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Title: | A STUDY ON ENABLERS AND BARRIERS OF ADDITIVE MANUFACTURING ADOPTION IN INDUSTRY 4.0: AN AHP APPROACH |
Authors: | BAVORIA, REHAN KUMAR |
Keywords: | ENABLER BARRIER ADDITIVE MANUFACTURING ANALYTIC HIERARCHY PROCESS |
Issue Date: | May-2023 |
Series/Report no.: | TD-6418; |
Abstract: | Industry 4.0 is the next generation of manufacturing that utilizes technologies like the artificial intelligence (AI), Internet of Things (IoT), and Additive Manufacturing (AM). Additive manufacturing has the potential that can revolutionize the manufacturing industry by enabling mass customization, reducing waste, and increasing design freedom. However, there are several barriers that hinder the widespread adoption of AM in Industry 4.0, including the lack of standardization, high costs, limited material selection, intellectual property and legal issues, quality and safety concerns, lack of skilled labor, and environmental concerns. On the other hand, there are several enablers that could facilitate the adoption of AM in Industry 4.0, including the Triple Helix, accessibility, capitalization, resource material, suffusing labor, interoperability & compatibility, optimization, AI, entrepreneurship, and personalization. This study aims at exploring the impact of additive manufacturing on Industry 4.0 by analyzing the barriers and enablers and determining their relative importance using the Analytic Hierarchy Process (AHP) technique. The results show that intellectual property and legal issues are the most significant barrier, followed by limited material selection. Among the enablers, suffusing labor and accessibility are the most important factors. The results of this study may offer insightful information about the possibilities of additive manufacturing in Industry 4.0 and may serve as a roadmap for further research and development in this area. |
URI: | http://dspace.dtu.ac.in:8080/jspui/handle/repository/19859 |
Appears in Collections: | M.E./M.Tech. Mechanical Engineering |
Files in This Item:
File | Description | Size | Format | |
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REHAN KUMAR BAVORIA M.Tech.pdf | 1.46 MB | Adobe PDF | View/Open |
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