In this study, the grey system theory is used for the first time to eliminate the uncertainties in the line balancing problem of U-type assembly lines, which are the most sensitive lines that can be easily affected by systemic and environmental parameters. Task times and learning effect are encoded with grey numbers for the U-type line balancing problem.
A 0–1 mathematical model is developed by considering the grey learning effect and grey task times within the framework of grey system theory, which aims to minimize the number of workstations (Type-1) by considering the uncertainty of the learning effect and task times.
Findings highlight the fact that by considering the grey learning effect and grey task times for U-type assembly lines, the number of required workstations can be decreased, while line efficiencies can be increased.
This study makes a significant contribution to the literature by introducing the novel application of grey theory and grey numbers to handle uncertainties in task times and learning effects within U-type assembly line balancing problems.
