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Introduction to Data Mining and its Applications to Manufacturing

Introduction to Data Mining and its Applications to Manufacturing

Jose D. Montero
Copyright: © 2008 |Pages: 23
ISBN13: 9781599049519|ISBN10: 1599049511|EISBN13: 9781599049526
DOI: 10.4018/978-1-59904-951-9.ch012
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MLA

Montero, Jose D. "Introduction to Data Mining and its Applications to Manufacturing." Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, IGI Global, 2008, pp. 146-168. https://doi.org/10.4018/978-1-59904-951-9.ch012

APA

Montero, J. D. (2008). Introduction to Data Mining and its Applications to Manufacturing. In J. Wang (Ed.), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (pp. 146-168). IGI Global. https://doi.org/10.4018/978-1-59904-951-9.ch012

Chicago

Montero, Jose D. "Introduction to Data Mining and its Applications to Manufacturing." In Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, 146-168. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-951-9.ch012

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Abstract

This chapter provides a brief introduction to data mining, the data mining process, and its applications to manufacturing. Several examples are provided to illustrate how data mining, a key area of computational intelligence, offers a great promise to manufacturing companies. It also covers a brief overview of data warehousing as a strategic resource for quality improvement and as a major enabler for data mining applications. Although data mining has been used extensively in several industries, in manufacturing its use is more limited and new. The examples published in the literature of using data mining in manufacturing promise a bright future for a broader expansion of data mining and business intelligence in general into manufacturing. The author believes that data mining will become a main stream application in manufacturing and it will enhance the analytical capabilities in the organization beyond what is offered and used today from statistical methods.

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