Sequence Based Optimization of Manufacturing Complexity in a Mixed Model Assembly Line

Abstract

Increasing production variability while maintaining operation efficiency remains a critical issue in many manufacturing industries. While the adoption of mixed-model assembly lines enables the production of high product variety, it also makes the system more complex as variety increases. This paper proposes an information entropy-based methodology that quantifies and then minimizes the complexity through product sequencing. The theory feasibility is demonstrated in a series of simulations to showcase the impact of sequencing in controlling the system predictability and complexity. Hence, the framework not only serves as a tool to quantitatively assess the impact of complexity on total system performance but also provides means and insights into how complexity can be mitigated without affecting the overall manufacturing workload.