Keywords and Phrases
Artificial Intelligence; Clustering; Critical Success Factors; Implementation; Lean Manufacturing; Modeling
”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.
Cudney, Elizabeth A.
Jackson, David C.
Liou, Frank W.
Engineering Management and Systems Engineering
Ph. D. in Engineering Management
Missouri University of Science and Technology
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
x, 93 pages
© 2020 Richard Charles Barclay, All rights reserved.
Dissertation - Open Access
Barclay, Richard Charles, "Development of a modeling algorithm to predict lean implementation success" (2020). Doctoral Dissertations. 2934.