Hybrid manufacturing – integrating traditional manufacturers with additive manufacturing (AM) supply chain

TLDR

Additive manufacturing is increasingly used for low‑volume, high‑value metal parts thanks to improved capabilities and design freedom, yet secondary post‑processing such as machining and heat treatment is required to meet GD&T, surface finish, and mechanical property targets, posing a challenge for traditional manufacturers to adopt direct digital manufacturing without costly in‑house AM investments. This research investigates a system of strategically‑located AM hubs that integrate hybrid‑AM with the capabilities and excess capacity of multiple traditional manufacturing facilities. Using NAICS data for U.S. machine shops, an uncapacitated facility‑location model determines optimal AM hub locations based on geography, demand, and hybrid‑AM processing cost.

Abstract

The ever-growing applications of Additive Manufacturing (AM) in the production of low volume- high value metal parts can be attributed to improving AM processing capabilities and complex design freedom. However, secondary post-processing using traditional processes such as machining, grinding, heat treatment and hot isostatic pressing, i.e., Hybrid Manufacturing, is required to achieve Geometric Dimensioning and Tolerancing (GD&T), surface finish and desired mechanical properties. It is often challenging for most traditional manufacturers to participate in the rapidly evolving supply chain of direct digital manufacturing (DDM) through in-house investments in cost prohibitive metal AM. This research investigates a system of strategically-located AM hubs which can integrate hybrid-AM with the capabilities and excess capacity in multiple traditional manufacturing facilities. Using North American Industry Classification System (NAICS) data for machine shops in the U.S., an uncapacitated facility location model is used to determine the optimal locations for AM hub centers based on: (1) geographical data, (2) demand and (3) cost of hybrid-AM processing. Results from this study have identified: (a) candidate US counties to build AM hubs, (b) total cost (fixed, operational and transportation) and (c) capacity utilization of the AM hubs. It was found that uncapacitated facility location models identified demand centroid as the optimal location and was affected only by AM utilization rate whereas a constrained p-median model identified 22 AM hub locations as the initial sites for AM hubs which grows to 44 AM hubs as demand increases. It was also found that transportation cost was not a significant factor in the hybrid-AM supply chain. Findings from this study will help both AM companies and traditional manufacturers to determine location in the U.S and key factors to advance the metal hybrid-AM supply chain.