Coordinating Optimisation of Complex Industrial Processes

    Project: Research

    Project Details

    Description

    The vision of COCOP is that complex process-industry plants are optimally run by operators with the guidance of a coordinating, real-time optimisation system. COCOP will strengthen the global position of the European process industry, which represents 20 per cent of the European manufacturing base with around 450,000 companies generating €1.6 billion in turnover and 6.8 million jobs.
    The project’s objective is to enable plant-wide monitoring and control by using the model-based, predictive, coordinating optimisation concept in integration with plant’s automation systems. This ambitious approach will be developed and verified in co-operation of European universities, research institutes and industry. The Consortium comprises two universities, three research organisations, the leading copper-plant technology provider, two large companies from the process industry (steel and special chemicals) and four SMEs providing automation solutions.
    Technical objective is to define, design and implement a concept that integrates existing industrial control systems with efficient data management and optimisation methods and provides means to monitor and control large industrial production processes. The plant-wide monitoring and control comprehend computationally intensive data analysis and large scale optimisation. The social objective is to improve operator plant-wide awareness and reduce mental workload.
    COCOP will liaise with standardisation bodies (automation) to ensure a sustained impact of the project’s results. Commercialisation of the solution by its process-automation industry partners will allow plant operators to approach optimal production and result in reduced energy and resource consumption, and decreased on-site material handling time and greenhouse gas emissions.
    Short titleCOCOP
    AcronymCOCOP
    StatusFinished
    Effective start/end date1/10/1631/03/20

    Keywords

    • H2020-EU.2.1.5.3.

    Research Output

    • 1 Conference article in proceedings

    Human factors in software projects for complex industrial processes

    Liinasuo, M., Lastusilta, T., Savolainen, J. & Kuula, T., Feb 2019, Intelligent Human Systems Integration 2019: IHSI 2019. Karwowski, W. & Ahram, T. (eds.). Cham: Springer, p. 517-523 7 p. (Advances in Intelligent Systems and Computing, Vol. 903).

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Open Access
    File
  • 19 Downloads (Pure)