Research Perspectives - Tools for Visualisation of Portfolios
EPSRC logo

EPSRC Database


Source RCUK EPSRC Data

EP/K018191/1 - Knowledge Driven Configurable Manufacturing (KDCM)

Research Perspectives grant details from EPSRC portfolio

http://www.researchperspectives.org/gow.grants/grant_EPK0181911.png

Professor R Harrison EP/K018191/1 - Knowledge Driven Configurable Manufacturing (KDCM)

Principal Investigator - WMG, University of Warwick

Other Investigators

Professor P Conway, Co InvestigatorProfessor P Conway

Professor AA West, Co InvestigatorProfessor AA West

Dr R Young, Co InvestigatorDr R Young

Scheme

Standard Research

Research Areas

Engineering Approaches to Manufacturing Operations Engineering Approaches to Manufacturing Operations

Engineering Design Engineering Design

Manufacturing Technologies Manufacturing Technologies

Start Date

04/2013

End Date

03/2018

Value

£1,928,198

Similar Grants

Automatic generation of similar EPSRC grants

Similar Topics

Topic similar to the description of this grant

Grant Description

Summary and Description of the grant

The proposed research programme will attempt to create self-reconfiguring manufacturing systems that are based on intelligent and highly accurate models of manufacturing processes and the products being manufactured. The goal of the research is to enable a radical change in manufacturing effectiveness and sustainability.
The target type of manufacturing is component-based modular reconfigurable systems, i.e. systems that are built up of various elements and assembled together, in a similar fashion to building with 'lego'. This is a class of manufacturing system that is typically used in assembly and handling applications, where you tend to find families of modular machine components that can be reused and reconfigured as the product, and hence production processes change. Major applications for this are in the automotive and aerospace sectors. One example is in powertrain assembly, as seen in the UK at Ford. If the re-configurability of such production systems can be enhanced, Ford estimate that potential savings of over 30% in costs are achievable with a target of a 50% reduction in the time to build and commission such a system that typically costs £30 million per engine line. The realisation of this research has the potential to help enable the retention of high value engineering activity in the UK by improving the competiveness in the engineering of reconfigurable manufacturing systems.
The capability to achieve this aim is to be built on the foundation of current, internationally leading research at Loughborough University, which has created a method for building reconfigurable systems from reusable components that is currently being adopted in automotive supply chains.
The concepts of flexible and reconfigurable manufacturing systems are well established; however problems still exist in the effective, efficient, rapid, configuration of such flexible systems, particularly as lifecycle product changes occur, whether such changes are minor or more fundamenal. Many flexible and reconfigurable system examples exist. However, most are designed intuitively and a systematic methodology is still lacking. Additionally, engineering this integration of product and processes is essential in a lifecycle context across the supply-chain, yet this remains largely unaddressed.
Virtual engineering also has a major role to play in that we can simulate production systems and products. However the effectiveness of such simulation design tools for reconfigurable systems remains poor. Such tools need to be able to encompass the full system lifetime and be able to replicate the functions of the production system exactly in the models. These models are key enablers for understanding what might happen throughout a production system's lifecycle and can drive better configuration of the modular manufacturing systems we aspire to create.

Structured Data / Microdata


Grant Event Details:
Name: Knowledge Driven Configurable Manufacturing (KDCM) - EP/K018191/1
Start Date: 2013-04-01T00:00:00+00:00
End Date: 2018-03-31T00:00:00+00:00

Organization: University of Warwick

Description: The proposed research programme will attempt to create self-reconfiguring manufacturing systems that are based on intelligent and highly accurate models of manufacturing processes and the products being manufactured. The goal of the research is to enable a ...