Statistical Quality Assurance Methods for Engineers

Rating:
Summary: great book on quality control from a statisticians viewpoint
Review: In my work with engineers at Biosense Webster I am often confronted with issues related to the design and/or analysis of an R&R Gauge study, the construction of tolerance intervals or the estimate of a process capability parameter. I often refer to or refer them to Vardeman's book to handle these problems. Many engineers are taught to do gauge R&R studies but they just know how to turn the crank. They don't have an understanding of the analysis of variance that gives meaning to the analysis and motivates the design. Too often sample estimates are treated as though they are the actual parameters. Vardeman and Jobe write for the engineers but with a statistician's perspective and understanding. They cover control charts, process capability, experimental design, inspection sampling and TQM. They provide simple formulas and tables to give the engineer the tools he needs to handle most common quality control problems. More importantly though, they also provide excellent development and discussion so that there can be depth of understanding of the key concepts. This book is not only good for engineers but also is a good reference book for statisticians. It can easily be used for a first course in quality control. Another good book along these lines is Ryan's "Statistical Methods for Quality Improvement". Certainly, Juran's "Quality Handbook" is a great reference also.

Rating:
Summary: great book on quality control from a statisticians viewpoint
Review: In my work with engineers at Biosense Webster I am often confronted with issues related to the design and/or analysis of an R&R Gauge study, the construction of tolerance intervals or the estimate of a process capability parameter. I often refer to or refer them to Vardeman's book to handle these problems. Many engineers are taught to do gauge R&R studies but they just know how to turn the crank. They don't have an understanding of the analysis of variance that gives meaning to the analysis and motivates the design. Too often sample estimates are treated as though they are the actual parameters. Vardeman and Jobe write for the engineers but with a statistician's perspective and understanding. They cover control charts, process capability, experimental design, inspection sampling and TQM. They provide simple formulas and tables to give the engineer the tools he needs to handle most common quality control problems. More importantly though, they also provide excellent development and discussion so that there can be depth of understanding of the key concepts. This book is not only good for engineers but also is a good reference book for statisticians. It can easily be used for a first course in quality control. Another good book along these lines is Ryan's "Statistical Methods for Quality Improvement". Certainly, Juran's "Quality Handbook" is a great reference also.