Title: Optimal cycle time for production-inventory systems considering shelf life and backordering
Authors: Maryam Mohammadi; S. Nurmaya Musa
Addresses: Centre of Advanced Manufacturing and Material Processing, University of Malaya, 50603 Kuala Lumpur, Malaysia; Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia ' Centre of Advanced Manufacturing and Material Processing, University of Malaya, 50603 Kuala Lumpur, Malaysia; Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
Abstract: Recently shelf life during which the items remain safe within the production plants is considered in production optimisation models. This paper addresses manufacturing system with multiple items produced on a single facility having shelf life restrictions and backorders. Backorders incur shelf life constraint alteration, affecting the corresponding inventory models. Accordingly, appropriate modifications are applied to the related mathematical models. The purpose is to determine the optimal cycle time and minimise the long-run average costs. While the cost-minimisation cycle time causes the spoilage of a product due to the shelf life restrictions, proper decisions are made based on one of the three options: production rate reduction, cycle time reduction, and a combination of both. For each option, optimal cycle time and production rate are estimated to satisfy shelf life constraint. Numerical examples are presented to illustrate the influence of production cost, backorders, and shelf life on total cost.
Keywords: multiple items; single facility; cycle time; production rate; backordering; shelf life; cost minimisation; production-inventory systems; production optimisation; manufacturing systems; mathematical modelling; production cost; backorders; inventory management.
International Journal of Procurement Management, 2017 Vol.10 No.3, pp.311 - 334
Received: 14 Mar 2016
Accepted: 30 May 2016
Published online: 31 Mar 2017 *