criteria used in literature to measure the effectiveness of OM activities. Because money is always the definite performance measure agreed by both researchers and practitioners, almost half of research concerns the performance on maintenance cost. The critical point is whether the OM conducted is cost-effective or not. This issue was extensively discussed by Mohamed-Salah et al. Optimal Criteria in Opportunistic Maintenance Others 6% Failure rate 4% Failure rate and Cost 9% Age 16% Age and Cost 16% Cost 49% Figure 4. Percentage of publications on various optimal criteria’s in OM research JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 110 (1999), Pham and Wang (2000), Rao and Bhadury (2000), Saranga (2004), Zhou et al. (2006), Besnard et al. (2009) and Laggoune et al. (2009). The early researchers (McCall, 1963; Radner and Jorgenson, 1963) started to investigate how the component failure rate can be reduced by conducting OM on a two-component system. The failures are assumed to happen stochastically throughout the production process and are considered as “opportunities”. As the wisest step is to take advantage of the situation and replace other parts as well, the researchers focused on the planning, scheduling and decision making of OM activities to save maintenance time and improve machine availability. Further on, cost becomes the main concern for most researchers. Savic et al. (1995b) stated that the choice depends on the probability distribution of components’ residual lives and also on the cost of maintenance if it was carried out on a not-yet-failed component. Maintenance costs included cost for repair as well as the cost of the machine downtime (Taghipour and Banjevic, 2012a). For Tan and Kramer (1997), cost is calculated based on production lost per unit time due to machine failure and production stoppages. Aside from that, Bevilacqua and Braglia (2000) included manpower and spare parts costs when calculating the maintenance cost when conducting OM. Laggoune et al. (2009, 2010) conducted research on OM cost structure and suggested that deterioration-based decisions can be included to solve the cost issue. The solution is found by analysing the cost or benefit balance of the component that can be preventively replaced during CM activities. Another common optimal criterion used in performance measurement is the age or reliability of component. To avoid waste in the form of good-age or lifetime of components, age is considered as deterministic factor during analysis. Day and George (1981) used a Bathtub curve to predict a component’s life limits. Mann et al. (1995) and Cassady et al. (2001) used Weibull wear out distribution while Satow et al. (2000) and Cheng et al. (2012) used the Poisson process to identify opportunities for maintenance. In recent years, researchers like Chien (2009), Laggoune et al. (2010) and Xiang et al. (2012) actively applied Weibull distributions to forecast a component’s lifetime and failure. The intention when using these tools is to ensure components replaced during OM are near their useful lifetime and to reduce spare parts cost. Mohamed-Salah et al. (1999) stressed out that OM can be applied only if certain technical and economical conditions in the maintenance system are satisfied. Therefore, aside from cost and age, some research focused on finding the balance between low maintenance cost and high component reliability. There are some researchers like Bevilacqua and Braglia (2000), Scarf and Deara (2003), Jiang and Ji (2002) and Derigent et al. (2009) who used multiple optimal criteria in decision making and planning of OM activities. Their aim is finding the optimal maintenance system when implementing the OM concept. 4. Application of OM in industries Despite numerous publications reported in relation to OM, its application in real industry remains limited. Nevertheless, this section of the paper will discuss the publications that apply and analyse the OM concept as an effort to show where OM is used and how practical the concept is. From the perspective of real industry, the concept of “opportunity” is twofold. First, it is applied when a shutdown of a system for CM activities takes place. Second, an opportunity is taken when the system is down for PM, in other words the PM is meant for the scheduled replacement of a component where OM is applied on the other maintenance-significant components which have the potential to fail in the near future (Savic et al., 1995b). Combining the two policies, OM was developed with the practice of conducting PM on failure-prone components Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) when performing CM on a failed component. OM can be conducted either by choice or based on the physical condition of the equipment (Cui and Li, 2006). OM can be considered as a modification of run-to-fail maintenance management philosophy (Samhouri, 2009). Generally, as a result from this opportunity, total equipment downtime and maintenance costs will be reduced. Tan and Kramer (1997) applied OM in a chemical processing plant for PM optimization. Similar to a nuclear power plant, the chemical industry requires timely and effective maintenance because of the sensitivity and criticality of the equipment and machines. The number of scheduled breakdowns for maintenance need to be reduced to the minimum because the researchers found that lost production costs (net income lost) in a chemical plant can range from $500 up to $100,000 per hour. Even worse, a typical chemical refinery was estimated to lose $20,000 to $30,000 per hour out of their production costs due to equipment failures. This estimation is based on ten days of lost production per year excluding scheduled outages. Tan and Kramer (1997) studied the idea of optimally utilizing system downtime opportunities (CM activities) to perform PM at a lower overall cost. Monte-Carlo simulation with a GA approach was used to find the cost-effectiveness of OM in the chemical plant. For research carried out by Samhouri (2009), GAs were employed to decide whether the OM activity is cost-effective or not. The research focused on OM strategy that involves several non-linear variables which affect the total cost of maintenance that should be optimized to achieve cost-effective decisions on maintenance activities. GAs were found to be well-suited to solve maintenance problems where there is a huge space of potential solutions available. Other than that, Scarf and Deara (2003) considered OM policies in a simulation study of block replacement and modified BRPs for a two-component system. This simulation focused on system reliability and cost-effectiveness or economic dependence. It was discussed that policy IVc1 (opportunistic independent modified block replacement) and policy IVc2 (opportunistic group modified block replacement) are among the near-optimal policies found in the research. Nilsson et al. (2009) applied OM in a nuclear power plant by reconstructing replacement schedules of shaft seals in a feed-water pump system. The approach used is calculating the total cost of maintenance and then minimizing the cost according to some constraints, and discounting to model the value of money in time. After that, a sensitivity analysis was done where the different parameters vary in relation to the discount rate. The conclusion drawn is that the OM optimization model is a deterministic model and applicable in practice. Amari and McLaughlin (2004) also focused on an optimal maintenance model. The research involved Markov analysis to provide a closed-form analytical solution for their model. The researchers stressed the importance of minimum overall maintenance costs or maximum system performance measures. Both issues are at the core of OM principle. One of the concerns in the publications is how OM is considered as an interruption to production operation. Iung et al. (2007) emphasises the integration of maintenance and production strategy planning in developing OM tasks that keep conjoint the product-production-equipment performance. This is done by developing an OM task by synchronizing it with production and keeping the production and the equipment performances simultaneously to preserve the product conditions. It means moving from a conventional maintenance approach towards new condition-based and predictive ones performed only when a certain level of equipment deterioration (impacting product conditions) occurs rather than after a specified period of time. Opportunistic maintenance 111 JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 112 Odds algorithm was used as a decision-making tool relevant to find the right place to stop, among the production stops, for performing optimal “just-in-time” maintenance action. In a different research area, Bonarini and Sassaroli (1997) applied the opportunistic concept and present an Opportunistic Model-Based Diagnosis System (OMISSYS) – a system to diagnose faults or failures in plants whose components are described by different types of models. As models and data are prone to be affected by uncertainty and imprecision, OMISSYS applies opportunistically different reasoning mechanisms on available models to find a set of diagnoses for a given system. The results show that the system is able to speed up the reasoning process by focusing on the most promising aspect of the plant. This research is a good example of how an opportunistic concept can save time and produce an optimal system. This way, a company can reduce the amount of equipment shut down for maintenance and have a more productive operation. Current research on OM revolves around the optimization of the maintenance system. Instead of using the common OM principle as discussed in Section 2, Levrat et al. (2008) studied the age of components for repair and failure with an odd-based decision-making tool. The aim is to have effective and synchronized activities between maintenance and production. Another informative research is by Derigent et al. (2009) who used Fuzzy modelling to assess the proximity of components when conducting OM. Numerical analysis was conducted within the decision-making process in order to achieve optimal maintenance. The situation is that when maintenance is conducted on a component, the technician or operator will locate another component close to the previous component so that additional maintenance actions can be undertaken. The other components also need to be controlled and maintained within the time allocated for maintenance. Similar to Levrat et al. (2008), this research strove to make OM practical and help the decision maker to optimize maintenance activities according to resources, material and time available in the company. 5. Findings and suggestion of future work Swanson (2001) categorized various types of maintenance policy into three main groups, named as reactive, proactive and aggressive maintenance approaches. Each approach has a designated technique regarding how the policies were implemented in a system. In the case of reactive maintenance, a fire-fighting approach was used where equipment in a system is run until it experiences a failure before any replacement or repair tasks are conducted. This approach is commonly used in the early history of maintenance systems and an example of the policy is CM. The approach of the proactive maintenance system contradicts the first group. Applying a preventive principle, the approach is to monitor the condition of each piece of equipment and then conduct maintenance tasks before the equipment fails. This is done in order to avoid equipment breaking down when it is operating. Policies like PM and RCM are best to describe the approach. The third group, aggressive maintenance, used an improvement approach. The principle is to conduct analysis and plan for improvement of the overall equipment operation. This type of approach not only focuses on the equipment itself but also on maintenance management, resource allocation and production rate. TPM falls under the aggressive approach. Looking at these three types of approach, the principle of OM does not fit in any of these groups. Instead, OM is best grouped under a new approach introduced by Khazraei and Deuse (2011). In the review on the taxonomy of maintenance policies, the Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) new approach is called prospective maintenance. The character of this approach is that PM tasks are conducted when a machine breaks down due to failure. According to Sherwin (1999), OM have a rule of conducting preventive tasks that are due or overdue on a system which was forced to stop because of a component’s failure. The stoppage is treated as an opportunity and aims to reduce the cost and time to conduct maintenance on the system. Based on the literature studied, a few more findings can be discussed regarding the merits, demerits and future of OM research. 5.1 Merits in implementing OM According to Tan and Kramer (1997), performing OM on components in a system will improve its overall reliability; reduce future or potential downtime and, at the same time, increase the production rate and a company’s net income. The advantage of OM is that CM combined with PM can be used to save set-up costs (Cui and Li, 2006) and to guarantee the expected performance of the system (Levrat et al., 2008). Companies can also save the set-up time for equipment by reducing the total amount of downtime due to failures. Cassady et al. (2001) put the situation as doing more at less cost. For Dekker and Dijkstra (1992), opportunities in OM policy means conducting cost-effective preventive replacement activities on a system when it is not required for service or when it cannot operate. According to Pham and Wang (2000), the process of conducting PM on non-failed but degraded components at the time of CM activities for another failed component may reduce unexpected CM at a fairly low cost. This is because PM together with CM can be conducted without substantial additional expenses. The reduction of maintenance costs was proven in case studies in a wind turbine system (Besnard et al., 2009) and in oil-refining facilities (Laggoune et al., 2009). OM also helps to optimize maintenance activities and decision making. Indirectly, OM can improve production quality and yield. Without unplanned downtime caused by failures, availability of machines will be high and their effectiveness will be improved. Also, repairing equipment before breakdowns will improve the equipment reliability and extend its lifetime (Zhou et al., 2009). Based on the benefits of OM stated in the literature, it can be concluded that the main benefits of implementing OM can be divided into three groups. The first group is the reduction of failure, the second is the reduction of cost and the final group is increment in equipment/system age. 5.2 Demerits and issues of OM The OM principle is that whenever maintenance is conducted on a failed component, other maintenance-significant components which have the potential to fail in the near future will also be repaired or replaced. The challenge is to find the maintenance-significant component. The researchers contemplate the possibility that a good component will be replaced during OM which will lead to other problem such as higher maintenance and spare parts costs. Then OM can no longer be considered as a cost-effective approach. The direct costs due to component failure and replacement are usually very high, and the impact of the different replacement intervals on the overall maintenance cost is often sensitive and significant (Laggoune et al., 2009). The findings from research by Liang (1985) highlighted that the “opportunity” concept actually performed worse than standard PM policy. It only becomes economic and effective when a system has many components as well as experiencing high failure rates. So much so that it can be concluded that OM is not cost-effective for single unit systems. However, multi-components systems would require complex planning and Opportunistic maintenance 113 JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 114 scheduling of maintenance activities. Other than that, Besnard et al. (2009) argue that OM has a problem with time constraints on the production line. As is already known, any maintenance activities will interrupt or cause the production line to stop its operation, thus the OM with combination of CM and PM will take more time to be conducted. This will create a loss of production rate and product sales. Then the company may face an increase in production costs due to product back-ordering (Zequeira et al., 2008). Hence, in order to have an optimized maintenance system, researchers need to find the best combination of CM and PM activities each time a failure occurs. Aside from that, the big issue with OM is whether maintenance activities conducted under the policy are “underdone” or “overdone” (Wang et al., 2008). The calculations in OM always evolved around the two issues, one is finding the optimal maintenance with the minimum overall cost and two is finding an optimal system that maximizes the system’s performance measure (Amari and McLaughlin, 2004). Researches need to solve these issues in order to allow OM to achieve an optimal system. The optimal maintenance system is the one that strives to ensure no excessive maintenance is conducted as it will result in high maintenance costs, while an inadequate amount of maintenance will cause a system to experience failures or drift into an undesirable state (AlDurgam and Duffuaa, 2013). Another OM drawback is regarding the planning and scheduling of maintenance activities. Cui and Li (2006) stated that by combining CM and PM, one may not know in advance which maintenance action should be taken. Thus, there is the likelihood of sacrificing the plan-able feature of PM, so it is not possible to conduct work preparation in advance (Levrat et al., 2008). An unexpected production demand or a spare parts shortage can also cause problems in OM activities (Zequeira et al., 2008). Nevertheless, this drawback can be remedied by having effective maintenance planning and scheduling. Carefully planned activities will avoid redundancy of tasks, while good maintenance scheduling will ensure companies are prepared in terms of human resources and spare parts for the activities. 5.3 Future work The increase of publications in relation to years shows the potential of OM policy. Still, more publications on the matter are required because its theory is not fully developed. There are also a few issues that need to be scrutinized and improved. Even though OM is found to have originated from ARP and BRP concepts, no publication directly addresses the issue and studies the evolution both in theory and in real industry application. As discussed in Sections 2.2 and 2.3, ARP focuses on the age of components were they to be maintained or replaced separately, but BRP focuses on maintenance on a group of components. Both policies contradict one another yet were claimed as the backbone of OM policy. Therefore, it would be interesting to see the connections between ARP, BRP and OM from a principle point of view. More research is needed on the issue so that OM can be more practical and easy to implement. These connections are also crucial for the development of OM assumptions, rules and limitations for industry application. From a maintenance planning point of view, the issues awaiting exploration in OM research can be divided into short-term, middle-term and long-term challenges. The short-term challenge is the maintenance planning and scheduling of multiple-component systems in both parallel and series systems. Research is required in this area especially for manufacturing plants with various processes Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) and multiple machines for each process. There should be some way to properly plan OM on the multiple machines to achieve an optimal maintenance system. The middle-term issue is concerned with production rate. OM application will affect the number of products manufactured in the maintained systems. Therefore, researchers should focus on the challenge of ensuring maintenance conducted not only does not interrupt the manufacturing process, but also that the tasks should be planned to accommodate the production plan so the machine availability is as high as possible. The ideal situation would be that the machine operated whenever required and did not experience failure during operation. Finally, the long-term challenge is how the application of OM policy can benefit a company in the quest to be a leader in the industry as well as achieving world class operation and quality. This concern about the effectiveness and optimality of OM can lead a company into becoming a successful organization. This way, maintenance will be an important value-added system in the company. Aside from that, future work should explore the OM concept from different optimal criteria in a maintenance system. For the purpose of achieving an optimal situation, it is not the case of achieving a perfect balance between all parameters in a system because that is an impossible feat. The process required a complex system with some criteria need to be weighted according to their importance. The best way to achieve the situation is by having a specific aim or objective of performance measure to be fulfilled. Future research can be directed into development of a standard decision support system for an optimal maintenance system. The model can consist of a few key performance measures like failure rate, maintenance cost and reliability of equipment as factors which then can be chosen according to the company’s aim and objective for improvement. Artificial intelligent methods such genetic algorithm, Fuzzy logic and Poisson distribution can be applied to achieve an optimized OM system. Another branch of research that can be explored in OM policy is regarding the practical rules or framework for implementation in the industry. The numerical analysis and theories in OM research need to be translated into practical theories for practitioners. As mathematical models developed for OM are always custom-made to fit certain situations selected by the researcher, it cannot be immediately implemented in the real system. Some adjustment with assumptions, limitations and rules should be developed for successful implementation of OM in the industry. That way, OM can be proved to be a catalyst for an optimal maintenance system. Aside from that, more extensive analysis should be done based on real data from companies to test the practicality of OM concepts in the industry. Studies and simulations of OM activities are also very much needed in finding the optimal trade-off especially between cost and reliability. A simulation of a maintenance system is required to reduce the gap between theories and practical implementation. As there is lots of numerical analysis published and models introduced in OM research, it should be simulated to find loopholes and test its practicality. 6. Conclusions Effective and optimized maintenance systems are highly acquired in today’s manufacturing system. First coined in the 1963, OM is known as a simple “opportunistic replacement policy” to unique names like “piggyback maintenance” and “all opportunity-triggered replacement”, and the OM concept has been applied in maintenance systems for decades. The number of publications has gradually increased Opportunistic maintenance 115 JQME 20,2 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 116 over the years, showing an encouraging trend and growing interest on this maintenance policy. OM is commonly applied in research on optimal maintenance systems as well as in effective maintenance policy. The OM concept has been widely and numerically studied for maintenance scheduling for multiple components, single component and two components as well as multi-equipment and multi-component systems. This policy evolves from age replacement and BRPs which used the concept of components’ relation to one another in a system to conduct maintenance simultaneously. Most publications provide numerical analysis and models on the optimal scheduling with a trade-off between the age of a component and maintenance cost when conducting OM. OM is the planning and scheduling of an optimal maintenance system that prospectively conducted PM activities on dependent/related components when a component failed, with consideration for the lowest maintenance cost possible and without sacrificing its reliability. 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About the authors Hasnida Ab-Samat received a BEng (Hons) degree in Manufacturing Engineering with Management from the Universiti Sains Malaysia in 2007, and completed her MSc in the School of Mechanical Engineering at the University Science Malaysia (USM) in 2010. She is currently pursuing a PhD at USM. Her research interests include industrial engineering, manufacturing systems and maintenance management. Dr Shahrul Kamaruddin received a BEng (Hons) degree from the University of Strathclyde, Glasgow, Scotland in 1996, a MSc degree from the University of Birmingham, UK, in 1998, and a PhD from the University of Birmingham in 2003. He is currently an Associate Professor in the School Mechanical Engineering (under the manufacturing engineering with management programme), Universiti Sains Malaysia. He has various past experiences with manufacturing industries from heavy to electronics industries especially in the field of industrial engineering, manufacturing processes and product design. He has more than 60 publications in reputed international and national journals/conferences. His current research interests include simulation and modelling of manufacturing systems, production planning and control, maintenance management and application of artificial intelligence techniques in manufacturing. Dr Shahrul Kamaruddin is the corresponding author and can be contacted at: meshah@eng.usm.my To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints Opportunistic maintenance 121 This article has been cited by: Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:21 08 February 2015 (PT) 1. Binghai Zhou, Jiadi Yu, Jianyi Shao, Damien Trentesaux, Salih Duffuaa, M Bendaya. 2015. Bottleneckbased opportunistic maintenance model for series production systems. Journal of Quality in Maintenance Engineering 21:1. . [Abstract] [PDF] Journal of Quality in Maintenance Engineering Improvement of industrial performance with TPM implementation Teonas Bartz Julio Cezar Mairesse Siluk Ana Paula Barth Bartz Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:18 08 February 2015 (PT) Article information: To cite this document: Teonas Bartz Julio Cezar Mairesse Siluk Ana Paula Barth Bartz , (2014),"Improvement of industrial performance with TPM implementation", Journal of Quality in Maintenance Engineering, Vol. 20 Iss 1 pp. 2 19 Permanent link to this document: http://dx.doi.org/10.1108/JQME-07-2012-0025 Downloaded on: 08 February 2015, At: 00:18 (PT) References: this document contains references to 36 other documents. To copy this document: permissions@emeraldinsight.com The fulltext of this document has been downloaded 420 times since 2014* Users who downloaded this article also downloaded: Elaine Aspinwall, Maged Elgharib, (2013),"TPM implementation in large and medium size organisations", Journal of Manufacturing Technology Management, Vol. 24 Iss 5 pp. 688-710 http:// dx.doi.org/10.1108/17410381311327972 Abhishek Jain, Rajbir Bhatti, Harwinder Singh, (2014),"Total productive maintenance (TPM) implementation practice: A literature review and directions", International Journal of Lean Six Sigma, Vol. 5 Iss 3 pp. 293-323 http://dx.doi.org/10.1108/IJLSS-06-2013-0032 Jitendra Kumar, Vimlesh Kumar Soni, Geeta Agnihotri, (2014),"Impact of TPM implementation on Indian manufacturing industry", International Journal of Productivity and Performance Management, Vol. 63 Iss 1 pp. 44-56 http://dx.doi.org/10.1108/IJPPM-06-2012-0051 Access to this document was granted through an Emerald subscription provided by 448547 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. 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The current issue and full text archive of this journal is available at www.emeraldinsight.com/1355-2511.htm JQME 20,1 Improvement of industrial performance with TPM implementation Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:18 08 February 2015 (PT) 2 Received 19 July 2012 Revised 21 July 2013 Accepted 12 October 2013 Teonas Bartz, Julio Cezar Mairesse Siluk and Ana Paula Barth Bartz Federal University of Santa Maria – UFSM, Santa Maria, Brazil Abstract Purpose – The purpose of this paper is to show the implementation of a maintenance management model based on total productive maintenance (TPM) in a production line of a metallurgical company, with high-precision equipment requiring effective maintenance to maintain the quality of the production process. Design/methodology/approach – Has been proposed a model for conducting the activities, emphasizing the training activities of the teams involved in the implementation, collection and analysis of industrial performance indicators from a year before the implementation of TPM. The development followed the timetable of activities and the results of these performance indicators were collected again after the application of the model. Findings – It observed that after the implementation of TPM, and the results of these performance indicators were collected again after the application of the model. Thus, it is concluded that the TPM assists in improving industrial performance and competitiveness of the production line studied. Originality/value – The angle, from which the paper approaches the TPM problem, is original for the studied company and shows positives results. It allows the company to apply the model in their others production lines and factories to achieve an improvement in industrial performance and competitiveness. Keywords Competitiveness, Total productive maintenance, Maintenance management, Performance indicators, Performance evaluation Paper type Case study Journal of Quality in Maintenance Engineering Vol. 20 No. 1, 2014 pp. 2-19 r Emerald Group Publishing Limited 1355-2511 DOI 10.1108/JQME-07-2012-0025 1. Introduction Competition between organizations is ever-increasing. According to Phusavat and Kanchana (2008), some factors considered as priorities to achieve competitiveness are: quality, reliability, flexibility, ability to meet demand and delivery. All of these factors depend on how each organization manages its processes. Furthermore, they all involve production planning and control, personnel management and acquisition of materials in addition to maintenance management. Lollar et al. (2010) emphasize that competitiveness can be achieved by two distinct methods: if the organization has a competitive advantage in cost or by differentiation, whether it is of product, service or both. Also, they point out that in addition to evaluating organizational performance, efficiency and the effectiveness of its activities, each organization must also work to increase the value of the activities involved in the process. Singh et al. (2008) suggest that organizational performance is directly related to the development of research and improvements in methods and procedures, acquisition of assets and in the application of a policy of continuous improvement, innovation and organizational change. Searching this continuous improvement, Yang et al. (2010) show that models for achieving them, such as total quality management and just-in-time, Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:18 08 February 2015 (PT) coupled with the collaboration of suppliers may favor the development of these improvements. The maintenance sector is undergoing a change of concept for entrepreneurs. Previously seen as a support sector, it is now treated as strategic since to reach the expected results the machinery and equipment must meet the expectations and plans made. Maintenance, with a strategic vision for a competitive environment, requires to look beyond the recovery of damages, the quality and productivity; interfering with organizational outcomes (Otani and Machado, 2008). These components are related to a modern management system and an efficient, economical and profitable production system (Khan and Darrab, 2010). For a production system to act without waste and be profitable, the maintenance system should operate effectively. This becomes necessary because the large investments made in organizations should generate profits, and the best way to maintain the operation of equipment, is by managing its maintenance. Regarding TPM as a strategic management model of maintenance, all areas of the company will work following this model. TPM integrates actions, transforming the traditional models of management through the continuous search for: eliminating waste, improving people, improvement of production processes, quality and service. With this transformation will come an evolution of the company in search of higher competitiveness. Therefore, using a data-driven approach and presented by Verron et al. (2010), the importance of maintenance management in achieving organizational goals was shown. Peres and Lima (2008) point out that it is also necessary to take a systemic view of the company so that decision making is quick and correct. Having this in mind techniques and maintenance strategies are used with focus on the prevention of equipment failures, and increasing equipment availability for operation and reliability when in use. Among these strategies and techniques, preventive maintenance, predictive maintenance, total productive maintenance (TPM) and more recently, the reliability-centered maintenance stand out (Khalil et al., 2009). Traditional methods of maintenance planning only partially meet businesses’ needs. Corrective maintenance should be employed in cases where preventive and predictive maintenance becomes costly, but with it comes the risk of downtime and unexpected drop in production. For Karim et al. (2009) this risk made it necessary to develop different methods of maintenance in recent years in order to manage the complexity generated by the technological evolution of equipment. Currently one of the most accepted method is reliability-centered maintenance, a means used to ensure confidence in equipment (Khanlari et al., 2008). In that sense, the adoption of a model of strategic maintenance management such as TPM has been increasingly accepted in industrial organizations. On the order hand, it is clear that many companies do not deploy this model in the right way because the correct application of a maintenance management model (and to observe and obtain the results) takes an estimate of five years. What is observed is that companies try to apply TPM and abandon the program because they do not see immediate results. The aim of this paper is to present the results of the implementation of a TPM-based maintenance management model in a production line in order to improve the performance and competitiveness of a metalworking company. 2. Maintenance Maintenance of industrial equipment has been a growing topic of discussion in the business environment, as the purchase of new equipment is becoming increasingly TPM implementation 3 JQME 20,1 Downloaded by UNIVERSITY OF WESTERN SYDNEY At 00:18 08 February 2015 (PT) 4 unviable, mainly due to the high cost of new technologies. Therefore, equipment care has become very important. In principle, maintenance simply consists of keeping equipment in working condition. Currently, maintenance consists in involving the person who works with the equipment in order to predict when it might suffer a breakdown and make the necessary improvements to ensure the best course of action. Moubray (2000) presents a maintenance evolution in four phases. The first generation, from 1940 to 1950 includes corrective maintenance. The second generation, from 1950 to 1980 basically works with preventive maintenance. The third generation, from 1980 to 2000, contains the TPM, the reliability-centered maintenance and predictive maintenance. For this author, we are the fourth generation since 2000, working with proactive maintenance, which seeks to adapt to the strategic goals of the company. Maintenance can be seen as a necessary evil, as a partially integral part of strategic planning for business productivity, and also as fundamental to equipment availability. From simple production service to the part which is essential in ensuring customer service by improving the reliability of equipment and processes. These are ...
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