Author:
Koochaki Javid,Bokhorst Jos,Wortmann Hans,Klingenberg Warse
Abstract
PurposeThis paper seeks to study maintenance policies on a plant‐wide level. It focuses on the effectiveness of condition‐based maintenance (CBM). It highlights the role of the production context and the importance of using appropriate metrics to assess CBM.Design/methodology/approachA simulation model was developed to explore the effects of production context using traditional performance indicators (costs and availability of each piece of equipment) and a more comprehensive metric (line efficiency).FindingsThe results showed that CBM has the best performance among other PM policies in loosely coupled processes. By contrast, in tightly coupled processes, CBM has a negative effect on the production line efficiency because it increases equipments' blockage and starvation states.Research limitations/implicationsThe simulation model was developed to reflect the reality. Nevertheless, some assumptions have been used to develop the conceptual and computerized model, which can be explored further in future research.Practical implicationsThe idea of this paper originates from empirical findings of fellow researchers. The findings in this paper provide a better understanding of how CBM affects key performance indicators in different production contexts and therefore help managers to appropriately execute CBM programmes.Originality/valueThis study focuses on CBM from a new angle. The majority of the literatures on condition‐based maintenance either discusses pure technical issues, or focusses on single equipment only. In this research, the effectiveness of CBM for two processes is studied and CBM is compared with block and age‐based replacement policies using a comprehensive performance indicator.
Subject
Industrial and Manufacturing Engineering,Strategy and Management,Safety, Risk, Reliability and Quality
Reference47 articles.
1. Al‐Najjar, B. and Alsyouf, I. (2003), “Selecting the most efficient maintenance approach using fuzzy multiple criteria decision making”, International Journal of Production Economics, Vol. 84 No. 1, pp. 85‐100.
2. Amari, S.V. and McLaughlin, L. (2004), “Optimal design of a condition‐based maintenance model”, The Annual Reliability and Maintainability Symposium‐RAMS 2004, pp. 528‐33.
3. Andijani, A.A. and Duffuaa, S.O. (2002), “Critical evaluation of simulation studies in maintenance systems”, Production Planning & Control, Vol. 13, pp. 336‐41.
4. Arts, R., Knapp, G.M. and Mann, L. Jr (1998), “Some aspects of measuring maintenance performance in the process industry”, Journal of Quality in Maintenance Engineering, Vol. 4 No. 1, pp. 6‐11.
5. Baek, J.G. (2007), “An intelligent condition‐based maintenance scheduling model”, International Journal of Quality and Reliability Management, Vol. 24 No. 3, p. 312.
Cited by
19 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献