Loughborough University
Browse
IJPR Paper_Before Review.pdf (829.46 kB)

Methods for the capture of manufacture best practice in product lifecycle management

Download (829.46 kB)
journal contribution
posted on 2012-12-21, 14:18 authored by A. George Gunendran, Robert I.M. Young
The capture of manufacturing best practice knowledge in product lifecycle management systems has significant potential to improve the quality of design decisions and minimise manufacturing problems during new product development. However, providing a reusable source of manufacturing best practice is difficult due to the complexity of the viewpoint relationships between products and the manufacturing processes and resources used to produce them. This paper discusses how best to organise manufacturing best practice knowledge, the relationships between elements of this knowledge plus their relationship to product information. The paper also explores the application of UML-2 as a system design tool which can model these relationships and hence support the reuse of system design models over time. The paper identifies a set of part family and feature libraries and, most significantly, the relationships between them, as a means of capturing best practice manufacturing knowledge and illustrates how these can be linked to manufacturing resource models and product information. Design for manufacture and machining best practice views are used in the paper to illustrate the concepts developed. An experimental knowledge based system has been developed and results generated using a power transmission shaft example.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

GUNENDRAN, A.G. and YOUNG, R.I.M., 2010. Methods for the capture of manufacture best practice in product lifecycle management. International Journal of Production Research, 48 (20), pp. 5885 - 5904.

Publisher

© Taylor & Francis Ltd.

Version

  • SMUR (Submitted Manuscript Under Review)

Publication date

2010

Notes

This article was published in the International Journal of Production Research [© Taylor & Francis]. The definitive version is available at: http://dx.doi.org/10.1080/00207540903104210

ISSN

0020-7543

eISSN

1366-588X

Language

  • en

Usage metrics

    Loughborough Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC