Design and Performance Evaluation of a Hybrid Sequencing System in an Automotive Assembly Line Using Digital Simulation Techniques
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Abstract
This research addresses the challenge of excessive buffer inventory within an automotive assembly line by integrating discrete-event simulation (DES) with workforce optimization and production sequencing strategies. The study initially involved the development and validation of a simulation model against empirical production data to analyze throughput and cycle time efficiency. Results demonstrate that a mixed-model sequencing strategy, utilizing a 2:1 ratio (standard vs. new model), is optimal. This configuration achieved
a 46.6% reduction in buffer capacity (decreasing from 15 to 8 slots) while maintaining a consistent throughput of 48 units per shift without increasing labor requirements. Further analysis indicates that throughput can be scaled to 58 units per shift with the strategic addition of a single operator. Additionally, the application of the Modified Blocking After Service (MBAS) protocol significantly refined the accuracy of buffer requirement calculations by accounting for downstream constraints. This study provides a robust decision-support framework for managing production complexity and minimizing work-in-process (WIP) inventory in high-variability manufacturing environments.
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