Minimization of Work Overlaod in Mixed Model Assembly Lines with Different Types of Operators

Abstract

The problem of sequencing mixed-model assembly lines (MMALs) is considered in this paper. Our objective is to figure out how to sequence the products to minimize work overload by sequencing and utilizing the idle worker available at particular time and line segmentation of operators for further reduction in work overload. This problem is identified as the MMAL sequencing problem with WO minimization using idle time of operators: we clearly use task processing times to find the optimized sequence of products. In this industrial environment, as a reaction to work overloads, operators at workstations accomplish their jobs before the product reaches the next workstation at the risk of fatigue, whereas in this process some operators are idle while others are under constant strain to finish their job. There are also various types of operators, each with their own set of responsibilities. This study is unique in that it models a new manner of reacting to work overloads, integrates three operator types into the sequencing model, and applies an optimized sequence to idle time usage. We validated a past study on metaheuristic technique based on genetic algorithm for further refinement in work overload by idle time utilization and line segmentation. The proposed idle time operator utilization scenarios are verified on industrial records and equated to the solutions attained with the already found solution. Further the solution is expanded by new Embedded Genetic Algorithm by utilizing idle time operators and the results reveal that the recommended strategies significantly improve the outcomes of the case study’s current procedure. Keywords: mixed-model assembly line; work overload minimisation; idle time utilization, sequencing problem ,meta-heuristics, line segmentation