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Product and manufacturing process improvement using data mining

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thesis
posted on 12.09.2018 by Muhammad Shahbaz
In recent years manufacturing enterprises are increasingly automated and collect and store large quantities of data relating to their products and production systems. This electronically stored data can hold both process measures and hidden information, which can be very important when discovered. Knowledge discovery in databases provides the tools to explore historic or current data to reveal many kinds of previously unknown knowledge from these databases. Manufacturing enterprises data is complex and may include information relating to design, process improvement and limitations, manufacturing machines and tools, and product quality. This thesis focuses on issues relating to information extraction from engineering databases in general and from manufacturing processes in particular using their historical databases. It also addresses the important issue of how the process or the design of the product can be improved based on such information. [Continues.]

Funding

Loughborough University, Wolfson School of Mechanical and Manufacturing Engineering (scholarship).

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Publisher

© Muhammad Shahbaz

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2005

Notes

A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy at Loughborough University.

Language

en

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