RP1.4 Dynamic manufacturing execution environments for smarter integration – Legacy manufacturing execution systems have non-modular architecture and will not cope with the dynamic nature of future manufacturing processes. Next-generation MES would require constant optimisation of quality and resource use. Furthermore, the amount of knowledge extracted from the level of automation should be fully exploited by MES. MES would need address the dynamism of environments and facilitate sustainable manufacturing through optimisation of knowledge-based systems and integration with supply-chain processes. These should furthermore be condition based, exploit experience on the shopfloor and facilitate self organisation of production systems. RP1.4 would implement the key ICT recommendations CL3 Collaborative service management to tackle complexity and optimise operations, CL4 Collaborative design and manufacturing for better products, IN9 Big data analysis and real-time decision making and IN11 High-performance simulation and analysis in the cloud. Industrial challenges Potential outcomes Reduction of lead towards just-in-time deliveries; Integration with automation level to provide flexible High process transparency through appropriate and dynamic MES to evolve with highly agile and human-machine interfaces; reconfigurable future manufacturing systems; Reliable and friendly-to-use modelling systems for the Full integration of MES with enterprise information process and production system; systems to use of internal and supply network Real-time monitoring and diagnosis at different levels resources better to demand changes; of the plant; Full integration of MES and automation systems for Reduction of energy consumption through more visualising the engineering value chain and intelligent production planning; and traceability of manufactured products; and Improved and efficient use of complex manufacturing What-if scenario analysis of future outcomes enabling environments which include fixed and mobile efficient use of resources. robotised systems. ICT research requirements New MES-based on software architectures which are modular in nature, state-of-the-art-based and High-performance computing leveraging the to leverage the best practices of cloud deployment. deal with the large amount of data coming from the level of automation and real-time reactivity to perform optimisation and what-if scenario analysis; Complex event processing (CEP) and data-stream Ambition Radar TRL analysis for generating real-time production performance indicators; optimisation of production schedules Impact Factor in real time based on implementation and 2.2 adaptation of self-learning approaches to MES; Horizon 2020 Next-generation software architectures which By 2016 By 2018 By 2020 aggregate conventional production metrics with sustainability metrics; and
RP1.4 – Dynamic manufacturing execution environments for smarter integration Legacy manufacturing execution systems have non-modular architecture and will not cope with the dynamic nature of future manufacturing processes. Next-generation MES would require constant optimisation of quality and resource use. Furthermore, the amount of knowledge extracted from the level of automation should be fully exploited by MES. MES would need address the dynamism of environments and facilitate sustainable manufacturing through optimisation of knowledge-based systems and integration with supply-chain processes. These should furthermore be condition based, exploit experience on the shopfloor and facilitate self organisation of production systems. RP1.4 would implement the key ICT recommendations CL3 Collaborative service management to tackle complexity and optimise operations, CL4 Collaborative design and manufacturing for better products, IN9 Big data analysis and real-time decision making and IN11 High-performance simulation and analysis in the cloud. Industrial challenges Reduction of lead towards just-in-time deliveries; High process transparency through appropriate human-machine interfaces; Reliable and friendly-to-use modelling systems for the process and production system; Real-time monitoring and diagnosis at different levels of the plant; Reduction of energy consumption through more intelligent production planning; and Improved and efficient use of complex manufacturing environments which include fixed and mobile robotised systems. Potential outcomes Integration with automation level to provide flexible and dynamic MES to evolve with highly agile and reconfigurable future manufacturing systems; Full integration of MES with enterprise information systems to use of internal and supply network resources better to demand changes; Full integration of MES and automation systems for visualising the engineering value chain and traceability of manufactured products; and What-if scenario analysis of future outcomes enabling efficient use of resources. ICT research requirements High-performance computing leveraging the to deal with the large amount of data coming from the level of automation and real-time reactivity to perform optimisation and what-if scenario analysis; Complex event processing (CEP) and data-stream analysis for generating real-time production performance indicators; optimisation of production schedules in real time based on implementation and adaptation of self-learning approaches to MES; Next-generation software architectures which aggregate conventional production metrics with sustainability metrics; and New MES-based on software architectures which are modular in nature, state-of-the-art-based and leverage the best practices of cloud deployment. Ambition Radar TRL Impact Factor 2.2 Horizon 2020 By 2016 By 2018 By 2020
001-ActionPlanTD33FinalRoadmap.docx