Optimizing Order Scheduling in Morocco’s Garment Industry for Fast Fashion: A K-Means Clustering-Driven Approach

The Moroccan garment industry faces challenges in scheduling small order batches, often hindered by traditional product family-based methods that increase downtime by 15–20%. This study proposes a clustering-based scheduling approach, grouping garments by technological times rather than product families to reduce changeovers and downtime by 30–35%. A case study in a Moroccan factory with 50–100-unit batches showed a 20% lead time reduction and a 15% productivity boost. Using methods like K-Means, the approach enhances planning flexibility and resource use. This methodology offers a scalable solution for optimizing production and maintaining competitiveness in fast fashion markets.