Optimal joint preventive maintenance and production policies

We study joint preventive maintenance (PM) and production policies for an unreliable production-inventory system in which maintenance/repair times are non-negligible and stochastic. A joint policy decides (a) whether or not to perform PM and (b) if PM is not performed, then how much to produce. We consider a discrete-time system, formulating the problem as a Markov decision process (MDP) model. The focus of the work is on the structural properties of optimal joint policies, given the system state comprised of the system's age and the inventory level. Although our analysis indicates that the structure of optimal joint policies is very complex in general, we are able to characterize several properties regarding PM and production, including optimal production/maintenance actions under backlogging and high inventory levels, and conditions under which the PM portion of the joint policy has a control-limit structure. In further special cases, such as when PM set-up costs are negligible compared to PM times, we are able to establish some additional structural properties. © 2005 Wiley Periodicals, Inc. Naval Research Logistics 52: 668 - 681, 2005.

[1]  T. W. Sloan,et al.  A periodic review production and maintenance model with random demand, deteriorating equipment, and binomial yield , 2004, J. Oper. Res. Soc..

[2]  Xiaodong Yao.  OPTIMAL PREVENTIVE MAINTENANCE POLICIES FOR UNRELIABLE QUEUEING AND PRODUCTION SYSTEMS , 2003 .

[3]  Sudeep Sarkar,et al.  Optimal preventive maintenance in a production inventory system , 1999 .

[4]  Martin L. Puterman,et al.  Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .

[5]  William P. Pierskalla,et al.  A survey of maintenance models: The control and surveillance of deteriorating systems , 1976 .

[6]  M.C. Fu,et al.  Optimal preventive maintenance scheduling in semiconductor manufacturing , 2004, IEEE Transactions on Semiconductor Manufacturing.

[7]  Ram Akella,et al.  Optimal control of production rate in a failure prone manufacturing system , 1985 .

[8]  J. George Shanthikumar,et al.  Using in-line equipment condition and yield information for maintenance scheduling and dispatching in semiconductor wafer fabs , 2002 .

[9]  F. A. van der Duyn Schouten,et al.  Maintenance optimization of a production system with buffer capacity , 1995 .

[10]  Stanley B. Gershwin,et al.  Manufacturing Systems Engineering , 1993 .

[11]  Jianqiang Hu,et al.  Structural properties of optimal production controllers in failure-prone manufacturing systems , 1994, IEEE Trans. Autom. Control..

[12]  Izak Duenyas,et al.  Integrated maintenance and production control of a deteriorating production system , 2002 .

[13]  Richard M. Feldman,et al.  A survey of preventive maintenance models for stochastically deteriorating single-unit systems , 1989 .

[14]  Zikuan Liu,et al.  Production and maintenance control for manufacturing systems , 2001, IEEE Trans. Autom. Control..

[15]  P. Whittle.  Restless bandits: activity allocation in a changing world , 1988, Journal of Applied Probability.

[16]  Mahmut Parlar,et al.  A survey of maintenance models for multi-unit systems , 1991 .

[17]  M. Caramanis,et al.  Production control of manufacturing systems with production rate-dependent failure rates , 1994, IEEE Trans. Autom. Control..

[18]  Hongzhou Wang,et al.  A survey of maintenance policies of deteriorating systems , 2002, Eur. J. Oper. Res..