Walter A. Shewhart
Walter Andrew Shewhart (pronounced like "Shoe-heart",
March 18,
1891 -
March 11,
1967) was a
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.Born
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.
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 Hawthorne 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 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."
[ Western Electric - A Brief History] 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.
["Why SPC?" British Deming Association SPC Press, Inc. 1992]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 summarised 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.
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 has no meaning apart from its context.#Data contains 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.
["A BRIEF HISTORY OF THE INDIAN STATISTICAL INSTITUTE"]He died at
Troy Hills, New Jersey in
1967.
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.
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 Control;
* 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.
Both pure and applied science have gradually pushed further and further the requirements for accuracy and precision. However, applied science, particularly in the mass production of interchangeable parts, is even more exacting than pure science in certain matters of accuracy and precision.
[Shewhart, Walter A. Statistical Method from the Viewpoint of Quality Control]Progress in modifying our concept of control has been and will becomparatively slow. In the first place, it requires the application of certainmodern physical concepts; and in the second place it requires the applicationof statistical methods which up to the present time have been for the most partleft undisturbed in the journal in which they appeared.
[Shewhart, Walter A. Economic Control of Quality of Manufactured Product]Shewhart's propositions
[Shewhart, Walter A. Economic Control of Quality of Manufactured Product]1. All chance systems of causes are not alike in the sense that they enable usto predict the future in terms of the past.
2. Constant systems of chance causes do exist in nature.
3. Assignable causes of variation may be found and eliminated.Based upon evidence such as already presented, it appears feasible to set upcriteria by which to determine when assignable causes of variation in qualityhave been eliminated so that the product may then be considered to becontrolled within limits. This state of control appears to be, in general, a kind of limit to which we may expect to go economically in finding and removingcauses of variability without changing a major portion of the manufacturingprocess as, for example, would be involved in the substitution of new materials or designs.
[Shewhart, Walter A. Economic Control of Quality of Manufactured Product]The definition of random in terms of a physical operation is notoriouslywithout effect on the mathematical operations of statistical theory because sofar as these mathematical operations are concerned random is purely and simply an undefined term. The formal and abstract mathematical theory has anindependent and sometimes lonely existence of its own. But when an undefinedmathematical term such as random is given a definite operational meaning inphysical terms, it takes on empirical and practical significance. Everymathematical theorem involving this mathematically undefined concept canthen be given the following predictive form: If you do so and so, then such and such will happen.
[Shewhart, Walter A. Statistical Method from the Viewpoint of Quality Control]Every sentence in order to have definite scientific meaning must be practicallyor at least theoretically verifiable as either true or false upon the basis ofexperimental measurements either practically or theoretically obtainable bycarrying out a definite and previously specified operation in the future. Themeaning of such a sentence is the method of its verification.
[Shewhart, Walter A. Statistical Method from the Viewpoint of Quality Control]In other words, the fact that the criterion we happen to use has a fine ancestry of highbrow statistical theorems does not justify its use. Such justification must come from empirical evidence that it works.
[Shewhart, Walter A. Economic Control of Quality of Manufactured Product]Presentation of Data depends on the intended actions
[Shewhart, Walter A. Statistical Method from the Viewpoint of Quality Control]Rule 1. Original data should be presented in a way that will preserve theevidence in the original data for all the predictions assumed to be useful.
Rule 2. Any summary of a distribution of numbers in terms of symmetricfunctions should not give an objective degree of belief in any one of theinferences or predictions to be made therefrom that would cause humanaction significantly different from what this action would be if theoriginal distributions had been taken as evidence.
*
Control chart*
Common cause and special cause*
Analytic and enumerative statistical studies
*
Economic Control of Quality of Manufactured Product (
1931) ISBN 73890760
*
Statistical Method from the Viewpoint of Quality Control (
1939) ISBN 0486652327
* Deming, W. Edwards (1967) Walter A. Shewhart, 1891-1967,
American Statistician, Vol. 21, No. 2. (Apr., 1967), pp. 39-40.
* Bayart, D. (2001) Walter Andrew Shewhart,
Statisticians of the Centuries (ed. C. C. Heyde and E. Seneta) pp. 398-401. New York: Springer.
* Fagen, M D (
ed.) (1975)
A History of Engineering and Science in the Bell System: The Early Years (1875-1925)* Fagen, M D (
ed.) (1978)
A History of Engineering and Science in the Bell System: National Service in War and Peace (1925-1975) ISBN 0932764002
*Wheeler, Donald J. (1999).
Understanding Variation: The Key to Managing Chaos - 2nd Edition. SPC Press, Inc. ISBN 0945320531.
*
ASQ Shewhart page*
Quality GurusThere is another photograph of Shewhart at
*
Walter A Shewhart on the
Portraits of Statisticians page.
