SUPPLY CHAIN MODELING OF ADDITIVELY MANUFACTURED VERSUS CNC-PRODUCED SPARE PARTS

Abstract

This research proposes a generic BLOC-ICE-based framework that considers multiple aspects of the adoption of additive manufacturing (AM) in the spare part supply chain. It proposes also a multi-period multiple parts mixed-integer linear programming optimization model for the trade-off analysis spare parts supply through computer numerical control (CNC) manufacturing and AM. The multiple spare parts have different characteristics including volume, shape size, and geometry complexity. The model focuses on minimizing lead times and thus reducing downtime costs. Scenario analyses are developed for some parameters to test the robustness of the model. The analysis shows that the mix between AM-based spare parts and CNC-based spare parts is sensitive to changes in demand. For the given data, the findings demonstrate that AM is cost-effective with spare parts having high geometry complexity while CNC-based manufacturing is economically feasible for spare parts with low geometry complexity and large sizes. The proposed model can support decision-makers in selecting the optimal manufacturing method for multiple spare parts having different characteristics and attributes.