By Rassoul Noorossana
A exceptional presentation of the main achievements in statistical profile tracking methods
Statistical profile tracking is a space of statistical qc that's becoming in value for researchers and practitioners, in particular due to its variety of applicability throughout a variety of carrier and production settings. made from contributions from popular academicians and practitioners within the box, Statistical research of Profile Monitoring offers the newest state of the art learn at the use of keep watch over charts to observe strategy and product caliber profiles. The publication offers complete insurance of profile tracking definitions, recommendations, versions, and alertness examples, fairly in a variety of parts of engineering and statistics.
The ebook starts with an creation to the concept that of profile tracking and its functions in perform. next chapters discover the basic suggestions, equipment, and concerns on the topic of statistical profile tracking, with subject matters of assurance including:
- Simple and a number of linear profiles
- Binary reaction profiles
- Parametric and nonparametric nonlinear profiles
- Multivariate linear profiles monitoring
- Statistical strategy keep watch over for geometric specifications
- Correlation and autocorrelation in profiles
- Nonparametric profile monitoring
Throughout the booklet, greater than dozen real-world case experiences spotlight the mentioned issues in addition to cutting edge examples and functions of profile tracking. Statistical research of Profile Monitoring is a wonderful booklet for classes on statistical quality controls on the graduate point. It additionally serves as a beneficial reference for caliber engineers, researchers and somebody who works in tracking and bettering statistical processes.
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Extra info for Statistical Analysis of Profile Monitoring (Wiley Series in Probability and Statistics)
1982) Measurement assurance for dimensional measurements on integrated-circuit photomasks. NBS Technical Note 1164, US Department of Commerce, Washington, DC, USA. Deming, W. E. (1982) Out of The Crisis, MIT Press, Cambridge. Gardner, M. , Lu, J. , Gyurcsik, R. , Wortman, J. , Hornung, B. , Heinisch, H. , Rying, E. , Davis, J. , and Mozumder, P. K. (1997) Equipment fault detection using spatial signatures. IEEE Transactions on Components, Packaging, and Manufacturing Technology—Part C, 20, 295–304.
And Chen, J. J. (1997) Multipoint dissolution specification and acceptance sampling rule based on profile modeling and principal component analysis. Journal of Biopharmaceutical Statistics, 7(3), 423–439. Walker, E. and Wright, S. P. (2002) Comparing curves using additive models. Journal of Quality Technology, 34, 118–129. Woodall, W. H. (2007) Current research on profile monitoring. Revista Produc˜ao, 17(3), 420–425. Woodall, W. , Spitzner, D. , Montgomery, D. , and Gupta, S. (2004) Using control charts to monitor process and product quality profiles.
M. In most of the work done in the area of simple linear profile monitoring, it was assumed that the X-values are fixed and take the same set of values for each sample. This is usually the case in the calibration applications. If the X-values are random, then under certain conditions one can simply modify the corresponding formulas to account for the varying X-values from sample to sample. For example, Neter et al. (1990, pp. 86–87) stated that the conditional distribution of Y | X must meet the simple linear regression assumptions with the probability distribution of X not dependent on any of the parameters in the regression model.
Statistical Analysis of Profile Monitoring (Wiley Series in Probability and Statistics) by Rassoul Noorossana