REPLICA: A Solution for Next Generation IoT and Digital Twin Based Fault Diagnosis and Predictive Maintenance

Nowadays competitiveness goes through several aspects: digitalization, productivity, and environmental impact. Technology is advancing fast and helping industries to obtain more and more detailed data about their processes and equipment. In fact, the possibility to monitor and control each part of the process is a strong base on which a more intelligent and focused control can be built. Technology advance brings innovation and the possibility to manage the production in terms of ”near future” through AI prediction and decision-making support. Forecasting demands and planning production, optimizing processes by reducing costs, and improving efficiency without corrupting the quality of the product is a big challenge at the plant level. In this paper, flexible, scalable architecture for intelligent digital twin realization called REPLICA has been proposed to cope with such problems and help industries advance and discover possible optimizations. This architecture sits on top of two European projects, namely CPSwarm and RECLAIM, where their contribution focuses on distributed simulation and optimization, and Adaptive Sensorial Networks, correspondingly. As a validation process, a hypothetical use case is presented, detailing the key differentiating points and benefits of the proposed architecture.