A Proposed Data Mining Methodology and its Application to Industrial Engineering

Author

Jose Solarte, University of Tennessee - Knoxville

Date of Award

8-2002

Degree Type

Thesis

Degree Name

Master of Science

Major

Industrial Engineering

Major Professor

Denise F. Jackson

Committee Members

Robert E. Ford, Tyler A. Kress

Abstract

Data mining is the process of discovering correlations, patterns, trends or relationships by searching through a large amount of data stored in repositories, corporate databases, and data warehouses. Industrial engineering is a broad field and has many tools and techniques in its problem-solving arsenal. The purpose of this study is to improve the effectiveness of industrial engineering solutions through the application of data mining. To achieve this objective, an adaptation of the engineering design process is used to develop a methodology for effective application of data mining to databases and data repositories specifically designed for industrial engineering operations. This paper concludes by describing some of the advantages and disadvantages of the application of data mining techniques and tools to industrial engineering; it mentions some possible problems or issues in its implementation; and finally, it provides recommendations for future research in the application of data mining to facilitate decisions relevant to industrial engineering.

Recommended Citation

Solarte, Jose, "A Proposed Data Mining Methodology and its Application to Industrial Engineering. " Master's Thesis, University of Tennessee, 2002.
https://trace.tennessee.edu/utk_gradthes/2172