THE TRANSFORMATION OF RAPID PROTOTYPING IN INDUSTRY 4.0: A SYSTEMATIC REVIEW OF CLOUD-BASED ADDITIVE MANUFACTURING

Abstract

Industry 4.0 changes the dynamics of how additive manufacturing (AM) is used for product development and rapid prototyping. Cloud computing, Internet of Things (IoT), cyber physical systems (CPS), artificial intelligence (AI) and machine learning (ML) and digital twins are increasingly becoming part of AM, providing enhanced connectivity, flexibility and access to manufacturing resources. However, the more technologies emerge and the greater the number of benefits that are touted, the more difficult it is to assess the extent to which cloud-based additive manufacturing (CBAM) has transformed rapid prototyping—let alone why its popularization remains stymied. This systematic review outlines the changes to rapid prototyping in the context of Industry 4.0 using CBAM. The literature published from 2016 to 2026 was retrieved from Google Scholar, Web of Science, IEEE Xplore and Emerald and screened according to the included and excluded criteria pre-designed, and reported using PRISMA 2020. The review categorises the enabling technologies based on function, data flow, consolidates the reported applications and benefits of the technologies, and identifies technical, operational, economic and organisational barriers to their adoption, specifically considering the needs of small and medium-sized enterprises (SMEs) and developing economies including Zimbabwe. The results demonstrate the potential of CBAM to provide access to manufacturing resources at distance, collaborative and iterative design, distributed manufacturing and stronger integration of digital and physical manufacturing systems. There are still major shortcomings, however, in cybersecurity, interoperability, data handling, network reliability, quality consistency and interoperability with heterogeneous systems. The evidence of technical feasibility is much greater than the evidence of long-term economic gains, industrial scalability and implementation in reality. The review thus suggests more rigorous industrial validation, shared interoperability and security rules, process-parameter knowledge-bases that can be reused and paths towards implementation that are low-cost and incremental for resource-poor manufacturers.