در مسیر یک درک جامع از اختلال در مدیریت عملیات
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|7572||2000||18 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Operations Management, Volume 18, Issue 6, November 2000, Pages 701–718
The paper reviews the literature on maintenance management, integrates key dimensions of maintenance within a taxonomy of maintenance configurations, and explores the impact of differing configurations on contextual factors and operational performance. “Prevention”, “hard maintenance integration” and “soft maintenance integration” were identified as key maintenance variables. Data were collected from 253 Swedish manufacturing companies, and three distinct clusters were identified. “Proactive Maintainers” emphasized preventive maintenance policies. “IT Maintainers” relied on computerized and company-wide integrated information systems for maintenance. “Maintenance Laggers” emphasized all maintenance dimensions to lesser extent than the others. The importance of maintenance prevention and integration differ between contexts. There were subtle performance differences across identified configurations, but preventive and integrated maintenance were more important for companies seeking competitive process control and flexibility. There existed no group with any great emphasis on all three maintenance dimensions, but attaining truly high performance may require a rare mix of the three dimensions. This mix of variables could constitute a hypothesized “World Class Maintenance” group.
Holistic and proactive concepts, such as Lean Production, Just-in-Time, Total Quality Management (TQM), Concurrent Engineering and Supply Chain Management, are becoming important for companies seeking lean processes with short through-put time and zero defects. In most plants, the physical equipment is susceptible to failure through breakdown, deterioration in performance through age and use, and to obsolescence due to improvements in technology. However, the rising importance of “streamlining” the processes and achieving process control and flexibility raises the cost of disturbances, and thus increases the need for reliable and consistent equipment without quality problems. Error-free production with a minimum of stoppages, speed losses and quality defects are, however, still uncommon in industrial practice. Studies indicate overall equipment efficiencies (defined by Nakajima, 1988, as Availability×Performance efficiency×Rate of quality product) in the 40% to 70% range Ljungberg, 1998 and Ericsson, 1997, due to frequent process disturbances. These disturbances may lead to production losses and other indirect “hidden” costs (e.g. bad internal and external environment and safety of operators) that affect the overall performances of the organizations, for example in terms of higher direct production costs, longer through-put times, lower product quality and low customer service. A main reason for disruptions and unavailability in the production equipment is often considered to be the absence of proper maintenance (e.g. Nakajima, 1988 and Ericsson, 1997). Therefore, maintenance should have an important role in operations management research and practices, yet this is not supported by current literature. This paper seeks to fill some of the gaps in the literature on maintenance within operations strategy. The objectives are to review the literature on maintenance management, integrate key dimensions of maintenance within a taxonomy of maintenance configurations, and explore the impact of differing configurations on contextual factors and operational performance. The growing use of advanced information and manufacturing technologies, such as electronic data interchange, enterprise resource planning, activity based costing, flexible manufacturing systems, robotics, and automatic handling systems, may help companies to achieve competitive process control and flexibility. Research in operations strategy has clearly shown that “learning organizations” with decentralized authority and empowered personnel are important prerequisites for achieving the full potential of investments in technology (e.g. Dean et al., 1992, Maffei and Meredith, 1994, Chen and Small, 1996 and Boyer et al., 1997). There was only one study to be found on advanced manufacturing technology (Jonsson, 1999), which emphasized the importance of maintenance, and explained that it is a key variable for achieving high performance in advanced manufacturing technology environments. Maintenance is also a key missing variable in existing works that have explored configurations of operations strategy and infrastructure, and their varied impact on performance. Those studies focusing on the competitive capabilities of operations strategy Miller and Roth, 1994, Sweeney, 1991 and Sweeney, 1993 are very well cited and have become “basic theory” in operations management. Another taxonomy describing manufacturing structure and infrastructure is also valuable for understanding the role of infrastructure in high-tech companies (Boyer et al., 1996). These configurations are important contributions to operations strategy, but development of a maintenance taxonomy that links maintenance to operations strategy and performance would further the theory and practical development of operations strategies. The paper is structured according to the objectives. First we discuss the development of the maintenance discipline, review the present maintenance literature, and identify three key variables within a cohesive maintenance management approach. Cluster analysis is then employed to identify an empirical maintenance taxonomy based on the three maintenance variables. Survey data is collected from seven Swedish manufacturing industries that together represent the majority of Swedish manufacturing companies. The similarities and differences of contextual factors and operational performance between the three identified clusters are explored by comparing means of the clusters. The paper ends with a discussion on the findings and limitations of the conducted study.
نتیجه گیری انگلیسی
Although the impact of maintenance on the performances of manufacturing companies may be considerable, maintenance strategy has not yet received full attention in practice or in research. The findings of the current paper provide a framework for understanding the role of preventive and integrated maintenance, and for further research on the link between maintenance and performance. It indicates that maintenance prevention and integration are important for the manufacturing strategy of a company, but that the mix of prevention and integration could differ between contexts. Those consultants and researchers that have promoted benefits of maintenance often fail to identify contextual issues that may make adoption difficult or ineffective. It is important that managers do not consider specific maintenance practices to be appropriate for all situations. In the current paper, manufacturing companies were clustered into three configurations, based on their emphases on preventive maintenance, hard maintenance integration and soft maintenance integration. The identified taxonomy showed that there was a variety of maintenance investment approaches and that each configuration could be profitable by itself. Further analysis revealed that preventive and company-wide integrated maintenance were important for companies, with high breakdown consequences and stop costs, which seek competitive process control and flexibility. It was proposed that maintenance should be most important in lean manufacturing organizations with “streamlined” processes, but this should be further researched. Profitability was highest for the group with heavy investments in information technology (hard integration). The link between maintenance and profitability, however, should be further analyzed. The measure could not identify proper indications of performance differences or similarities between configurations. A limitation of the conducted study was that the profitability was measured with only one objective measure, which was difficult to compare across industries. Maintenance may not directly lead to high performance, but may affect mediating variables and should be important to a greater or lesser degree in various manufacturing and marketing contexts. A specific approach is not good for all situations and it is believed that contextual studies are important to further improve the understanding of maintenance strategy in different environments. An unexplored research question involves identifying the underlying variables necessary for achieving high performance within respective maintenance configurations. The present study proposes that: “preventive and integrated maintenance is quite important for IT Maintainers and Proactive Maintainers, in order to achieve high performance, but that it is of less importance for Maintenance Laggers”. This hypothesis could be addressed by identifying contextual variables, developing more complex measures of operational performance, and conducting regression analysis. Separate regression models within respective configurations, with independent contextual and maintenance variables and dependent operational performance variables, could then be employed. Another finding was that none of the clusters contained companies that simultaneously emphasized all three dimensions to any great extent. Therefore, it is interesting to analyze whether a high emphasis on all dimensions necessarily relates to increased effectiveness. This question could be studied in a broad based study, similar to the one conducted in this paper, but that focuses on companies in heavy industries with serious breakdown consequences and high stop costs (i.e. companies that need preventive and integrated maintenance). The measures used have some drawbacks and need to be further developed in future research. All measures could be more detailed and expressed as multiple scales. This is especially true for HMAIN, which could cover other aspects than the information system. PMAIN focuses purely on hours spent on policies, but does not tell how well policies are carried out. SMAIN covers various aspects of soft integration. It could be extended and split into a set of related scales.