Abstract
Mass-customization of products imposes new challenges on the planning of assembly lines due to an increased number of product models and a large variety of parts. Traditionally, both academics and practitioners approached the planning of an assembly line by balancing the assembly line, i.e., assigning tasks to stations, and decided on line feeding policies based on this outcome. However, this approach neglects the reciprocal effects between the two decision-making outcomes, i.e., the impact of line feeding decisions on task times and the impact of balancing decisions on feeding requirements and constraints. This interaction is of peculiar interest for assembly lines in a mass-customization environment due to the large number of assembly tasks and parts. Therefore, this study describes a framework that simultaneously optimizes both problems and minimizes overall costs. We show preliminary results using real-world data from a large automotive company.
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