Developing a metaheuristic model for the general assembly line balancing optimization based on a new workforce performance index: a case study in the garment industry

Abstract

In garment industries, it is very important to assign fairly workers and tasks to the stations of an assembly line while the precedence relations and resource constraints are satisfied. Many objectives were treated to optimize the working group selection, but consider objectively the workers skills to judge the balancing effectiveness are still non-existent. This paper proposes a new approach for solving the Assembly Line Balancing Problem with workers’ competence hierarchical assignment using the ant colony optimization. According to this approach, the workforce’s performance index is appreciated with a global Competence Index ‘CIg ’ developed on the basis of measurable criteria to rank hierarchically the workers. The global Competence Index ‘CIg ’ is designed integrating 3 objective criteria: global Quality index ‘QIg’, global Activity degree ‘Ag’ and global Attendance Rate ‘ARg’, which are related to 3 parameters expressing, respectively, the work quality degree, the labour efficiency level and the assiduity for a working group. The global Competence Index is considered as a new ‘objective function’ for the ant colony optimization algorithm called ‘ACO−CIg ’. The aim is to find the best solution assigning workers and tasks to an assembly line stations so that the global competence index is maximized. The results showed that the algorithm implementation was useful in real manufacturing process dealing with hierarchical workforce assignments in a reasonable time and allowing to select the best balancing solution, hence, to predict and control the production line’s performance.