Proceedings of the 2009 Industrial Engineering Research Conference Enhancing Lean Sustainability via Bayesian Network Techniques Yanzhen Li Gagan Rajpal Rapinder S. Sawhney Xueping Li Department of Industrial and Information Engineering University of Tennessee, Knoxville, Tennessee 37996, USA Abstract With the manufacturing system and its external environment becoming more and more complex, a great range of risk factors could affect the sustainability of Lean implementation. The purpose of this study is to develop a risk assessment model to systematically evaluate the potential risks and enhance the implementation of Lean initiatives. Deriving from the Bayesian Network (BN) methodology, the proposed model combines graphical approach to represent cause-and-effect relationships between events of interests and probabilistic inference to estimate their likelihoods. The model can be used for assessing the risks associated with Lean initiatives and prioritizing efforts to minimize the potential risks. Keywords Bayesian Network, Lean Manufacturing, Lean Sustainability, Risk Management 1. Introduction Today's U.S. manufacturers are under tremendous pressure of improving their performance in order to stay competitive in the rapidly expanding global economy. The recently broke-out financial crisis has worsened the trend of manufacturing as global demand plummets. U.S. manufacturers have been using numerous approaches to improve their production performance. Among them, Lean manufacturing has proved to be effective in reducing costs, increasing efficiency, and improving quality. The term Lean production was coined by Womack, Jones and Roos in their book, The Machine That Changed the Word [1], based on a five-year study of automobile industry. Compared to the traditional mass production, Lean production is “lean” because “it uses less of everything compared to mass production - half the human effort in the factory, half the manufacturing space, half the investment in tools, half the engineering hours to develop a new product in half the time. Also, it requires keeping far less than half the needed inventory on site, results in many fewer defects, and produces a greater and ever growing variety of products” [1]. Many efforts have also been conducted in different aspects of the manufacturing system other than the production line. Examples are supply chain system [2], human issues [3], and maintenance [4]. Because of their advantages in efficiency, cost, quality and flexibility in production, Lean techniques can also contribute to the performance improvements of other industries such as service sector [5], health care [6], and construction [7]. Lots of manufacturing organizations are developing or have already had Lean manufacturing strategies in place. However, many companies have tumbled this journey or failed to achieve the desired results. According to Rubrich [8], 884 U.S. companies responded to a survey conducted by Industry Week magazine in 2004. 72% of them were undergoing the implementation of an improvement strategy such as Lean, Six Sigma, Agile manufacturing, or others. However, “75% of these companies reported that they had ‘no’ or just ‘some’ progress toward their World Class manufacturing goals”. “Only 2% of the companies reported achieving World Class manufacturing status”. It has been observed that, while the application of individual tools can be beneficial in either short or long run, the transition of the entire process, which represents the real solution, is very difficult to achieve. This is largely due to the fact that it requires cultural conversion to achieve operational excellence. Such major alteration could pose great risks to the implementation of Lean manufacturing strategies. 1173