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The incorporation of additive manufacturing within the automotive supply chain holds the potential to improve operational efficiency and generate significant cost savings while enhancing sustainability. This innovative model delves into the advantages of integrating additive manufacturing into the production process, emphasizing its ability to facilitate on-demand manufacturing, decrease inventory expenses, and expedite prototyping. The proposed model considers the manufacturing of two types of high-demand spare parts in the automotive industry, assuming constant demand. It conducts a thorough and meticulous evaluation of pre-production, production, post-production, inspection, and parts transportation costs to calculate the total cost. Two hybrid additive manufacturing machines are included in the production process and the results underscore transportation (12.06% of total cost) and setup (84.95% of total cost) as major cost factors, with setup costs incurred only in the first year and depreciated over a decade for long-term financial stability. The optimized model also reduces production cycle time, enhancing sustainability by waste reduction. Leveraging genetic algorithm techniques for optimization and reinforced by rigorous numerical analysis, its efficacy and validity are robustly demonstrated.
Chauhan et al. (Thu,) studied this question.
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