Quality Control in the Third Generation of ISO – New Quality Engineering for Biochemical Analysis –

Yasuo Iwaki

doi:10.20965/ijat.2014.p0062

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IJAT Vol.8 No.1 pp. 62-71

doi: 10.20965/ijat.2014.p0062

(2014)

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Quality Control in the Third Generation of ISO – New Quality Engineering for Biochemical Analysis –

Yasuo Iwaki

Chaos Applied Research Office, 4-55 Otabicho, Koga, Fushimiku, Kyoto 612-8493, Japan

Received:

August 10, 2013

Accepted:

November 1, 2013

Published:

January 5, 2014

Keywords:

QE, QC, QA, ISO-GUM, MCMC Inference

Abstract

Since the uncertainty of measurement data was becoming complicated, ISO-26000s of the third generation was created from the technical field of Quality Control (QC). QC engineering started the first generation of ISO-9000s. The second generation of ISO-14000s and the innovation has continued up to now with new the third generation of ISO-26000s. The first generation has established a critical reliance and an assurance. A Quality Assurance (QA) and Quality Reliance (QR) are problems utmost importance. The second generation has planned predication technology for QC. Further more Environment Assessment (EA) is important for the QA performance. Significant improvement is necessary better accuracy. Furthermore, performing management was adapted for EA. is represented by the International Organization for Standardization (ISO) and Environmental Protection Agencies (EPA). Many rules for QC are made by the related organization. The third generation established a timeframe for making it sustainable to deliver social responsibility inmarket dealings. This study considers the third generation for biochemical analysis, and the verification is performed in the calibration curve. The first generation and the second generation are standard and regulation in nature, whereas the third generation is mere guidance and do not mandatory.

Cite this article as:

Y. Iwaki, “Quality Control in the Third Generation of ISO – New Quality Engineering for Biochemical Analysis –,” Int. J. Automation Technol., Vol.8 No.1, pp. 62-71, 2014.

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References

[1] ISO-26000-2010, “Guidance of Social Responsibility.”
[2] P. Ghinato, “Quality control methods: Towards modern approaches through well established principles,” Total Quality Management, Vol.9, No.6, pp. 463-477, 1998.
[3] J. O. Westgard and S. A. Westgard, “Equivalent Quality Testing Versus Equivalent QC Procedures,” Medicare, Medicaid and CLIS program Fed Regist., Vol.16, pp. 3640-3714, Jan 24, 2003.
[4] P. Ghinato, “Quality control method: Towards modern approaches through well established principles” Total Quality Management, Vol.9, No.6, pp. 463-477, 1998.
[5] BIPM, IFCC, IEC, IUPAC, and OIML, “Guide to the Expression of Uncertainty,” ISBN92-67-10, 1995.
[6] PDCA From wikipedia, the free encyclopedia [last modified on June 23 2012]
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[14] K. Gregory, G. Bibbo, and J. E. Pattson, “A standard approach to measurement uncertainties for scientists and engineers in medical,” Australasian Physical and Engineering Sciences in Medicine, Vol.28, No.2, 2005.
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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] ISO-26000-2010, “Guidance of Social Responsibility.”

[2] [2] P. Ghinato, “Quality control methods: Towards modern approaches through well established principles,” Total Quality Management, Vol.9, No.6, pp. 463-477, 1998.

[3] [3] J. O. Westgard and S. A. Westgard, “Equivalent Quality Testing Versus Equivalent QC Procedures,” Medicare, Medicaid and CLIS program Fed Regist., Vol.16, pp. 3640-3714, Jan 24, 2003.

[4] [4] P. Ghinato, “Quality control method: Towards modern approaches through well established principles” Total Quality Management, Vol.9, No.6, pp. 463-477, 1998.

[5] [5] BIPM, IFCC, IEC, IUPAC, and OIML, “Guide to the Expression of Uncertainty,” ISBN92-67-10, 1995.

[6] [6] PDCA From wikipedia, the free encyclopedia [last modified on June 23 2012]

[7] [7] J. Fremandez-Villaverde, P. A. Guerron-Quintana, and J. Rubio-Ramriez, “Estimating dynamic Equilibrium Model with Stochastic Volatility,” NBER working paper No.18399, September 2012.

[8] [8] M. W. Brandt and C. S. Jones “Bayesian rang-based estimation of stochastic volatility model,” Finance Research Letters, No.2, pp. 201-209, 2005.

[9] [9] J. Besag, “Markov Chain Monte Carlo for Statistical Inference,” Center for statistics and the social Sciences working paper No.9, April 2001.

[10] [10] GLUE (uncertainty assessment) from wikipedia, the free encyclopedia [last modified on June 23 2012]

[11] [11] A. Mikusheva, “MCMC: Gibbs Sampling,” Time Series Analysis, Fall 2007.

[12] [12] Stochastic volatility, from wikipedia, the free encyclopedia [last modified on March 15 2013]

[13] [13] P. Fotwies, “Method for calculating the coverage factor in calibration,” OINL Bulletin XL111, No.4, October 2002.

[14] [14] K. Gregory, G. Bibbo, and J. E. Pattson, “A standard approach to measurement uncertainties for scientists and engineers in medical,” Australasian Physical and Engineering Sciences in Medicine, Vol.28, No.2, 2005.

[15] [15] L. Tang and S. Willi, “Uncertainty calculation in analysis chemistry,” Clinical Metrology INNS, URCC, February 2001.

[16] [16] Pareto analysis, from wikipedia, the free encyclopedia [last modified on May 28 2013]

[17] [17] K. Gregory, G. Bibbo, and J. E. Pattison “A standard approach to measurement uncertainties for scientists and engineers in medicine,” Australasian Physical & Engineering Sciences in Medicine, Vol.28, No.2, 2005.

[18] [18] ISO Handbook, “statistical methods for quality control,” Vol.1.

[19] [19] Abel. J. Biological effect of low doses of ionizing radiation, IAEA BULLETIN 4, 1994.