<p>This study combines the development of defects, rework, and scrap disposal in the face of uncertainty to provide a sustainable inventory optimization model for defective manufacturing systems. Production rates that rely on inventories and price-sensitive demand throughout both production and non-production periods are taken into consideration by the suggested framework. This is not the same as conventional strategies, which primarily concentrate on maximizing profits or reducing expenses. Fermatean fuzzy numbers are used to address demand, degradation, and defect rate uncertainty. An effective population-based heuristic for non-linear systems, the Social Group Optimization (SGO) method, is used to address the optimization issue. The optimal method achieves a production rate of 2.20 units/time, a rework rate of 1.20 units/time, and a selling price of $90 per unit while using realistic parameter choices in numerical trials. This yields a total profit of 37,036.4 every cycle, with a 1.78-month cycle period. Sensitivity analysis indicates that profit is positively impacted by increased demand potential, lower inventory levels, and improved rework efficiency. Conversely, an excessive amount of scrap significantly reduces earnings. In order to successfully balance profitability, resource use, and sustainability in uncertain manufacturing environments, the findings suggest that managers should use dynamic production modifications, give rework precedence over trash, and apply fuzzy optimization.</p>