Determining the efficacy of additive manufacturing for the aerospace spare parts supply chain

Abstract

This thesis investigates how additive manufacturing (AM) based on-demand part production can supplement or replace the traditional production and inventory in typical aerospace’s spare parts supply chain systems. This study focuses on the operational characteristics of AM and its impacts on the overall logistics of plant-level operations. To capture the microscopic operational aspects of the AM production, a discrete-event simulation based approach was adopted, with key AM operation resources (e.g. AM system, operator) and attributes (e.g. AM manufacturing speed, individual part characteristics and demands) accounted for in the modeling process. In addition, a benchmark warehouse inventory model was also established separately based on classic theories, which was subsequently utilized to create a cost/benefit analysis for the AM based part supply strategies versus the traditional strategies. The results from virtual experiments with these models were analyzed in order to gain an understanding of the operational characteristics (e.g., production cost, system utilization, lead time) as a function of various production policies such as machine/operator configurations and part prioritization. Data analysis shows cost savings for AM as an alternative to warehousing under high penalty scenarios. Results also indicate higher cost savings with the addition of extra machines over extra operators to meet capacity. Finally, analysis shows that reprioritizing orders waiting in a queue has higher savings when assessing due date and penalty outcomes.