Loughborough University
Browse

An integrated model driven approach in support of next generation

Download (380.01 kB)
conference contribution
posted on 2011-07-26, 10:02 authored by Tariq Masood, Richard H. Weston
Shortened product life cycles and globalization have induced dynamism and uncertainty into world markets. Hence manufacturing enterprises (MEs) can gain competitive advantage from being reconfigurable. But appropriate application of agile and lean Manufacturing philosophies must complement the application of reconfiguration techniques. However, choosing and applying the best philosophies and techniques are far from being well understood and well structured processes because most MEs deploy complex and unique configurations of processes and resource systems, and seek economies of scope and scale in respect of a number of distinctive product flows. It follows that systematic methods of achieving model driven configuration of component based manufacturing systems are required to design, engineer and change next generation MEs. This paper discusses research aimed at developing and prototyping a model-driven environment for the design, optimization and control of reconfigurable manufacturing enterprises with an embedded capability to handle various types of change. The developed environment supports the engineering of common types of strategic, tactical and operational process found in many MEs. Also reported are initial findings of manufacturing case study work in which coherent multi-perspective models of a specific ME have facilitated process reengineering and associated resource system configuration. The paper outlines key areas for future research including the need for research into unified modelling approaches and interoperation of partial models in support of complex organisation design and change (OD&C).

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

MASOOD, T. and WESTON, R.H., 2008. An integrated model driven approach in support of next generation. IN: Proceedings of the 4th Virtual International International Conference on Intelligent Production Machines and Systems (I*PROMS), The Internet, July 1 -14, 7pp.

Publisher

© The authors

Version

  • AM (Accepted Manuscript)

Publication date

2008

Notes

This is a conference paper.

Language

  • en