integrated systemic modeling of production scheduling, maintenance, and quality control in closed-loop supply chains

Closed-loop supply chains (clscs) are increasingly recognized as essential frameworks for achieving operational efficiency and sustainability in modern industries. this study focuses on optimizing production scheduling, maintenance strategies, and quality control within clscs, specifically tailored for the home appliances industry. the proposed model integrates preventive and corrective maintenance policies, scheduling, and quality management into a unified system that minimizes costs while enhancing reliability and sustainability. the strategic choice approach (sca) was employed to structure complex decision-making processes, leveraging the expertise of industry professionals to identify key uncertainties and variables. a genetic algorithm (ga) was utilized to optimize decision variables, including sample size, sampling intervals, control limits, and maintenance schedules, ensuring robust solutions under real-world constraints. the model categorizes machine failures into immediate and delayed modes, providing tailored strategies for each to maintain system performance. comparative analyses highlight the integrated model’s superior cost-effectiveness and operational benefits over traditional independent approaches. sensitivity analyses further demonstrate the robustness of the model under varying operational conditions, validating its adaptability and scalability. by addressing the interconnected challenges of maintenance, scheduling, and quality control, this research offers a practical and holistic solution for clscs, contributing to improved operational resilience, customer satisfaction, and alignment with sustainability objectives. the decision-making process provides valuable insights and confident recommendations for future research.