Article: Healthcare industry input parameters for a deterministic model that optimally locates additive manufacturing hubs Journal: International Journal of Healthcare Technology and Management (IJHTM) 2024 Vol.21 No.2 pp.111 - 128 Abstract: Recent innovations in additive manufacturing (AM) have proven its efficacy for not only the manufacturing industry but also the healthcare industry. Researchers from Cal Poly, San Luis Obispo, and California State University Long Beach are developing a model that will determine the optimal locations for additive manufacturing hubs that can effectively serve both the manufacturing and healthcare industries. This paper will focus on providing an overview of the healthcare industry's unique needs for an AM hub and summarise the specific inputs for the model. The methods used to gather information include extensive literature research on current practices of AM models in healthcare and an inclusive survey of healthcare practitioners. This includes findings on AM's use for surgical planning and training models, the workflow to generate them, sourcing methods, and the AM techniques and materials used. This paper seeks to utilise the information gathered through literature research and surveys to provide guidance for the initial development of an AM hub location model that locates optimal service locations. Inderscience Publishers - linking academia, business and industry through research

Title: Healthcare industry input parameters for a deterministic model that optimally locates additive manufacturing hubs

Authors: Ethan Sanekane; Jill Speece; Mohamed Awwad; Xuan Wang; Sara Moghtadernejad

Addresses: Industrial and Manufacturing Engineering, California Polytechnic State University, 1 Grand Ave, Bldg. 192, San Luis, Obispo, CA, 93407, USA ' Industrial and Manufacturing Engineering, California Polytechnic State University, 1 Grand Ave, Bldg. 192, San Luis, Obispo, CA, 93407, USA ' Industrial and Manufacturing Engineering, California Polytechnic State University, 1 Grand Ave, Bldg. 192, San Luis, Obispo, CA, 93407, USA ' Industrial and Manufacturing Engineering, California Polytechnic State University, 1 Grand Ave, Bldg. 192, San Luis, Obispo, CA, 93407, USA ' Department of Chemical Engineering, California State University Long Beach, 1250 Bellflower Blvd, EN2-104A, Long Beach, CA, 90840-5103, USA

Abstract: Recent innovations in additive manufacturing (AM) have proven its efficacy for not only the manufacturing industry but also the healthcare industry. Researchers from Cal Poly, San Luis Obispo, and California State University Long Beach are developing a model that will determine the optimal locations for additive manufacturing hubs that can effectively serve both the manufacturing and healthcare industries. This paper will focus on providing an overview of the healthcare industry's unique needs for an AM hub and summarise the specific inputs for the model. The methods used to gather information include extensive literature research on current practices of AM models in healthcare and an inclusive survey of healthcare practitioners. This includes findings on AM's use for surgical planning and training models, the workflow to generate them, sourcing methods, and the AM techniques and materials used. This paper seeks to utilise the information gathered through literature research and surveys to provide guidance for the initial development of an AM hub location model that locates optimal service locations.

Keywords: 3D printing; additive manufacturing; healthcare; hub; location model; medical models; orthotic insoles; preoperative planning; surgical planning; training.

DOI: 10.1504/IJHTM.2024.140392

International Journal of Healthcare Technology and Management, 2024 Vol.21 No.2, pp.111 - 128

Received: 30 Jun 2023
Accepted: 05 Jun 2024
Published online: 06 Aug 2024 *

Title: Healthcare industry input parameters for a deterministic model that optimally locates additive manufacturing hubs

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