Towards sustainable manufacturing: A Fuzzy AHP model for multi-dimensional risk evaluation

This study presents a novel application of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) to evaluate multi-dimensional risks in a motorcycle spare parts manufacturing setting, with a strong emphasis on environmental sustainability. Unlike conventional safety assessments that focus solely on worker injuries or equipment damage, this research integrates environmental impact, such as emissions and ecological harm as a core criterion within the multi-criteria decision-making process. By embedding environmental considerations alongside health, asset, and reputational risks, the proposed model offers a more comprehensive and sustainable risk analysis approach. Thirteen hazards across six production activities were assessed, resulting in classifications of extreme (7.7%), high (53.8%), and medium (38.5%) risk levels. Control strategies include elimination, substitution, engineering measures, administrative actions, and PPE. By addressing the complexity and uncertainty in risk prioritization through fuzzy logic and expert input, this study supports SDG 3 (Good Health and Well-being), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action): A rare intersection in risk analysis research that highlights the integration of safety and environmental stewardship in sustainable manufacturing.