Bi-objective optimization-based multi-criteria decision-making framework for disassembly line balancing and employee assignment problem

Abstract

Purpose

Although disassembly balancing lines has been studied for over two decades, there is a gap in the robotic disassembly. Moreover, combination of problem with heterogeneous employee assignment is also lacking. The hazard related with the tasks performed on disassembly lines on workers can be reduced by the use of robots or collaborative robots (cobots) instead of workers. This situation causes an increase in costs. The purpose of the study is to propose a novel version of the problem and to solve this bi-objective (minimizing cost and minimizing hazard simultaneously) problem.

Design/methodology/approach

The epsilon constraint method was used to solve the bi-objective model. Entropy-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization methods for Enrichment Evaluation (PROMETHEE) methods were used to support the decision-maker. In addition, a new criterion called automation rate was proposed. The effects of factors were investigated with full factor experiment design.

Findings

The effects of all factors were found statistically significant on the solution time. The combined effect of the number of tasks and number of workers was also found to be statistically significant.

Originality/value

In this study, for the first time in the literature, a disassembly line balancing and employee assignment model was proposed in the presence of heterogeneous workers, robots and cobots to simultaneously minimize the hazard to the worker and cost.

Citation

Deniz, N. and Ozcelik, F. (2024), "Bi-objective optimization-based multi-criteria decision-making framework for disassembly line balancing and employee assignment problem", Kybernetes, Vol. 53 No. 3, pp. 1073-1091. https://doi.org/10.1108/K-06-2022-0857