Production Systems Engineering (PSE) is an emerging branch of Engineering intended to uncover fundamental laws that govern production systems and utilize them for the purposes of analysis, continuous improvement, and design. PSE uses traditional terms, such as bottleneck, leanness, continuous improvement, etc., but infuses them with precise engineering knowledge and, thereby, offers a possibility of designing and managing production systems with the highest efficiency and guaranteed performance.
The approach of PSE is based on mathematical modeling of serial lines and assembly systems, with subsequent analyses of the obtained models using recursive aggregation procedures. As a result, methods for solving the following problems are derived: Performance analysis; Identification of bottlenecks; Continuous improvement; Design of lean buffering; Product Quality; Transient Behavior. To enable applications of these methods, toolboxes that implement procedures and algorithms obtained in PSE have been developed.
PSE has been applied to dozens of production systems in large, medium, and small manufacturing organizations. These include, for example, GM, Ford, Chrysler, Toyota, MillerCoors, Kraft Foods, Kroger, Lexmark, Subzero, Ruud Lighting, HellermannTyton, etc. Consistently, significant improvements in productivity, quality, and customer demand satisfaction have been obtained.
The intent of this website is to present PSE to both academic and industrial audiences. For the academic audience, the emphasis is on the theory and illustrative case studies. For the industrial audience, the emphasis is on practical issues and applications. For both audiences, educational materials (textbooks) and computational means (toolboxes) are provided.
The results reported here have been developed in the research group of Professor Semyon M. Meerkov at the University of Michigan, Ann Arbor, MI. In addition to the co-authors of this website, Professor Jingshan Li (currently at the University of Wisconsin, Madison, WI) and Professor Liang Zhang (currently at the University of Wisconsin, Milwaukee, WI), this group included, over the years, the following doctoral students: Jong-Tae Lim (currently Professor at KAIST, Korea), Ferudun Top, David Jacobs (currently Plant Manager at BorgWarner, USA), Chi-Tsung Kuo (deceased) , Shu-Yin Chiang (currently Professor at Ming Chuan University, Taiwan), and Emre Enginarlar (currently at Los Alamos National Lab., USA).
The approach of PSE is based on mathematical modeling of serial lines and assembly systems, with subsequent analyses of the obtained models using recursive aggregation procedures. As a result, methods for solving the following problems are derived: Performance analysis; Identification of bottlenecks; Continuous improvement; Design of lean buffering; Product Quality; Transient Behavior. To enable applications of these methods, toolboxes that implement procedures and algorithms obtained in PSE have been developed.
PSE has been applied to dozens of production systems in large, medium, and small manufacturing organizations. These include, for example, GM, Ford, Chrysler, Toyota, MillerCoors, Kraft Foods, Kroger, Lexmark, Subzero, Ruud Lighting, HellermannTyton, etc. Consistently, significant improvements in productivity, quality, and customer demand satisfaction have been obtained.
The intent of this website is to present PSE to both academic and industrial audiences. For the academic audience, the emphasis is on the theory and illustrative case studies. For the industrial audience, the emphasis is on practical issues and applications. For both audiences, educational materials (textbooks) and computational means (toolboxes) are provided.
The results reported here have been developed in the research group of Professor Semyon M. Meerkov at the University of Michigan, Ann Arbor, MI. In addition to the co-authors of this website, Professor Jingshan Li (currently at the University of Wisconsin, Madison, WI) and Professor Liang Zhang (currently at the University of Wisconsin, Milwaukee, WI), this group included, over the years, the following doctoral students: Jong-Tae Lim (currently Professor at KAIST, Korea), Ferudun Top, David Jacobs (currently Plant Manager at BorgWarner, USA), Chi-Tsung Kuo (deceased) , Shu-Yin Chiang (currently Professor at Ming Chuan University, Taiwan), and Emre Enginarlar (currently at Los Alamos National Lab., USA).
Acknowledgement: The material reported on this website has been obtained in the framework of the research supported, for over 25 years, by the U.S. National Science Foundation. Many companies, including GM, Ford, and Chrysler, also contributed by providing funds and enabling case studies. Without this support this research would not have been possible.
About the image at the top of this page: In 1932, the famous Mexican artist, Diego Rivera, was commissioned by Edsel Ford, President of Ford Motor Company, to create two murals for the Detroit Institute of Arts. The murals, completed in 1933, are currently located on the Northern and Southern walls of the Detroit Institute of Art's Rivera Court. The image on this page is the Northern Wall’s mural. It depicts operations involved in the production of the engine and transmission for the 1932 Ford V8. Although the manufacturing technology has changed dramatically since then, the fundamental principles of production systems did not. PSE is devoted to these principles.
About the image at the top of this page: In 1932, the famous Mexican artist, Diego Rivera, was commissioned by Edsel Ford, President of Ford Motor Company, to create two murals for the Detroit Institute of Arts. The murals, completed in 1933, are currently located on the Northern and Southern walls of the Detroit Institute of Art's Rivera Court. The image on this page is the Northern Wall’s mural. It depicts operations involved in the production of the engine and transmission for the 1932 Ford V8. Although the manufacturing technology has changed dramatically since then, the fundamental principles of production systems did not. PSE is devoted to these principles.
© 2012 J. Li, S.M. Meerkov, and L. Zhang