Dr. Kailash (Kal) C. Kapur is a professor of Industrial & Systems Engineering at the University of Washington, where he was also the Director from 1993 to 1999. He was a professor and the director of the school of Industrial Engineering, The University of Oklahoma, Norman, Oklahoma during 1989-1992. He was a professor in the Department of Industrial and Manufacturing Engineering at Wayne State University, Detroit, Michigan during 1970-1989. Dr. Kapur has worked with General Motors Research Laboratories as a senior research engineer. He has also worked with Ford Motor Company as a visiting scholar and the U.S. Army, Tank-Automotive Command as a reliability engineer. He has served on the Board of Directors of American Supplier Institute, Inc., Dearborn, Michigan.
Dr. Kapur received a Bachelor's degree (1963) in Mechanical Engineering with Distinction from Delhi University; M. Tech. degree (1965) in Industrial Engineering from Indian Institute of Technology; M.S. degree (1967) in Operation Research; and Ph.D. degree (1969) in Industrial Engineering from the University of California, Berkeley.
He has co-authored the book Reliability in Engineering Design, John Wiley & Sons. He has written chapters on reliability and quality engineering for several handbooks such as Industrial Engineering and Mechanical Design. He has published over forty papers in technical, research and professional journals. He is a member of ORSA, TIMS, IIE, ASQC, and ASEE. He is on the editorial board of journals such as Quality Engineering and Transactions of the Institute of Industrial Engineers. He is a registered professional engineer. Dr. Kapur has received funding from OCAST (Oklahoma Center for Applied Science and Technology), General Motors, Ford, US Army Tank-Automotive Command and NSF.
He has done extensive consulting in design of experiments, Taguchi Methods, reliability design and management, statistical process control, quality engineering, and total quality management.
He received The Allan Chop Technical Advancement Award from the Reliability Division and The Craig Award from the Automotive Division of American Society for Quality Control. He was elected a Fellow of American Society for Quality Control and the Institute of Industrial Engineers.
OPTIMUM SPECIFICATION FOR QUALITY IMPROVEMENT
The object of any quality program is to minimize total losses to both the producer and the consumer - thus the whole society. Optimum specifications should be developed based on total quality costs due to variation from target, measurement or inspection costs, costs associated with nonconforming units and/or rework, etc. The objective of this research is to develop an economic based methodology to define optimum specifications.
QUALITY ENGINEERING: DESIGN, OPTIMIZATION, AND CONTROL
The objective of the research is to develop a generic optimization model for any product or process. For any performance characteristic, we have a target value and we like to minimize the variation from target due to noise factors. For dynamics systems, the target changes are based on the intent of the customer. This research focus on various measures of robustness of the system, such as signal to noise ratio, and evaluates their effectiveness. Optimization and control issues in the context of design of experiments are being explored to improve quality and productivity.
QUALITY FUNCTION DEPLOYMENT
Quality Function Deployment (QFD) means the all operation of the company are driven by the "voice of the customer". QFD uses the systems and design approach to breakdown the voice of the customer into segments and identifies specific mean for achieving each segment. This research focuses on the development of a systems approach and associated methodologies and the their integration to achieve the objectives for a customer driven company.
RELIABILITY ANALYSIS FOR MULTISTATE SYSTEMS WITH MULTISTATE COMPONENTS
An important problem in reliability theory is to determine the reliability of a complex system give the reliabilities of its components. In real life, the system and its components can be found in a range of states varying from perfect functioning through various levels of performance degradation to complete failure. The focus of this research is to develop properties of system structure function and to develop computational methods for estimating system reliability measures. Multi-level modular decomposition methods are also being developed for such systems.
ROBUST DESIGN FOR SIMULTANEOUS ENGINEERING
A product must be designed for manufacturability and must be insensitive to variability present in the production environment and in the field when used by the customer. Products and processes that are less sensitive to noise factor are called "robust". Simultaneous engineering focuses on the integration of engineering design and manufacturing. The objective of this research is to develop a design methodology so that designs are robust against manufacturing an other environmental and "time" oriented noise factors.
- IND E 315: Probability & Statistics for Engineers
- IND E 316: Regression Analysis and Design of Experiments
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