This research studies how to improve efficiency in use of manufacturing resources, in particular energy, in order to achieve the future eco-factories. The objective is to analyse how to minimise demands, optimise production planning and scheduling, manage switch-off modes. Results include methodologies for eco-factory management and energy-aware control of production lines with innovative technologies, e.g. IoT and Digital Twin, in the vision of Industry 4.0 and Cyber-Physical Production Systems.
Energy and Resource Efficient Manufacturing
About the project
KEY RESEARCH QUESTIONS
– Energy and Resource Efficiency (ERE) has become one of the most relevant topics of research in manufacturing, as industry accounts for a major part of the world energy consumption and for the need for sustainable development at planetary level. Furthermore, the availability of innovative technologies, such as Internet of Things (IoT), Data Analytics and Cyber-Physical Production Systems, has led to increasing attention to the vision of Industry 4.0, which includes energy and resource efficiency as one of the key areas, together with management of the increasingly complex manufacturing systems. In this context, manufacturers have to completely change their
management systems. Despite the relevance of the problem, many areas are still unexplored: still modeling and simulation of sustainable manufacturing systems lack depth and software tools to exploit the potential of collaborative approaches for global optimization; furthermore, the complexity of the problems of production planning and control and lack of performance indicators hinder development of practical solutions for Operations optimization; finally, despite existence of many advanced industrial automation standards, still Industry 4.0-ready platforms are not available.
This research project investigates innovative methods to manage, plan and control the future ERE eco-factories, and how to model and integrate from the ICT point of view the novel manufacturing systems in order to tackle the complex and dynamic network of relationships among the different components of the factory at its different levels.
Results of the research so far include:
- holistic model of the future eco-factories;
- ERE KPI framework and KPI development methodology for energy efficiency;
- industrial use case validation of the ERE KPI framework;
- study by simulation of energy-aware autonomous production line control policies;
- laboratory experiment of digital-twin based energy-aware autonomous production line control.
OUTPUTS & IMPACTS
- Palasciano, C., Thiede, B., Taisch, M., & Herrmann, C. (2017, September). Deployment Architecture for Energy and Resource Efficient Cyber Physical Systems. In IFIP International Conference on Advances in Production Management Systems (pp. 159-167). Springer, Cham.
- Palasciano, C., Taisch, M. (2016). Autonomous energy-aware production systems control. In XXI Summer school” Francesco Turco” (pp. 107-112).
- Palasciano, C., Bustillo, A., Fantini, P., & Taisch, M. (2016). A new approach for machine’s management: from machine’s signal acquisition to energy indexes. Journal of Cleaner Production, 137, 1503-1515.
- May, G., Barletta, I., Stahl, B., & Taisch, M. (2015). Energy management in production: A novel method to develop key performance indicators for improving energy efficiency. Applied energy, 149, 46-61.
- Fantini, P., Palasciano, C., & Taisch, M. (2015). Back to intuition: proposal for a performance indicators framework to facilitate eco-factories management and benchmarking. Procedia Cirp, 26, 1-6.
- Fantini, P., Palasciano, C., Taisch, M., Vasyutynskyy, V., Beccaris, M., Cultrona, P., & Rusinà, F. (2014, June). Towards environmental conscious manufacturing. In 2014 International Conference on Engineering, Technology and Innovation (ICE) (pp. 1-7). IEEE.
- Academic: University of Burgos (E), IWF Technical University of Braunschweig (D)
- Corporate: COMAU (I), ENGINEERING Ingegneria Informatica (I); SAP AG(D).