Optimality of zero-inventory policies for unreliable manufacturing systems
Operations Research
Production lot sizing with machine breakdowns
Management Science
Bounds for production lot sizing with machine breakdowns
Computers and Industrial Engineering
Optimal manufacturing batch size with rework process at a single-stage production system
Computers and Industrial Engineering
Introduction to Operations Research and Revised CD-ROM 8
Introduction to Operations Research and Revised CD-ROM 8
Applied Stochastic Models in Business and Industry
Production systems with rework and machine failure taking place in backorder filling time
CISST'10 Proceedings of the 4th WSEAS international conference on Circuits, systems, signal and telecommunications
Production systems with backordering, rework and machine failure taking place in stock piling time
CISST'10 Proceedings of the 4th WSEAS international conference on Circuits, systems, signal and telecommunications
WSEAS Transactions on Information Science and Applications
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This study examines the optimal run time for the economic manufacturing quantity (EMQ) model with failure-in-work, backlogging, and random breakdown happening in stock-piling time. A recent article by Chiu and Chiu [Mathematical modeling for production system with backlogging and failure in repair, Journal of Scientific & Industrial Research, 65 (2006) 499-506] investigated optimal lot-size for EMQ model with backordering and failure-in-rework. By incorporating random machine breakdown-another inevitable reliability factor into their model, this research examines its effects on the optimal run time and on the long-run average costs. Mathematical modeling and cost analysis are employed and the renewal reward theorem is used to cope with variable cycle length. Convexity of the expected production- inventory cost function is proved. An optimal replenishment policy that minimizes overall costs is derived for such an unreliable system. Numerical example is provided to show its practical usage. Managers in the field can adopt this run time decision to establish their own robust production plan accordingly.