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Item type:Publication, Multiple criteria assessment of sustainability programs in the textile industry(Wiley, 2020-09-14)Abstract To survive in the long term, business needs to profit, controlling environmental impacts with social responsibility. Sustainability programs involve the integration of social and environmental issues in business models and organizational processes. The assessment of sustainability programs is a problem of multiple criteria decision analysis (MCDA). This work presents applications of MCDA for the assessment of sustainability programs in the textile industry. Applied methods for MCDA are analytic hierarchy process (AHP) and the technique for the order of preference by similarity to ideal solution (TOPSIS). The reasons to apply AHP and TOPSIS include providing an assessment index, ranging from 0 to 1, and that the MCDA model is expected to have more criteria than alternatives. Therefore, an application of other methods, such as data envelopment analysis, could be prejudiced. Concepts from the triple bottom line, economic, social as well as environmental criteria were inserted in the proposed model. Sustainability programs of six leading companies from the Brazilian textile industry were evaluated. The main finding of the research is that AHP and TOPSIS resulted in similar evaluations for sustainability programs. Both methods resulted in the same rank of alternatives. However, with TOPSIS, companies' sustainability indices were more disperse, varying from 0.10 to 0.92 against a range from 0.23 to 0.69 with AHP. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Multi-criteria classification of spare parts in the steel industry(Associação Brasileira de Engenharia de Produção, 2025-01-22)Goal: This research addresses the critical challenge of evaluating spare parts inventory in the steel industry to enhance maintenance efficiency and reduce operational costs. Design/methodology/approach: The study applies the Analytic Hierarchy Process (AHP), a widely recognized multi-criteria decision-making (MCDM) method, to develop a robust decision support system. A hierarchical structure of criteria and sub-criteria, along with alternatives (spare parts), was constructed based on an extensive literature review and validated through input from three maintenance and inventory management experts. The system was implemented in a Brazilian steel plant. Results: The AHP-based framework systematically classified spare parts, emphasizing their criticality. Spare Parts 1 and 2 were categorized as Class B, scoring 0.6 and 0.56, while Spare Parts 3 and 4 were classified as Class A, scoring 0.82 and 0.83. These findings confirm the effectiveness of the AHP methodology in prioritizing spare parts for improved inventory management and decision-making. Sensitivity analysis validated the framework's robustness, demonstrating stable classifications across varying criteria weights. Limitations of the investigation: While tailored to a Brazilian steel plant, the framework's scalability is evident. Limitations include its reliance on a specific context and the involvement of a limited number of experts, suggesting opportunities for broader validation. Practical implications: The simplified AHP framework gives managers an accessible tool for classifying spare parts, eliminating the need for complex hybrid methods. It enables efficient decision-making, particularly in industries with high operational demands. Originality: This research contributes a novel multi-criteria decision-making model for spare parts classification, significantly advancing maintenance efficiency and cost-effectiveness compared to traditional single-criterion approaches.1