A decision support model for efficient garment reprocessing for a sustainable circular business model.

Abstract

The rapidly growing fashion business has intensified environmental, and sustainability concerns due to its focus on high-volume production at low costs. The rental-based business models in the circular economy, by promoting an alternative approach to garment ownership, aim to mitigate environmental impact, enhance businesses' competitiveness, and provide user value to customers. The rapid reprocessing of garment rentals offered to customers boosts corporate earnings and mitigates environmental issues. However, considering the complexities of garment reprocessing and fluctuations in rental demand, the objective of this study is to use an open Jackson queueing network with a decomposition approach to analyse the effects of external arrival rates and worker's processing rates on lead processing time and throughput for different garment types. The tradeoff curves provide a sensitivity analysis by varying the external arrival rate and the worker's processing rate to examine their impact on lead time and throughput of garment types. The results based on the workcell utilization demonstrate the tradeoff in throughput of various garment types by varying process parameters in the garments reprocessing. The results indicate that deviations in process parameters beyond certain upper and lower thresholds result in reduced throughput and increased lead time for garment types. The rearrangement of workers in the reprocessing workcell network showed a favourable improvement in the throughput of garment types. The findings significantly benefit the garment sector by offering a methodical approach for efficient processing, consequently improving overall efficiency and sustainability, and promoting circular economy efforts.