Knowledge backgrounds and additive manufacturing: moderating effects on part identification approaches and supply chain outcomes: additive Manufacturing for Operations and Supply Chain Management

Abstract

This study investigates how knowledge backgrounds influence part identification in additive manufacturing (AM) decision-making. We examine the interplay between design- and supply chain-oriented expertise in shaping whether firms pursue AM-based redesign or 1:1 substitution. Using a multiple-case study approach, we conducted workshops in two defence-related organisations and one workshop beyond the defence sector, analysing how diverse knowledge backgrounds impact decision outcomes. The findings suggest that while diverse expertise fosters creative potential, effective facilitation is necessary to manage conflicting priorities. We introduce a structured decision framework to support AM part identification by balancing design feasibility and supply chain constraints. This study contributes to knowledge management (KM) in AM by demonstrating how absorptive capacity influences decision-making in AM adoption, with implications for organisations integrating AM into their supply chains.