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Top Ten Quality Gurus 1. Dr. Walter Shewhart 2. Dr. W. Edwards

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Top Ten Quality Gurus 1. Dr. Walter Shewhart 2. Dr. W. Edwards Top Ten Quality Gurus 1. Dr. Walter Shewhart 2. Dr. W. Edwards Deming 3. Dr. Joseph M. Juran 4. Armand V. Feigenbaum 5. Dr. Kaoru Ishikawa 6. Dr. Genichi Taguchi 7. Shigeo Shingo 8. Philip B. Crosby 9. Dr. Eliyahu M. Goldratt 10. Taiichi Ohno 1. Dr. Walter Shewhart Walter Andrew Shewhart (pronounced like "shoe-heart", March 18, 1891 - March 11, 1967) was an American physicist, engineer and statistician, sometimes known as the father of statistical quality control. W. Edwards Deming said of him: As a statistician, he was, like so many of the rest of us, self-taught, on a good background of physics and mathematics. Early life and education Born in New Canton, Illinois to Anton and Esta Barney Shewhart, he attended the University of Illinois before being awarded his doctorate in physics from the University of California, Berkeley in 1917. Work on industrial quality Bell Telephone’s engineers had been working to improve the reliability of their transmission systems. Because amplifiers and other equipment had to be buried underground, there was a business need to reduce the frequency of failures and repairs. When Dr. Shewhart joined the Western Electric Company Inspection Engineering Department at the Hawthorne Works in 1918, industrial quality was limited to inspecting finished products and removing defective items. That all changed on May 16, 1924. Dr. Shewhart's boss, George D. Edwards, recalled: "Dr. Shewhart prepared a little memorandum only about a page in length. About a third of that page was given over to a simple diagram which we would all recognize today as a schematic control chart. That diagram, and the short text which preceded and followed it, set forth all of the essential principles and considerations which are involved in what we know today as process quality control."[1] Shewhart's work pointed out the importance of reducing variation in a manufacturing process and the understanding that continual process-adjustment in reaction to non-conformance actually increased variation and degraded quality. Shewhart framed the problem in terms of assignable-cause and chance-cause variation and introduced the control chart as a tool for distinguishing between the two. Shewhart stressed that bringing a production process into a state of statistical control, where there is only chance-cause variation, and keeping it in control, is necessary to predict future output and to manage a process economically. Dr. Shewhart created the basis for the control chart and the concept of a state of statistical control by carefully designed experiments. While Dr. Shewhart drew from pure mathematical statistical theories, he understood data from physical processes never produce a "normal distribution curve" (a Gaussian distribution, also commonly referred to as a "bell curve"). He discovered that observed variation in manufacturing data did not always behave the same way as data in nature (Brownian motion of particles). Dr. Shewhart concluded that while every process displays variation, some processes display controlled variation that is natural to the process, while others display uncontrolled variation that is not present in the process causal system at all times.[2] Shewhart worked to advance the thinking at Bell Telephone Laboratories from their foundation in 1925 until his retirement in 1956, publishing a series of papers in the Bell System Technical Journal. His work was summarized in his book Economic Control of Quality of Manufactured Product (1931). Shewhart’s charts were adopted by the American Society for Testing and Materials (ASTM) in 1933 and advocated to improve production during World War II in American War Standards Z1.1-1941, Z1.2-1941 and Z1.3-1942. Later work From the late 1930s onwards, Shewhart's interests expanded out from industrial quality to wider concerns in science and statistical inference. The title of his second book Statistical Method from the Viewpoint of Quality Control (1939) asks the audacious question: What can statistical practice, and science in general, learn from the experience of industrial quality control? Shewhart's approach to statistics was radically different from that of many of his contemporaries. He possessed a strong operationalist outlook, largely absorbed from the writings of pragmatist philosopher C. I. Lewis , and this influenced his statistical practice. In particular, he had read Lewis's Mind and the World Order many times. Though he lectured in England in 1932 under the sponsorship of Karl Pearson (another committed operationalist) his ideas attracted little enthusiasm within the English statistical tradition. The British Standards nominally based on his work, in fact, diverge on serious philosophical and methodological issues from his practice. His more conventional work led him to formulate the statistical idea of tolerance intervals and to propose his data presentation rules, which are listed below: Data have no meaning apart from their context. Data contain both signal and noise. To be able to extract information, one must separate the signal from the noise within the data. Walter Shewhart visited India in 1947-48 under the sponsorship of P. C. Mahalanobis of the Indian Statistical Institute. Shewhart toured the country, held conferences and stimulated interest in statistical quality control among Indian industrialists.[3] He died at Troy Hills, New Jersey in 1967. Influence In 1938 his work came to the attention of physicists W. Edwards Deming and Raymond T. Birge. The two had been deeply intrigued by the issue of measurement error in science and had published a landmark paper in Reviews of Modern Physics in 1934. On reading of Shewhart's insights, they wrote to the journal to wholly recast their approach in the terms that Shewhart advocated. The encounter began a long collaboration between Shewhart and Deming that involved work on productivity during World War II and Deming's championing of Shewhart's ideas in Japan from 1950 onwards. Deming developed some of Shewhart's methodological proposals around scientific inference and named his synthesis the Shewhart cycle. Achievements and honours In his obituary for the American Statistical Association, Deming wrote of Shewhart: As a man, he was gentle, genteel, never ruffled, never off his dignity. He knew disappointment and frustration, through failure of many writers in mathematical statistics to understand his point of view. He was founding editor of the Wiley Series in Mathematical Statistics, a role that he maintained for twenty years, always championing freedom of speech and confident to publish views at variance with his own. His honours included: Founding member, fellow and president of the Institute of Mathematical Statistics; Founding member, first honorary member and first Shewhart Medalist of the American Society for Quality; Fellow and President of the American Statistical Association; Fellow of the International Statistical Institute; Honorary fellow of the Royal Statistical Society; Holley medal of the American Society of Mechanical Engineers; Honorary Doctor of Science, Indian Statistical Institute, Calcutta. 2. Dr. W. Edwards Deming William Edwards Deming (October 14, 1900 – December 20, 1993) was an American statistician, professor, author, lecturer, and consultant. He is perhaps best known for his work in Japan. There, from 1950 onward, he taught top management how to improve design (and thus service), product quality, testing and sales (the last through global markets)[1] through various methods, including the application of statistical methods. Deming made a significant contribution to Japan's later reputation for innovative high-quality products and its economic power. He is regarded as having had more impact upon Japanese manufacturing and business than any other individual not of Japanese heritage. Despite being considered something of a hero in Japan, he was only just beginning to win widespread recognition in the U.S. at the time of his death.[2] Overview: Dr. Deming's teachings and philosophy can be seen through the results they produced when they were adopted by Japanese industry, as the following example shows: Ford Motor Company was simultaneously manufacturing a car model with transmissions made in Japan and the United States. Soon after the car model was on the market, Ford customers were requesting the model with Japanese transmission over the USA-made transmission, and they were willing to wait for the Japanese model. As both transmissions were made to the same specifications, Ford engineers could not understand the customer preference for the model with Japanese transmission. Finally, Ford engineers decided to take apart the two different transmissions. The American-made car parts were all within specified tolerance levels. On the other hand, the Japanese car parts were virtually identical to each other, and much closer to the nominal values for the parts - e.g., if a part were supposed to be one foot long, plus or minus 1/8 of an inch - then the Japanese parts were within 1/16 of an inch. This made the Japanese cars run more smoothly and customers experienced fewer problems. Engineers at Ford could not understand how this was done, until they met Deming. Deming received a BSc in electrical engineering from the University of Wyoming at Laramie (1921), an M.S. from the University of Colorado (1925), and a Ph.D. from Yale University (1928). Both graduate degrees were in mathematics and physics. Deming had an internship at Bell Telephone Laboratories while studying at Yale. He later worked at the U.S. Department of Agriculture and the Census Department. While working under Gen. Douglas MacArthur as a census consultant to the Japanese government, he famously taught statistical process control methods to Japanese business leaders, returning to Japan for many years to consult and to witness economic growth that he had predicted would come as a result of application of techniques learned from Walter Shewhart at Bell Laboratories. Later, he became a professor at New York University while engaged as an independent consultant in Washington, D.C.
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