An evolutionary algorithm for sequencing production on a paced assembly line

A new sequencing method for mixed-model assembly lines is developed and tested. This method, called the Evolutionary Production Sequencer (EPS) is designed to maximize production on an assembly line. The performance of EPS is evaluated using three measures: minimum cycle time necessary to achieve 100% completion without rework, percent of items completed without rework for a given cycle time, and sequence ‘smoothness’. The first two of these measures are based on a simulated production system. Characteristics of the system, such as assembly line station length, assembly time and cycle time, are varied to better gauge the performance of EPS. More fundamental variation is studied by modeling two production systems. In one set of tests, the system consists of an assembly line in isolation (i.e., a single-level system). In another set of tests, the production system consists of the assembly line and the fabrication system supplying components to the line (i.e., a two-level system). Sequence smoothness is measured by the mean absolute deviation (MAD) between actual component usage and the ideal usage at each point in the production sequence. The performance of EPS is compared to those of well-known assembly line sequencing techniques developed by Miltenburg, Okamura and Yamashina, and Yano and Rachamadugu. EPS performed very well under all test conditions when the criterion of success was either minimum cycle time necessary to achieve 100% production without rework or percent of items completed without rework for a given cycle time. When MAD was the criterion of success, EPS was found inferior to the Miltenburg heuristic but better than the other two production-oriented techniques.