Guy Richard Kibouka, Donatien Nganga-Kouya, Jean-Pierre Kenné, Vladimir Polotski and Victor Songmene
The 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…
Abstract
Purpose
The 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/approach
This 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.
Findings
The 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 implications
Following 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/value
Considering the assumptions presented in this paper leads to a new structure of the control laws for the production planning of manufacturing systems with setup.
Details
Keywords
Abdoulaye Badiane, Sylvie Nadeau, Jean-Pierre Kenné and Vladimir Polotski
The optimization of production imposes a review of facility maintenance policies. Accidents during maintenance activities are frequent, sometimes fatal and often associated with…
Abstract
Purpose
The optimization of production imposes a review of facility maintenance policies. Accidents during maintenance activities are frequent, sometimes fatal and often associated with deficient or absent machinery lockout/tagout. Lockout/tagout is often circumvented in order to avoid what may be viewed as unnecessary delays and increased production costs. To reduce the dangers inherent in such practice, the purpose of this paper is to propose a production strategy that provides for machinery lockout/tagout while maximizing manufacturing system availability and minimizing costs.
Design/methodology/approach
The joint optimization problem of production planning, maintenance and safety planning is formulated and studied using a stochastic optimal control methodology. Hamilton-Jacobi-Bellman equations are developed and studied numerically using the Kushner approach based on finite difference approximation and an iterative policy improvement technique.
Findings
The analysis leads to a solution that suggests increasing the “comfortable” inventory level in order to provide the time required for lockout/tagout activities. It is also demonstrated that the optimization of lockout/tagout procedures is particularly important when the equipment is relatively new and the inventory level is minimal.
Research limitations/implications
This paper demonstrates that it is possible to integrate production, maintenance and lockout/tagout procedures into production planning while keeping manufacturing system cost objectives attainable as well as ensuring worker safety.
Originality/value
This integrated production and maintenance policy is unique and complements existing procedures by explicitly accounting for safety measures.