A production inventory model with imperfect item and low quality manufacturing under α-cut type-2 fuzzy environment using fuzzy H2 differentiation

This study delves into a fuzzy economic manufacturing model focused on inventory models encountering imperfect and low-quality production processes, inclusive of rework scenarios. The concern arises primarily during epidemics when unsold items accumulate, escalating maintenance costs due to constant deterioration. Uniquely, this research incorporates a special mathematical formulation contrasting discounted lowquality items with non-discounted ones under fuzzy conditions. Enhanced computer techniques founded on fuzzy logic are employed to refine identification, decision-making, and optimization. These situations are depicted through a bi-objective framework aiming for a simultaneous minimization of overall cost and emissions, subject to a meticulously devised constraint set. The significance of optimal manufacturing is accentuated by attributing a triangular fuzzy number to economic production quantity. The EPQ model?s optimal total cost is discerned in its crisp form, meriting emphasis. Production inventory, varying from raw materials to unfinished products, sometimes includes imperfect items, posing significant challenges like increased production costs and delayed processes. Addressing this involves implementing rigorous quality control measures and possibly adopting lean manufacturing principles aimed at minimizing waste and enhancing production efficiency. These strategies aid in maintaining quality, ensuring customer satisfaction, and sustaining profits by mitigating the challenges posed by inferior quality items within the production inventory.