Additive Manufacturing of Slow-Moving Automotive Spare Parts: A Supply Chain Cost Assessment

This study develops a cost model for the additive manufacturing (AM)-produced spare parts supply chain in the automotive industry. Moreover, we evaluate the economic feasibility of AM for slow-moving automotive spare parts by comparing the costs of the traditional manufacturing (TM) spare parts supply chain (SPSC) with centralized, outsourced AM SPSC. Data from a multiple case study of an OEM in the automotive industry regarding SPSC is utilized. The supply chain costs of 14 individual spare parts were analyzed, and the total SPSC cost for the AM and TM, were compared. Three of the fourteen parts showed potential for cost-savings, if they were produced with AM instead of TM. In this context, AM polymer parts showed greater potential than metal to replace TM as the more economical option of manufacturing from a total supply chain cost perspective. This study shows that the AM competitiveness to TM, from a financial perspective, increases for spare parts with low demand, high minimum order quantity, and high TM production price. The SPSC cost model included: cost of production, transport, warehousing, and service costs. This study contributes to the emerging field of part identification for AM and the existing literature regarding cost modeling in SPSCs

Identification of aftermarket and legacy parts suitable for additive manufacturing : A knowledge management-based approach

A research stream identifying aftermarket and legacy parts suitable for additive manufacturing (AM) has emerged in recent years. However, existing research reveals no golden standard for identifying suitable part candidates for AM and mainly combines preexisting methods that lack conceptual underpinnings. As a result, the identification approaches are not adjusted to organizations and are not completely operationalizable. Our first contribution is to investigate and map the existing literature from the perspective of knowledge management (KM). The second contribution is to develop and empirically investigate a combined part-identification approach in a defense sector case study. The part identification entailed an analytical hierarchy process (AHP), semi-structured interviews, and workshops. In the first run, we screened 35,000 existing aftermarket and legacy parts. Similar to previous research, the approach was not in sync with the organization. However, in contrast to previous research, we infuse part identification with KM theory by developing and testing a “Phase 0” assessment that ensures an operational fit between the approach and the organization. We tested Phase 0 and the knowledge management-based approach in a second run, which is the main contribution of this study. This paper contributes empirical research that moves beyond previous research by demonstrating how to overcome the present challenges of part identification and outlines how knowledge management-based part identification integrates with current operations and supply chains. The paper suggests avenues for future research related to AM; however, it also concerns Industry 4.0, lean improvement, and beyond, particularly from the perspective of KM.© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).fi=vertaisarvioitu|en=peerReviewed

Additive Manufacturing of Slow-Moving Automotive Spare Parts: A Supply Chain Cost Assessment

This study develops a cost model for the additive manufacturing (AM)-produced spare parts supply chain in the automotive industry. Moreover, we evaluate the economic feasibility of AM for slow-moving automotive spare parts by comparing the costs of the traditional manufacturing (TM) spare parts supply chain (SPSC) with centralized, outsourced AM SPSC. Data from a multiple case study of an OEM in the automotive industry regarding SPSC is utilized. The supply chain costs of 14 individual spare parts were analyzed, and the total SPSC cost for the AM and TM, were compared. Three of the fourteen parts showed potential for cost-savings, if they were produced with AM instead of TM. In this context, AM polymer parts showed greater potential than metal to replace TM as the more economical option of manufacturing from a total supply chain cost perspective. This study shows that the AM competitiveness to TM, from a financial perspective, increases for spare parts with low demand, high minimum order quantity, and high TM production price. The SPSC cost model included: cost of production, transport, warehousing, and service costs. This study contributes to the emerging field of part identification for AM and the existing literature regarding cost modeling in SPSCs