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Details of Grant 

EPSRC Reference: EP/K019368/1
Title: Self-Resilient Reconfigurable Assembly Systems with In-process Quality Improvement
Principal Investigator: Ceglarek, Professor D
Other Investigators:
Matuszewski, Professor BJ Shark, Professor LK
Researcher Co-Investigators:
Project Partners:
BAE Systems EnginSoft UK Ltd Georgia College of Engineering
Georgia Institute of Technology Hexagon Metrology Ltd Jaguar Land Rover Limited
Stadco Ltd University of Huddersfield University of Michigan
Department: WMG
Organisation: University of Warwick
Scheme: Standard Research
Starts: 11 November 2013 Ends: 17 May 2019 Value (£): 2,002,994
EPSRC Research Topic Classifications:
Design Engineering Manufacturing Machine & Plant
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Manufacturing
Related Grants:
Panel History:
Panel DatePanel NameOutcome
26 Nov 2012 Flexible & Reconfigurable Manufacturing Systems Panel Announced
Summary on Grant Application Form
Globalization and ever-changing customer demands resulting in product customization, variety and time to market have intensified enormous competition in automotive and aerospace, manufacturing worldwide. Manufacturers are under tremendous pressures to meet changing customer needs quickly and cost effectively without sacrificing quality. Responding to these challenges manufacturers have offered flexible and reconfigurable assembly systems. However, a major challenge is how to obtain production volume flexibility for a product family with low investment and capability to yield high product quality and throughput while allowing quick production ramp-up.

Overcoming these challenges involves three requirements which are the focus of this proposal: (1) Model reconfigurable assembly system architecture. The system architecture should purposefully take into account future uncertainties triggered by product family mix and product demands. This will require minimizing system changeability while maximizing system reusability to keep cost down; (2) Develop novel methodologies that can predict process capability and manage product quality for given system changeability requirements; and (3) Take advantage of emerging technologies & rapidly integrate them into existing production system, for e.g., new joining processes (Remote Laser Welding) and new materials.

This project will address these factors by developing a self-resilient reconfigurable assembly system with in-process quality improvement that is able to self-recover from (i) 6-sigma quality faults; and (ii) changes in design and manufacturing. In doing so, it will go beyond state-of-the-art and practice in following ways: (1) Since current system architectures face significant challenges in responding to changing requirements, this initiative will incorporate cost, time and risks involving necessary changes by integrating uncertainty models; decision models for needed changes; and system change modelling; and (2) Current in-process quality monitoring systems use point-based measurements with limited 6-sigma failure root cause identification. They seldom correct operational defects quickly and do not provide in-depth information to understand and model manufacturing defects related to part and subassembly deformation. Usually, existing surface-based scanners are used for parts inspection not in-process quality control. This project will integrate in-line surface-based measurement with automatic Root Cause Analysis, feedforward/feedback process adjustment and control to enhance system response to fault or quality/productivity degradation. The research will be conducted for reconfigurable assembly system with multi-sector applications. It will involve system changeability/adaptation and in-process quality improvement for: (i) Automotive door assembly for implementing an emerging joining technology, e.g. Remote Laser Welding (RLW), for precise closed-loop surface quality control; and (ii) Airframe assembly for predicting process capability also for precise closed-loop surface quality control.

Results will yield significant benefits to the UK's high value manufacturing sector. It will further enhance the sector by accelerating introduction of new emerging eco-friendly processes, e.g., RLW. It will foster interdisciplinary collaboration across a range of disciplines such as data mining and process mining, advanced metrology, manufacturing, and complexity sciences, etc. The integration of reconfigurable assembly systems (RAS) with in-process quality improvement (IPQI) is an emerging field and this initiative will help to engender the development into an internationally important area of research. The results of the research will inform engineering curriculum components especially as these relate to training future engineers to lead the high value manufacturing sector and digital economy.

Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.warwick.ac.uk