4.6 Article

Supply chain design for industrial additive manufacturing

Journal

Publisher

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/IJOPM-12-2021-0802

Keywords

Additive manufacturing; 3D printing; Distributed manufacturing; Supply chain design; Supply chain governance; Case study research

Categories

Funding

  1. DB Schenker Lab - Technical University of Darmstadt Cooperation Institute

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This study explores the supply chain designs for industrial additive manufacturing and the rationales behind manufacturing firms' decision-making in selecting these designs. The findings highlight the trade-off between economies of scale and market potential from customer proximity, as well as the importance of supplier control and reevaluation of core competencies in governance choice. This study provides practical implications for managers implementing industrial additive manufacturing.
Purpose This study extends and refines the current knowledge on emerging supply chain designs (SCDs) for industrial additive manufacturing (AM) and manufacturing firms' rationales in selecting them. Design/methodology/approach Following an exploratory research design, a multiple-case study is conducted in the context of industrial AM. It focuses on two key dimensions of SCD, the geographic dispersion and governance structure. Four cohesive AM SCD configurations are characterized and form the basis for exploring the rationales for the SCD decision of manufacturing firms. Findings The findings indicate that manufacturing firms' SCD for industrial AM depends on the trade-off between economies of scale in a centralized setting and the market potential from customer proximity realized by decentral AM. Furthermore, the control of suppliers and the reevaluation of manufacturing firms' core competencies guide the governance choice. Many of the identified rationales currently drive manufacturing firms toward in-house AM at a centralized location or distributed AM in a secure, firm-owned network. Practical implications The arguments for the AM SCD choices are illustrated. They provide guidance for managers of manufacturing firms when implementing industrial AM. Originality/value The study reveals and enhances the understanding of why the extant academic expectation of decentralized and outsourced AM is not sufficiently reflected in current industry practice. Thereby, the study provides a basis for elaborative decision-support research on AM SCDs.

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