Author:
Kibouka Guy Richard,Nganga-Kouya Donatien,Kenné Jean-Pierre,Polotski Vladimir,Songmene Victor
Abstract
PurposeThe purpose of this paper is to find the optimal production and setup policies for a manufacturing system that produces two different types of parts. The manufacturing system consists of one machine subject to random failures and repairs. Reconfiguring the machine to switch production from one type of product to another generates a non-production time and a significant cost.Design/methodology/approachThis paper proposes an approach based on the development of optimal production and setup policies, taking into account the possibilities of undertaking the setup for all modes of the machine, and covering them at the end of setup. New optimality conditions are developed in terms of modified Hamilton-Jacobi-Bellman (HJB) equations and recursive numerical methods are applied to solve such equations.FindingsThe proposed approach led to determine more realistic production rates of both parts and setup sequences for the different modes of the machine that significantly influence the inventory and the system capacity. A numerical example and sensitivity analysis are used to determine the structure of the optimal policies and to show the helpfulness and robustness of the results obtained.Practical implicationsFollowing the steps of the proposed approach will provide the control policies for industrial manufacturing systems with setup permitted at all modes of the machine, and when the setup does not necessarily restore the machine to its operational mode. The proposed optimal policy takes into account the stochastic nature of the machine mode at the end of setup and we show that ignoring it leads to non-natural policies and underestimates significantly the safety stock thresholds.Originality/valueConsidering the assumptions presented in this paper leads to a new structure of the control laws for the production planning of manufacturing systems with setup.
Subject
Industrial and Manufacturing Engineering,Strategy and Management,Safety, Risk, Reliability and Quality
Cited by
8 articles.
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