The DISRUPT project aims for the following:

  • Provide ICT support in manufacturing execution: offer a multi-sided, cloud-based platform for large corporations and SMEs to optimise business goals
  • Materialise ICT-enabled innovation in manufacturing: unify automation hierarchy of IoT and CPS production systems under a seamless data-intensive modelling approach
  • Implement modular, decentralised production topologies: integrate Smart Objects into analytics, simulation and optimisation tools for efficient decision support in the context of plant's virtual production model
  • Devise novel and coherent business models: sustain individual strategies and visions of manufacturing companies and especially SMEs, while optimising the entire manufacturing chain

To achieve these aims, the DISRUPT project sets the following specific objetives:

  • Design, deploy and validate a responsive architecture that is both service- and event-driven to enhance situational awareness and exploit the capabilities of CPS, IoT and Machine-to-Machine (M2M) communication, coupling them with cloud-based decision support services and tools.
  • Deploy analytics for both lower level detection of complex events on machine operations and factory parameters at higher level monitoring of the behaviour for processes and products.
  • Provide modelling and design services that allow building digitised models for (cloud-based) collaboration of different factory automation components, by combining a bottom-up orchestration of CPSs and production systems with a top-down virtualisation of production processes.
  • Offer co-simulation tools for modelling the behaviour of both the plant floor components and the manufacturing chain.
  • Develop optimisation methods and tools for (near-)optimal solutions to production scheduling, capacity planning and factory problems, throughput the production planning and manufacturing chain optimisation.
  • Implement a reference cloud-based collaboration platform as a self-learning knowledge-based system that facilitates the in-depth monitoring and the efficient operation of the manufacturing unit, as well as the effective experimentation on novice simulated plant floor or manufacturing chain designs during new product or process design phases.
  • Employ a user centric validation of DISRUPT reference implementations through proof-of-concept demonstrations for real industrial cases in the automotive and the consumer durables and electronics industries.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 723541

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