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New Progresses and Main Implications in Additive Manufacturing for Operations...
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New Progresses and Main Implications in Additive Manufacturing for Operations and Supply Chain Management

A special issue of Logistics (ISSN 2305-6290).

Deadline for manuscript submissions: 31 July 2026 | Viewed by 3341

Special Issue Editors

Dr. Antonio Maria Coruzzolo

E-Mail Website
Guest Editor
Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy
Interests: inventory management; spare parts; supply chain; additive manufacturing; risk assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Alessandra Cantini

E-Mail Website
Guest Editor
Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4B, 20156 Milan, Italy
Interests: supply chain management; spare parts; inventory management; explainable artificial intelligence; additive manufacturing
Special Issues, Collections and Topics in MDPI journals
Dr. Francesco Lolli

E-Mail Website
Guest Editor
Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia, 41121 Modena, Italy
Interests: multi criteria decision making; inventory management; spare parts; additive manufacturing
Special Issues, Collections and Topics in MDPI journals
Dr. Filippo De Carlo

E-Mail Website
Guest Editor
Department of Industrial Engineering (DIEF), University of Florence, 50134 Florence, Italy
Interests: industrial plant engineering; maintenance; industrial safety and risk; reliability; manufacturing systems; additive manufacturing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Additive manufacturing is an emerging production technology which has the potential to disrupt the characteristics and performance of operations and supply chains. Unlike conventional manufacturing, it offers the possibility to produce items close to the point of use by adding layers of material, thus, allowing complex shapes to be produced with little material waste. Positive impacts of additive on operations and supply chains include (but are not limited to) reducing the dependency on suppliers, minimizing procurement lead times and inventory levels, and enabling remanufacturing, circular economy, and sustainable development. However, implementing additive manufacturing in organizations does not come without challenges due to the continuous advancements of this manufacturing technology. This poses the need to investigate new progresses, trends, and main implications in this field. The current literature has overlooked this research domain. Therefore, this Special Issue is intended for the presentation of new ideas and experimental results in the domain of additive manufacturing for operations and supply chain management, including both theoretical and practical investigations. As an example, we encourage papers addressing the following research questions:

  • How does the adoption of additive manufacturing impact the structure, performance, and resilience of operations and supply chains?
  • How can additive manufacturing support circular economy and sustainable development within operations and supply chains?
  • What barriers and enablers are encountered in industrial applications of additive manufacturing?
  • What guidelines can be developed to facilitate the broader adoption of additive manufacturing?

Related papers:

  • Woldesilassiea, T.L., Lemu, H.G., Gutema, E.M., 2024. Impacts of Adopting Additive Manufacturing Process on Supply Chain: Systematic Literature Review. Logistics 8, 3. https://doi.org/10.3390/logistics8010003
  • Verboeket, V., Krikke, H., Salmi, M., 2024. Implementing Additive Manufacturing in Orthopedic Shoe Supply Chains—Cost and Lead Time Comparison. Logistics 8, 49. https://doi.org/10.3390/logistics8020049
  • Ferraro, S., Baffa, F., Cantini, A., Leoni, L., De Carlo, F., Campatelli, G., 2024. Exploring remanufacturing conveniency: An economic and energetic assessment for a closed-loop supply chain of a mechanical component. Journal of Cleaner Production 458, 142504. https://doi.org/10.1016/j.jclepro.2024.142504
  • Sæterbø, M., Arnarson, H., Yu, H., Solvang, W.D., 2024. Expanding the horizons of metal additive manufacturing: A comprehensive multi-objective optimization model incorporating sustainability for SMEs. Journal of Manufacturing Systems 77, 62–77. https://doi.org/10.1016/j.jmsy.2024.08.026
  • Cardeal, G., Leite, M., Ribeiro, I., 2023. Decision-support model to select spare parts suitable for additive manufacturing, Computers in Industry, Volume 144, 103798, ISSN 0166-3615, https://doi.org/10.1016/j.compind.2022.103798.
  • Debnath, B., Shakur, M.S., Tanjum, F., Rahman, M.A., Adnan, Z.H., 2022. Impact of Additive Manufacturing on the Supply Chain of Aerospace Spare Parts Industry—A Review. Logistics 6, 28. https://doi.org/10.3390/logistics6020028
  • Lolli, F., Coruzzolo, A. M., Peron, M., Sgarbossa, F., 2022. Age-based preventive maintenance with multiple printing options, International Journal of Production Economics, Volume 243, 108339, ISSN 0925-5273, https://doi.org/10.1016/j.ijpe.2021.108339.

Dr. Antonio Maria Coruzzolo
Dr. Alessandra Cantini
Dr. Francesco Lolli
Dr. Filippo De Carlo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Logistics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • additive manufacturing
  • 3D Printing
  • rapid manufacturing
  • remanufacturing
  • operations management, supply chain design
  • supply chain management
  • operations and supply chain resilience

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Published Papers (3 papers)

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30 pages, 2004 KB  
Article
Bridging Accuracy and Interpretability: A Decision Support System for Stock Deployment and Additive Manufacturing Decisions in Spare Parts Distribution Networks
by Alessandra Cantini, Antonio Maria Coruzzolo, Francesco Lolli, Filippo De Carlo and Alberto Portioli-Staudacher
Logistics 2026, 10(4), 77; https://doi.org/10.3390/logistics10040077 - 2 Apr 2026
Viewed by 393
Abstract
Background: Spare parts distribution networks (DNs) play a strategic role in retailers’ profitability. Among DN configuration decisions, selecting the optimal stock deployment policy—centralised, decentralised, or hybrid inventory allocation across distribution centres (DCs)—critically affects service levels and logistics costs. This decision becomes more complex [...] Read more.
Background: Spare parts distribution networks (DNs) play a strategic role in retailers’ profitability. Among DN configuration decisions, selecting the optimal stock deployment policy—centralised, decentralised, or hybrid inventory allocation across distribution centres (DCs)—critically affects service levels and logistics costs. This decision becomes more complex with additive manufacturing (AM) as an alternative to conventional manufacturing (CM). While AM enables production with shorter lead times, its higher costs alter stock deployment cost-effectiveness. Given the complexity of joint stock deployment and manufacturing decisions, retailers require decision support systems (DSSs). Methods: To address this need, we develop a DSS through a three-step methodology: (i) a mathematical model evaluates logistics costs across different stock deployment policies and manufacturing technologies; (ii) parametric analysis tests the model across 2000 realistic scenarios; (iii) Random Forest trained on this dataset predicts optimal solutions, with SHapley Additive exPlanations (SHAP) interpreting post hoc recommendations. Results: The DSS achieves 93.4% prediction accuracy—outperforming (+16.4%) the only comparable literature DSS (77%)—while explaining recommendations. SHAP reveals that AM and CM unit costs dominate decision-making, followed by backorder costs. Conclusions: Beyond individual spare parts recommendations, the DSS provides guidelines enabling retailers to maintain cost-effective DNs aligned with evolving customer needs and to plan valuable investments in AM. Full article
(This article belongs to the Special Issue New Progresses and Main Implications in Additive Manufacturing for Operations and Supply Chain Management)
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26 pages, 5240 KB  
Article
Designing Sustainable Healthcare Additive Manufacturing Networks Using a Multi-Objective Spatial Routing Framework
by Kasin Ransikarbum, Chanipa Nivasanon and Pornthep Anussornnitisarn
Logistics 2026, 10(2), 35; https://doi.org/10.3390/logistics10020035 - 2 Feb 2026
Viewed by 619
Abstract
Background: This study evaluates an additive manufacturing (AM) network designed to balance economic performance, lead time, and environmental impact within the healthcare logistics and supply chain. Methods: An integrated framework is proposed that identifies optimal AM facility locations using spatial K-means [...] Read more.
Background: This study evaluates an additive manufacturing (AM) network designed to balance economic performance, lead time, and environmental impact within the healthcare logistics and supply chain. Methods: An integrated framework is proposed that identifies optimal AM facility locations using spatial K-means clustering and optimizes delivery routes through a multi-objective vehicle routing problem with time windows (MOVRPTW). This framework was applied to a case study in Phra Nakhon Si Ayutthaya, Thailand, utilizing hospital geocoordinates, demand profiles, and CO2 emission factors to evaluate centralized versus decentralized network configurations. Results: Findings demonstrate that hub structures derived from K-means clustering achieve the highest economic efficiency, reducing the AM part cost per unit to 698.51 Baht. In contrast, a fully centralized network resulted in a significantly higher unit cost of 4759.79 Baht, while clustering based on hospital types yielded a unit cost of 959.34 Baht. Quantitative results indicate that the multi-objective approach provides a superior trade-off, achieving lead time requirements while maintaining operational costs and emissions. Conclusions: The results indicate that the proposed framework, particularly through spatial clustering, offers a practical decision-support tool for designing AM networks that achieve a balance between operational efficiency and sustainability objectives in healthcare logistics. Full article
(This article belongs to the Special Issue New Progresses and Main Implications in Additive Manufacturing for Operations and Supply Chain Management)
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21 pages, 514 KB  
Article
Sustainability Through Additive Manufacturing Operations: A Comparative Industrial Analysis with a Life Cycle Assessment Case Study of Türkiye
by Saliha Karadayi-Usta
Logistics 2026, 10(1), 7; https://doi.org/10.3390/logistics10010007 - 26 Dec 2025
Viewed by 791
Abstract
Background: Additive manufacturing (AM), commonly known as 3D printing, is transforming global production systems with sustainability at its core. The global AM market growth underscores the urgency of evaluating its environmental implications. Methods: This study aims to (1) identify Life Cycle [...] Read more.
Background: Additive manufacturing (AM), commonly known as 3D printing, is transforming global production systems with sustainability at its core. The global AM market growth underscores the urgency of evaluating its environmental implications. Methods: This study aims to (1) identify Life Cycle Assessment (LCA) factors influencing additively manufactured products across aerospace, automotive, medical devices, industrial equipment, energy, construction, and consumer electronics industries; (2) determine the relative importance of these factors using Adaptive Choice-Based Conjoint (ACBC) analysis within a Türkiye case study; and (3) assign sustainability levels for each industry via the PrOPPAGA technique. Since LCA quantifies environmental impacts throughout a product’s life cycle, from raw material extraction to end-of-life, this research assesses the sustainability dimensions of AM operations by examining energy consumption, emissions, and waste generation. Results: The findings provide practical and managerial insights for industry stakeholders seeking to enhance sustainable practices in AM. Conclusions: The study introduces a novel sustainability evaluation framework integrating ACBC and PrOPPAGA methods, offering a significant theoretical contribution to the literature on sustainable manufacturing. Full article
(This article belongs to the Special Issue New Progresses and Main Implications in Additive Manufacturing for Operations and Supply Chain Management)
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