Evaluating the optimal facility location for additive manufacturing technology

Sagar Ghuge; Milind Akarte; Rohit Kumar

doi:10.14488/BJOPM.2567.2025

Authors

Sagar Ghuge A Pai Management Institute, Manipal Academy of Higher Education (MAE Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India. https://orcid.org/0000-0002-3405-9866
Milind Akarte Indian Institute of Management Mumbai (IIM Mumbai), Mumbai, India.
Rohit Kumar Indian Institute of Management Mumbai (IIM Mumbai), Mumbai, India. https://orcid.org/0009-0006-8202-172X

DOI:

https://doi.org/10.14488/BJOPM.2567.2025

Keywords:

Discrete event simulation, Spare Parts, Facility Location, Scenario Analysis, Additive manufacturing

Abstract

Goal: This research identifies the optimal location for additive manufacturing (AM) facilities within the spare parts supply chain, addressing a critical yet underexplored dimension in the literature on strategic facility location for AM technology deployment.
Design / Methodology / Approach: The study integrates agent-based discrete event simulation with scenario analysis to evaluate four facility locations for four distinct spare parts. The model aims to reduce order fulfillment losses and opportunity costs by supporting evidence-based location decisions.
Results: The findings indicate that the Thane location is the most suitable for establishing an AM facility, offering a balanced trade-off between supply reliability and economic efficiency.
Limitations of the investigation: The scope is confined to a specific case involving four locations and four spare parts, which may limit generalizability. The study’s scenario-based approach also relies on assumptions that warrant further validation.
Practical implications: The results offer actionable insights for firms adopting AM in spare parts management. Strategic facility placement enhances service responsiveness, reduces downtime, and supports cost-effective ful-fillment strategies.
Originality / Value: This research provides an incremental empirical contribution by proposing and demonstrat-ing a simulation-based AM facility location selection framework, supported by real-world case data. It addresses a less explored strategic decision of AM facility placement, considering dynamic operational uncertainties, thereby extending the existing literature on AM supply chain design.

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