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A best practice advice system to support automotive engineering analysis processes

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Abstract

Engineering design teams today are often widely distributed, and design authority is shared between collaborating companies. Technology is changing rapidly, and understanding of the most appropriate approach to the application of engineering assessment tools is developing accordingly. There is therefore a need to support coordination and auditing of engineering processes, and to provide best practice advice. This paper describes a computing approach to the provision of best practice advice within a workflow-enabled engineering computing environment. The engineering context is described using a formal information model for automotive engineering analysis processes, embedded in an object database. This same model is used to associate best practice advice documents with the engineering context. The best practice adviser (BPA) system assembles four types of information: general information that is pertinent to a particular activity, irrespective of the context in which it is taking place; context-specific information that is pertinent to the particular circumstance in which an activity is taking place; errors and warnings that may be encountered in the activity, especially when software is being used, and examples of previous application of the activity in related contexts. The BPA is implemented in a three-tier architecture using server pages technology. In the absence of any suitable matching information for a particular context in the BPA database, the BPA Server can execute a “close-match” algorithm which searches the database for information that is provided on contexts that are close to the user’s interest. The paper describes the initial implementation and population of the BPA, and presents some early feedback from prototype trials.

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Acknowledgements

The authors gratefully acknowledge the support of DG III of the European Commission for the INTEREST project under the ESPRIT/AIT initiative. They are also grateful to their colleagues in the project for their contributions to this paper.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Bath, Bath, UK

    C. A. McMahon

  2. Faculty of Engineering, University of Bristol, Bristol, UK

    Y. Liu & R. Crossland

  3. Cedar Ltd, London, UK

    D. Brown & D. Leal

  4. Land Rover, Warwick, UK

    J. Devlukia

Authors
  1. C. A. McMahon
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  2. Y. Liu
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  3. R. Crossland
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  4. D. Brown
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  5. D. Leal
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  6. J. Devlukia
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Correspondence to C. A. McMahon.

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McMahon, C.A., Liu, Y., Crossland, R. et al. A best practice advice system to support automotive engineering analysis processes. Engineering with Computers 19, 271–283 (2004). https://doi.org/10.1007/s00366-003-0267-x

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