Cloud-Based CAD/CAM Collaboration Platforms for Distributed Manufacturing: A Systematic Review
Department of Industrial and Manufacturing Engineering, Faculty of Engineering, National University of Science and Technology (NUST), P.O. Box AC 939, Ascot, Bulawayo, Zimbabwe.
* Corresponding Author
Review
Open Access Research Journal of Science and Technology, 2026, 18(01), 111–125.
Article DOI: 10.53022/oarjst.2026.18.1.0094
Publication history:
Received on 26 August 2026; revised on 01 October 2026; accepted on 03 October 2026
Abstract:
Engineering practices are changing from file-centric desktop models to multi-user, real-time, cloud-based computer-aided design and manufacturing (CAD/CAM) platforms like Onshape, Autodesk Fusion, 3DEXPERIENCE and Siemens NX X that serve as a complement to cloud manufacturing (CMfg) and Industry 4.0. This paper summarizes the capabilities and limitations of distributed manufacturing and cloud-based CAD/CAM, the drivers for the adoption of cloud-based CAD/CAM, and the integration architectures. In line with the PRISMA 2020 guidelines, 312 records were identified from IEEE Xplore, Scopus, Web of Science and ScienceDirect databases and were then synthesized thematically to a total of 87 (87%) primary studies published between January 2016 and 06/26/2026. The review suggests a four-dimensional taxonomy of platforms based on: architectural model, granularity of collaboration, depth of manufacturing integration and adherence to a standard for interoperability. In looking at the taxonomy, there is a constant riddle of how platforms with a fine-grained real-time co-editing feature deliver shallow manufacturing integration, while the PLM-based platforms offering deep MES/ERP and digital-twin integration maintain coarse check-out-based co-editing. Empirical studies demonstrate the benefits of simultaneous access in the form of new modes of teamwork, but that benefits in terms of quality and productivity rely on design of work processes and team dynamics and permissioning. The major challenges to adoption are not platform maturity, but the absence of standards for exchanging parametric models and integrating CAD with MES, inadequate evidence of IP-protection and a lack of evidence from the developing world where connectivity, power reliability and skills are very different. The paper identifies eight priority research directions based on the process-optimisation, condition monitoring and Industry 4.0 adoption studies conducted in Zimbabwe and discusses implications for practitioners and for engineering education using learning factories.
Keywords:
cloud-based CAD; Cloud Manufacturing; Collaborative Design; Distributed Manufacturing; Digital Twin; Interoperability; Industry 4.0; PLM; Developing Economies; Systematic Review
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