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Information Management and Process Improvement Using Data Mining Techniques

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1821))

Abstract

This paper describes a computer component manufacturing scenario which concentrates on the application of data mining techniques to improve information management and process improvement within a manufacturing scenario. The case study involved, relates to an engineering component manufacturing company with a consortium of several plant outlets in various geographical locations world-wide. Currently, data, information and knowledge management, transparency and communication between plants within the scenario are limited. As a result, important information and best practices are not collectively pooled or conversed with the objective of improving information management and process development procedures on a global basis. This paper explores the possible enhancement of these consortium relationships and it also investigates the use of data mining techniques with the potential to advance information management and process improvement within the manufacturing environment concerned.

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References

  1. Fayyad, U, Piatetsky-Shapiro, Smyth, P & Uthurusamy, R, “Advances in Knowledge Discovery and Data Mining”, AAAI Press, 1996.

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© 2000 Springer-Verlag Berlin Heidelberg

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Gibbons, W.M., Ranta, M., Scott, T.M., Mantyla, M. (2000). Information Management and Process Improvement Using Data Mining Techniques. In: Logananthara, R., Palm, G., Ali, M. (eds) Intelligent Problem Solving. Methodologies and Approaches. IEA/AIE 2000. Lecture Notes in Computer Science(), vol 1821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45049-1_12

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  • DOI: https://doi.org/10.1007/3-540-45049-1_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67689-8

  • Online ISBN: 978-3-540-45049-8

  • eBook Packages: Springer Book Archive

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