Developing methods and tools for deployment of highly optimised and reactive planning systems is our vision. This can be done using factory modelling and simulation based on empirical data. The data is captured using smart sensors as well as pro-active human-machine interfaces.

Energy is the future

The impact of energy management on factory planning and optimisation is specifically assessed in the project. Reducing energy waste on one side, while understanding how energy is used in detail on the other side, allows future factories to reschedule production according to desired energy consumption. This is especially beneficial to energy providers, who seek to balance energy demand.

A digital simulation modelling toolbox

This tool box will contain:

  • semantically enriched process modelling
  • big-data generation
  • decision making support throughout the system’s lifecycle

These next generation manufacturing systems will be supported by data rich manufacturing execution systems. This is destined to lead to a dramatic improvement in:

  • system performance
  • operational efficiency and equipment utilisation
  • real-time equipment and station performance monitoring
  • adaptation and resource optimisation

The OPTIMISED toolbox will allow:

  • Monitoring system performance through an integrated sensor network, automatically detecting bottlenecks, faults and performance drop-off
  • Better understanding and monitoring of energy demand curve and energy usage per industrial process and within a whole factory context
  • Higher efficiency of production line through reduced energy waste
  • Quick response to disruptive events, including supply chain and non-quality issues
  • To understand potential benefits, added value and impacts of participating in Demand Side Response processes. 
  • Informed decision-making process when choosing energy providers

One holistic planning tool

All functionalities of the tool box will be accessible within one system. The novel and holistic information management approach will lead to:

  • accelerated ramp-up, reconfiguration and adaptation
  • drastically decreased down-times
  • increased operational performance and productivity
  • higher reliability and maintainability

In summary OPTIMISED will deliver:

  • Real-time monitoring, comparative analysis vs simulation, pinch point identification
  • Integration of external data monitoring, supporting forecasting of disruptive events
  • Condition monitoring of key process equipment: failure prediction and maintenance schedule optimisation
  • Distributed big-data processing framework enabling advanced in-network evaluation
  • Updating of interfaces for real-time usage of data to inform simulation models
  • Digital simulation modelling toolbox
  • Shared semantic modelling to highlight factory capabilities
  • Data analysis enabling system performance assessment against production objectives
  • Hybrid human-machine decision support systems