Wayne Nelson (statistician)

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For the American musician, see Wayne Nelson.

Wayne Nelson is an American statistician. His main contributions to the reliability theory are the Nelson-Aalen Estimator for lifetime data, various statistical procedures for accelerated life testing and both: nonparametric and parametric procedures for recurrent data analysis.

Contents

Early life and education

Nelson was born in Chicago in 1936. He studied Physics at Caltech and graduated with a Bachelor of Science in 1958. Nelson obtained a Master of Science in Physics from the University of Illinois in 1959, then a Ph.D. in statistics from the same university in 1965. [1]

Career

Nelson was employed from 1965 to 1989 at General Electric R&D. [2] He was also an adjunct professor teaching graduate courses on applications of statistics at Union College and Rensselaer Polytechnic Institute. [1] Currently, Nelson works as a private consultant and legal expert witness in statistical analysis and modeling of data in many industries; including automotive, aviation, electric power, electronics, materials, medical devices, microelectronics, military hardware, nuclear power, railroad, software, and transportation. [2]

Work

His research work focuses on collecting and analyzing reliability data, laboratory tests, accelerated tests, quality control, measurement error analysis, planned experiments, sampling, and data analysis. Nelson worked with Odd Aalen on constructing the Nelson Aalen estimator., [3] [4] [5] a non-parametric approximation of the cumulative hazard function that can account for both failure and censored data. He also developed a method to estimate Weibull distribution (with few or no failures) for products with evolutionary design (same shape parameter β). [6] In the late 1960s, Wayne developed a cumulative hazard analysis method for nonparametric estimation of a population's cumulative life distribution. The resulting estimate is most conveniently displayed and interpreted on a probability plot. Until Wayne developed his method practitioners relied on crude approximations for such analyses. Wayne’s paper "Hazard Plotting for Incomplete Failure Data" [3] in the inaugural issue of the J. of Quality technology received the Brumbaugh Award for the ASQ as the 1969 [7] paper that made a great contribution to the development of industrial applications of quality control. Moreover, his paper "Theory and Applications of Hazard Plotting for Censored Failure Data" was reprinted in the 40th Anniversary issue of Technometrics (2000) [8] as one of the "Two Classics in Reliability Theory." Dr. Wayne also developed software that is widely used in reliability analysis; STATPAC is the first complete package for analysis of reliability and accelerated test data, including censored and interval data. It was the first to provide probability plots, confidence limits, maximum likelihood fitting of many models including accelerated life test models, proper analysis of step-stress data, residuals and their analyses, and a simple user interface. Its versatile reliability features stimulated imitations in SPLUS, SAS, JMP, ReliaSoft, WinSmith, and others. [9] Also, POWNOR, a software that fits the power-(log)normal distribution to censored life data on specimens of differing sizes. This was developed on his NSF-NIST-ASA senior research fellowship at NIST to develop better statistical models for electromigration failures of microcircuits. [10]

Selected publications

Books

Papers

Awards

Related Research Articles

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<span class="mw-page-title-main">Failure mode and effects analysis</span> Analysis of potential system failures

Failure mode and effects analysis is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet. There are numerous variations of such worksheets. An FMEA can be a qualitative analysis, but may be put on a quantitative basis when mathematical failure rate models are combined with a statistical failure mode ratio database. It was one of the first highly structured, systematic techniques for failure analysis. It was developed by reliability engineers in the late 1950s to study problems that might arise from malfunctions of military systems. An FMEA is often the first step of a system reliability study.

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Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability describes the ability of a system or component to function under stated conditions for a specified period. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time.

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<span class="mw-page-title-main">Kaplan–Meier estimator</span> Non-parametric statistic used to estimate the survival function

The Kaplan–Meier estimator, also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data. In medical research, it is often used to measure the fraction of patients living for a certain amount of time after treatment. In other fields, Kaplan–Meier estimators may be used to measure the length of time people remain unemployed after a job loss, the time-to-failure of machine parts, or how long fleshy fruits remain on plants before they are removed by frugivores. The estimator is named after Edward L. Kaplan and Paul Meier, who each submitted similar manuscripts to the Journal of the American Statistical Association. The journal editor, John Tukey, convinced them to combine their work into one paper, which has been cited more than 34,000 times since its publication in 1958.

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Accelerated life testing is the process of testing a product by subjecting it to conditions in excess of its normal service parameters in an effort to uncover faults and potential modes of failure in a short amount of time. By analyzing the product's response to such tests, engineers can make predictions about the service life and maintenance intervals of a product.

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<span class="mw-page-title-main">Roy Billinton</span>

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References

  1. 1 2 "Wayne Nelson Biography".
  2. 1 2 Rodgers, Tim (January 2017). "Wayne Nelson Interview".
  3. 1 2 Nelson, W. (1969). "Hazard plotting for incomplete failure data". Journal of Quality Technology. 1: 27–52. doi:10.1080/00224065.1969.11980344.
  4. Nelson, W. (1972). "Theory and applications of hazard plotting for censored failure data". Technometrics. 14 (4): 945–965. doi:10.1080/00401706.1972.10488991.
  5. Aalen, Odd (1978). "Nonparametric inference for a family of counting processes". Annals of Statistics. 6 (4): 701–726. doi: 10.1214/aos/1176344247 . JSTOR   2958850.
  6. Nelson, Wayne (1985). "Weibull Analysis of Reliability Data with Few or No Failures". Journal of Quality Technology. 17 (3): 140–146. doi:10.1080/00224065.1985.11978953.
  7. 1 2 "BRUMBAUGH AWARD WINNERS".
  8. Nelson, W. (2000). "Theory and applications of hazard plotting for censored failure data". Technometrics. 42 (1, Special 40th Anniversary): 12–25. doi:10.2307/1271428. JSTOR   1271428.
  9. Meeker, William; Escobar, Luis (August 2001). "Software for Reliability Data Analysis and Test Planning". Iowa State University - Digital Repository: 5.
  10. Nelson, Wayne; Dognanksoy, Necip (February 2017). "A Computer Program POWNOR for Fitting the Power-Normal and -Lognormal Models to Life or Strength Data from Specimens of Various Sizes" (PDF). NISTIR 4760 (National Bureau of Standards).{{cite journal}}: Cite journal requires |journal= (help)
  11. "Fulbright Scholar Directory".
  12. "SHEWHART MEDALISTS".
  13. "WAYNE NELSON Receives Lifetime Achievement Award" (PDF). Summer_Current_Source_Newsletter. IEEE. Summer 2005.
  14. "SHAININ MEDALISTS".
  15. "Gerald J. Hahn Q&P Achievement Award".