Towards Additive Manufacturing Enabled Sustainable Spare Parts Supply Chain: A Multi-Objective MILP Model for Cost and Carbon Emissions Minimization

Abstract

Additive manufacturing (AM) enables on-demand production of spare parts and enhances supply chain visibility by downstream shift of part production; however, it poses supply chain redesign challenges. Integration of sustainability objectives into AM spare parts supply chains is vital to evaluate the long-term transition potential of AM to meet global environmental goals and enhance corporate social responsibility. Developing a multi-objective model is critical to address the complex interaction between economic viability and environmental sustainability in AM-enabled spare parts supply chains. This study proposes a mixed integer linear programming model formulated as a bi-objective optimization problem to minimize the costs and carbon emissions of the AM-enabled spare part supply chain operations. A lexicographic approach was used to solve this bi-objective optimization problem with the Gurobi solver. If the cost objective function is given high priority, the optimal cost value is $5,900171 and the total carbon emissions obtained are 138.1 tCO2e. If the environmental objective is given higher priority, the optimal carbon emissions value is reduced to 128.9 tCO2e, however, the cost value obtained is significantly higher at $6523143. These results provide valuable insights for strategic decision-makers to carefully consider the trade-offs between cost and environmental objectives to achieve the desired balance.