Thesis Details

Thesis Title: Process and Product Data Management for Staple Yarn Manufacturing
Thesis Author: Brian Hamilton
Abstract: The contemporary cotton spinning mill is home to modern machinery capable of generating massive amounts of data. This data comes in the form of online data, which is real-time data created by the processing machinery, and offline data, which is created via laboratory testing of samples. Data mining is the use of advanced statistical tools to discover hidden relationships within a large set of data. When there is a situation in which a vast amount of data is available, such as in the US cotton yarn spinning industry, there is an opportunity for data mining. This study applied data mining techniques to two data sets. One set was obtained from an open-end spinning plant. The other set is the results of a government research project. This analysis served to discover unknown trends within this data sample and to determine the potential value of data mining for the cotton spinning industry. This research presents a perspective into the current state of data management in the cotton spinning industry obtained through interviews and observations of active spinning mills. It also details the data mining performed on the acquired data sets and suggests a data management model which facilitates effective data mining and enhanced decision making.