Optimizing Factory Performance
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Manufacturing is a crucial component of the foundation that maintains the security, health, and wealth of any country. One of the most important measures of manufacturing performance is cycle time—the time between introduction of a job into the factory and its completion. Firms whose factories deliver the right product to the right customer at the right time ultimately dominate those that are runner-ups. Manufacturers that are fast and agile will be the survivors in the highly competitive world of making “things.”
Over the past 50 years, more than 50 management and manufacturing fads and fashions have been proposed for the achievement of improved organizational and factory performance. Almost all have failed to live up to their hype. Today, in fact, the principal performance measure of a factory—load-adjusted cycle-time efficiency—is the same or only marginally better than that of factories of a half-century ago. Consequently, there is enormous room for improvement in the running of almost any factory—in any country.
While methods such as lean manufacturing, reengineering, theory of constraints, and six sigma may—when and if applied properly—improve factory performance, they represent just one part of the solution. To achieve significant and, in particular, sustainable performance improvement, an approach that balances the art and science of manufacturing must be employed. It will necessitate, however, a paradigm shift—a shift akin to that which occurred when the third dimension of warfare was realized by means of exploitation of the airplane.
In this course, we examine manufacturing's importance, history, and terminology. We show that to improve factory performance cost-effectively, one must venture beyond the traditional first and second dimensions of manufacturing—the dimensions that rely almost exclusively on physical changes to the factory or its components. Instead, the most effective approach to improved factory performance may be achieved by means of the third dimension of manufacturing—the dimension involving changes to factory operating and maintenance protocols (i.e., the strategies and tactics employed to actually run a factory).
We introduce the operating and maintenance protocols best suited for effectively dealing with the two main enemies of factory performance; i.e., the obstacles of complexity and variability. While the approaches illustrated have a scientific basis and rely on the three fundamental equations and one fundamental model of manufacturing, the material is presented in a way as to limit the need for expertise in mathematics beyond that of a high school student.
Optimizing Factory Performance is a 3-day course that provides detailed instruction on those methods that comprise the Third Dimension of Manufacturing. Implementation of these methods is discussed and illustrated. Attendees will be able to actually manage and run a simulated factory. The course is designed for those who serve as managers, engineers, or scientists within the manufacturing sector.
- Introduction and overview
- A brief history of manufacturing: Everything old is new again
- The 3 dimensions of manufacturing
- Basic concepts, definitions, and terminology
- Workstation-Centric versus Process Step-Centric focus
- Ignizio-Burke 12 workstation demonstration ... in 2 dimensions
- When, where, and why the fundamental premise of lean fails
- The scope and limitations of the theory of constraints
- The impact of complexity and variability on performance
- The 3 fundamental equations of manufacturing
- Ignizio-Burke 12 workstation model ... in 3 dimensions
- The Good, the Bad, and the Ugly measures of factory performance
- A look back, a look forward
- Practical and pragmatic methods for reducing complexity
- Process step reduction and refinement
- C4U compliant specifications
- The Waddington Widget: An exercise in the development of C4U compliant PM and Operating Specifications
- Introduction to Waddington Analysis
- Practical and pragmatic methods for educing variability
- The impact of clustering: Smoother is better
- Allocation of personnel
- Putting it all together: Improving the performance of real factories
- A return to the 12 workstation model factory
- Establishment of the factory performance team
- Do's and Don'ts
- Summary and conclusions
Dr. James Ignizio
James Ignizio received a Ph.D. in Industrial Engineering and Operations Research from Virginia Tech in 1971. He is a Fellow of the Institute of Industrial Engineering, a Fellow of the British Operational Research Society, and a Fellow of the World Academy of Productivity Science.
Dr. Ignizio is the author of 9 books and more than 350 publications, including over 150 refereed papers in international professional journals. In 1980 he was awarded The First Hartford Prize by the U.S. National Safety Council for his contributions to this country’s manned moon-landing program. Dr. Ignizio was also a Fellow and Senior Research Associate for the National Research Council from 1982-6. In 2002 Dr. Ignizio was inducted into the Academy of Distinguished Alumni of Virginia Tech.
Dr. Ignizio has held the positions of Professor and Chair: University of Virginia; Professor and Chair: University of Houston; Distinguished Professor: Pennsylvania State University; Visiting Professor: Naval Postgraduate School; Visiting Professor: U.S. Army ALMC; and Distinguished Adjunct Professor: Helsinki School of Economics. His efforts in the fields of Industrial Engineering, Operational Research, and AI have received international recognition and his textbooks on these topics have been widely adopted in the US and abroad. Dr. Ignizio’s short courses on Operational Research, Industrial Engineering, Manufacturing Science, and Artificial Intelligence have been attended by several thousands of industrial, governmental, and military sector personnel over the past 30 years.
Prior to his 30-plus year academic career, Dr. Ignizio served as a Program Manager for the Apollo manned moon-landing mission. He was also Deputy Director of the Apollo/Saturn Integration Committee – with a focus on Fast Cycle Time. Dr. Ignizio has also served as a consultant to numerous industrial and governmental organizations in both the United States and abroad, including the U.S. Army, U.S. Air Force, U.S. Navy, NASA, SDI (‘Star Wars’), Litton, Exxon, Texaco, Boeing, SAI, GRC, SRI, Bell Labs, Finland’s Ministry of Economics, Quantas Airways, KAIST, Virginia Manufacturing Institute, Chase Bank, and the Commercial Bank of Greece.