Assessing the impact of a dynamic allocation of continuous improvement in flow shop under uncertain conditions

Abstract

The competitiveness of the companies depends on continuous progress, and the allocation of the continuous improvement is crucial in today’s market competition. The main approaches proposed in the literature are distributed and centralized policies. This research proposes a novel model for resource allocation that surpasses existing methods. It leverages throughput rate evaluation as the core principle. This model considers key improvement parameters and utilizes a mathematical framework to allocate improvement resources to each parameter. The experiments conducted concern failure parameters (Mean Time Between Failures and Mean Time To Repair), setup time, defective rate, bottleneck numbers and the increasing processing time of the bottleneck. The original contribution is twofold: the evaluation considers a wider range of conditions and their impact on flow line’s sustainability. The model emphasizes sustainability by focusing on minimizing the idle time of workstations within the flow line. Numerical analysis of the proposed model reveals a substantial reduction in total idle time improving the related energy consumption. Furthermore, the model achieves a throughput rate that closely aligns with the centralized policy, traditionally considered the most effective approach.

Article history: Received (December 6, 2023); Revised (May 28, 2024); Accepted (June 21, 2024); Published online (July 12, 2024)