Service level-based production smoothening model for robust cellular manufacturing system

Abstract

This paper presents a new strategy addressed as “service level-based smooth production strategy” for the cell formation decisions of a robust cellular manufacturing system (CMS) to handle varying demands. In this strategy, a service level concept is adapted to fix smooth production level estimated to meet the desired demand satisfaction rate (DSR) or fill rate of the customers. Besides, the model considers cross-flow and scheduling aspects, which are not often addressed in CMS designs. A non-linear integer program is formulated to evolve CMS decisions for the specified DSR under fluctuating demands. Two solution methodologies of mathematical programming using ILOG CPLEX solver and genetic algorithm (GA) with adaptive mutation and crossover operators addressed in as adaptive genetic algorithm (AGA) are proposed. The model analysis carried out under various DSR reveals that the cell formation decisions are highly sensitive to DSR. This paper also discusses how this model can be used to compare robust and reconfigurable approaches to decide the suitable approach to handle fluctuating demands with minimum cost. The performance study of solution methodologies reveals that CPLEX and AGA are efficient in finding optimal solutions to smaller-size problems. However, AGA is comparatively efficient for larger-size problems with a reasonable computational time.