Doctoral Dissertations

Keywords and Phrases

Artificial Intelligence; Clustering; Critical Success Factors; Implementation; Lean Manufacturing; Modeling

Abstract

”Lean has become a common term and goal in organizations throughout the world. The approach of eliminating waste and continuous improvement may seem simple on the surface but can be more complex when it comes to implementation. Some firms implement lean with great success, getting complete organizational buy-in and realizing the efficiencies foundational to lean. Other organizations struggle to implement lean. Never able to get the buy-in or traction needed to really institute the sort of cultural change that is often needed to implement change. It would be beneficial to have a tool that organizations could use to assess their ability to implement lean, the degree to which they have implemented lean, and what specific areas they should focus on to improve their readiness or implementation level.

This research investigates and proposes two methods for assessing lean implementation. The first is utilizing standard statistical regression. A regression model was developed that can be used to assess the implementation of lean within an organization. The second method is based in artificial intelligence. It utilizes an unsupervised learning algorithm to develop a training set corresponding to low, medium, and high implementation. This training set could then be used along with a supervised learning algorithm to dynamically monitor an organizations readiness or implementation level and make recommendations on areas to focus on to improve implementation success”--Abstract, page iv.

Advisor(s)

Cudney, Elizabeth A.

Committee Member(s)

Allada, Venkat
Gosavi, Abhijit
Jackson, David C.
Liou, Frank W.
Sun, Zeyi

Department(s)

Engineering Management and Systems Engineering

Degree Name

Ph. D. in Engineering Management

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2020

Journal article titles appearing in thesis/dissertation

  • Structural equation modeling in lean practices: A systematic literature review
  • Determining critical success factors for a lean culture
  • Using cluster analysis to identify factors affecting lean implementation

Pagination

x, 93 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2020 Richard Charles Barclay, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11773

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