- Project Dates: From 1st Feb 2013 to 31st July 2018
- Project Leader: Prof. Svetan Ratchev (PI, University of Nottingham, Faculty of Engineering)
- Staff: Prof. Natalio Krasnogor, Prof. Sarah Sharples (University of Nottingham, Faculty of Engineering), Prof. Dragos Axinte (University of Nottingham, Faculty of Engineering), Prof. Atanas Popov (University of Nottingham, Faculty of Engineering), Dr. Peter Kinnell (Loughborough University, School of Mechanical and Manufacturing Engineering), Dr. Panorios Benardos (University of Nottingham, Faculty of Engineering), Dr. Brian Logan (University of Nottingham, School of Computer Science), Dr. E. M. Kelly (CI, University of Nottingham, Faculty of Engineering), Dr. R. F. Oates (CI, University of Nottingham, School of Computer Science)
- Sponsors: EPSRC
- Partners: ABB, Airbus Group Limited, AstraZeneca, BAE Systems, Destaco, GE (General Electric Company), Hyde Group Ltd, Manufacturing Technology Centre, Midlands Aerospace Alliance, Siemens, TQC Ltd
Assembly of final products in sectors such as automotive, aerospace, pharmaceutical and medical industries is a key production process in high labour cost areas such as the UK. To respond to the current challenges manufacturers need to transform current capital-intensive assembly lines into smart systems that can react to external and internal changes and can self-heal, self-adapt and reconfigure. This need is dictated by: (1) demand for rapid ramp-up and downscale of production systems; (2) the fact that current assembly systems lack autonomous responsiveness to disruptive events and demand fluctuations; (3) an economics and societal drive towards 'manufacturing as a service'. Consequently, there is a need for a radically new approach towards development of future assembly systems able to continuously evolve to respond to changes in product requirements and demand with extremely short set-up times combined with low cost of maintenance, system reconfiguration and capability upgrade with emerging new technologies. As the level and type of automation changes, future assembly systems will also require a different type of engagement of human operators in hybrid decision-making, monitoring and system adaptation.
The proposed research brings together a multidisciplinary and multi-sector partnership drawing upon skills from across the University of Nottingham with an established track record in multi-disciplinary transformative research, and industries representing key high value manufacturing companies together with their representative bodies. The goal of the research programme is to define and validate the vision and support architecture, theoretical models, methods and algorithms for Evolvable Assembly Systems as a new platform for open, adaptable, context-aware and cost effective production.
The research programme will deliver a new paradigm shift in adaptable and cost effective manufacture that breaks with traditional approaches and is predicated on an innovative intertwining of the following foundational research challenges in complex collective adaptive manufacturing systems: Product-Process-System Evolution; Data Analytics; Knowledge Modelling; Emergence Engineering; and Open Manufacturing. These fundamentally 'collective', pillars for a new extremely flexible and evolvable manufacturing infrastructure are expected to shed new insights on the self-configuration, self-organisation, self-adaptation and evolution of future production platforms. Together the pillars will presage a game-changing strategy for industry's ability to respond and solve current and future societal grand challenges linked to retaining and expanding manufacturing operations in the UK.
The research will ultimately enable a compressed product life cycle through the delivery of robust and compliant manufacturing systems that can be rapidly configured and optimised, thus reducing production ramp-up times and programme switchovers. This will lead to increased opportunities for new, small and independent production stakeholders, particularly those involved in the realisation of product, process and assembly system co-evolution. Our approach of building an underlying architecture, using simulated and real-world data to test and populate models, and working closely with industry stakeholders, will ensure scalable and adaptable approaches that will be transferable between different manufacturing sectors.