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Case Example 2: Data analysis for diagnostics and process monitoring of automotive engines

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Part of the book series: Manufacturing Systems Engineering Series ((MSES,volume 5))

Abstract

This case example describes software for analysis of data from cold tests of fully and partially assembled engines. Cold testing of engines (testing without fueled running) at engine assembly plants has attracted considerable interest for its potential to reduce test costs and improve product quality. Cold testing of newly manufactured engines offers several advantages over traditional ‘hot’ tests (fueled, running tests):

  • Speed: fewer hookups and detachments, shorter overall test time.

  • Cost: less expensive test and facility hardware; cold testing also offers improved safety and environmental conditions.

  • Quality: extremely sensitive to mechanical deviations which affect performance and therefore much lower probability of missing a failure.

  • Coverage: wide range of potential defects can be detected and identified.

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References

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  2. Marko, K.A., James, J., Dosdall, J. and Murphy, J. (1989) Automotive control system diagnostics using neural nets for rapid pattern classification of large data sets. Proceedings of IJCNN, 11–13.

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© 1999 Springer Science+Business Media Dordrecht

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Bryant, B.D., Marko, K.A. (1999). Case Example 2: Data analysis for diagnostics and process monitoring of automotive engines. In: Lee, J., Wang, B. (eds) Computer-aided Maintenance. Manufacturing Systems Engineering Series, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5305-2_13

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  • DOI: https://doi.org/10.1007/978-1-4615-5305-2_13

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7421-3

  • Online ISBN: 978-1-4615-5305-2

  • eBook Packages: Springer Book Archive

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