Abstract
The global COVID-19 pandemic has brought attention to the vulnerability of the modern supply chain (SC), particularly in the manufacturing sector, emphasizing the necessity of reassessing conventional SC models and exploring innovative technologies that can fortify SC against disruptions while maintaining flexibility and responsiveness. In this context, additive manufacturing technology (AMT) has emerged as a transformative technology capable of automating and digitalizing traditional manufacturing SC. With an increasing understanding of the potential benefits of AMT, there is a demand for a comprehensive decision support framework (DSF) that enables the seamless integration of AMT into existing manufacturing systems while fostering flexibility in operations against disruptions. Despite various studies assessing the technological maturity of AMT, there remains a gap in presenting specific models or techniques to evaluate and enhance the relative performance of AMT in bolstering SC flexibility, resilience, and sustainability. This study aims to bridge this gap through the formulation of a DSF based on an empirical model that encompasses seven latent variables and sixty-seven indicators. This framework addresses key research questions influencing the strategic decision-making process for the integration of AMT into manufacturing systems. The analysis of the models has been conducted utilizing the partial least squares structural equation modeling (PLS-SEM) algorithm using the data from the nationwide survey of industry experts and researchers in AMT. The findings underscore that the AMT SC risk mitigation capabilities, success determinants to AMT incorporation, and supplier selection framework facilitated by AMT capabilities in the SC positively impact various considered SC parameters, while impediments to AMT incorporation negatively impact them. This study contributes comprehensive frameworks and DSF consisting of diverse incorporation factors influencing the decision to adopt AMT, aiming to empower industry practitioners with the tools to enhance SC flexibility and resilience.
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References
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Singh, S., Misra, S.C. & Singh, G. Leveraging Additive Manufacturing for Enhanced Supply Chain Resilience and Sustainability: A Strategic Integration Framework. Glob J Flex Syst Manag 25, 343–368 (2024). https://doi.org/10.1007/s40171-024-00389-w
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DOI: https://doi.org/10.1007/s40171-024-00389-w