Year of Publication
Doctor of Philosophy (PhD)
Dr. Ibrahim S. Jawahir
It is important for organizations to understand the factors responsible for establishing sustainable continuous improvement (CI) capabilities. This study uses learning curves as the basis to examine learning obtained by team members doing work with and without the application of fundamental aspects of the Toyota Production System. The results are used to develop an effective model to guide organizational activities towards achieving the ability to continuous improve in a sustainable fashion.
This research examines the effect of standardization and waste elimination activities supported by systematic problem solving on team member learning at the work interface and system performance. The results indicate the application of Standard Work principles and elimination of formally defined waste using the systematic 8-step problem solving process positively impacts team member learning and performance, providing the foundation for continuous improvement Compared to their untreated counterparts, treated teams exhibited increased, more uniformly distributed, and more sustained learning rates as well as improved productivity as defined by decreased total throughput time and wait time. This was accompanied by reduced defect rates and a significant decrease in mental and physical team member burden.
A major outcome of this research has been the creation of a predictive probability model to guide sustainable CI development using a simplified assessment tool aimed at identifying essential organizational states required to support sustainable CI development.
Maginnis, Michael Abbot, "THE DEVELOPMENT OF A PREDICTIVE PROBABILITY MODEL FOR EFFECTIVE CONTINUOUS LEARNING AND IMPROVEMENT" (2012). Theses and Dissertations--Mechanical Engineering. 2.