<![CDATA[Delayed raw material delivery is a persistent supply chain problem in apparel manufacturing, often causing material shortages, production disruptions, productivity losses, and increased operating costs. Although various supplier selection approaches have been developed, relatively limited research has integrated the economic consequences of supplier performance with multidimensional supplier evaluation to support cost-oriented procurement decisions. This study therefore proposes and validates an integrated supplier selection framework that combines Cost Ratio Analysis (CRA) and Dimensional Analysis (DA) to improve supply chain performance and minimize production losses associated with delayed material delivery. A quantitative industrial case study was conducted using operational data from two apparel manufacturing companies in Bangladesh. CRA was employed to quantify the financial impact of supplier-related delivery delays, while DA was used to rank supplier alternatives according to multiple operational performance criteria. The integrated framework was subsequently applied to identify the most appropriate suppliers for timely raw material procurement. The results demonstrate substantial improvements following supplier selection, with the benefit-to-cost ratio increasing by 50% and on-time raw material delivery improving from 60% to 94%. These improvements contributed to an approximately 20% increase in production efficiency and reduced productivity losses attributable to material shortages. The principal novelty lies in integrating economic impact quantification through CRA with multidimensional supplier ranking through DA within a single, practical decision-support framework validated using real industrial data. The framework provides apparel manufacturers with a transparent and cost-oriented approach for supplier evaluation, strategic sourcing, and production planning, thereby strengthening supply chain reliability, operational efficiency, and competitiveness. ]]>
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