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Digital Twins (DT) are a core Smart Manufacturing technology that is applicable across industries and use cases. However, manufacturers face numerous challenges when it comes to identifying appropriate tools to build custom applications, considering systems’ complexity, cost, compatibility, interoperability, and other factors. This study presents a systematic framework for selecting suitable Development Environment (DE) for DT applications in manufacturing. By analysing different DEs categorised into three groups (Simulation Engines, Game Engines, and Robotics Engines) before evaluating them based on curated, predefined criteria, the framework assists stakeholders in making informed decisions tailored to their specific project’s requirements. The framework considers factors such as cost, compatibility, scalability, ease of use, and technical capabilities, ensuring accessibility for expert users and practitioners with limited experience. It was evaluated in a real use case for its robustness and practicality. The results demonstrated the framework’s utility in identifying fit-for-purpose DE, highlighting the strengths and limitations of different environments. Challenges include balancing visualisation capabilities with industrial functionality and managing the steep learning curves of complex environments. The framework aims to support manufacturers, researchers, and technology enthusiasts in selecting suitable DE that meet technical requirements and align with strategic goals, ultimately driving innovation and efficiency in manufacturing.
Dodero et al. (Thu,) studied this question.