A New Approach to the Assessment of the Analysis Method Accuracy

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Standardization is the activity of normalizing norms and rules which are in general obligatory for products, services and methods of measurement, control and testing. One of the main demands to the methods of analysis is to ensure a certain level of accuracy. Requirements for the analysis sequence and the accuracy of the measurement data are the result of a compromise between the consumer and the supplier of the analysis. It is suggested to use functional-target analysis in order to determine the relations between the properties and functions of the object. On the example of X-ray fluorescence analysis it is shown that it is possible to formulate the functions of the researched object and analyze the properties which are necessary to put these functions into practice. It allows for determining such indicators of the analytical method that can be assessed quantitatively. Such approach can be used to construct mathematical models to estimate the degree of accuracy required for solving specific problems of consumers of precise measurement information.

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454-458

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July 2017

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© 2017 Trans Tech Publications Ltd. All Rights Reserved

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[1] R.H. Allen, R.D.  Sriram, The role of standards in innovation, Technological Forecasting and Social Change. 64 (2–3) (2000) 171 – 181.

DOI: 10.1016/s0040-1625(99)00104-3

Google Scholar

[2] Yu. Sered, Y. Reich, Standardization and modularization driven by minimizing overall process effort, Journal Computer-Aided Design. 38 (5) (2006) 405-416.

DOI: 10.1016/j.cad.2005.11.005

Google Scholar

[3] M.B. Spring, Standards Management in the Twenty-First Century: Architectural Challenges and Management Opportunities, International Journal of Standardization Research. 14 (1) (2016) 34-44.

DOI: 10.4018/ijsr.2016010103

Google Scholar

[4] M.G. Filho, E.V. Saes, From time-based competition (TBC) to quick response manufacturing (QRM): the evolution of research aimed at lead time reduction, The International Journal of Advanced Manufacturing Technology. 64 (5) (2013) 1177–1191.

DOI: 10.1007/s00170-012-4064-9

Google Scholar

[5] R. Schmitt, S. Stiller, B. Falk, Introduction of a quality production theory for product realization processes, Enabling Manufacturing Competitiveness and Economic Sustainability. (2014) 309-314.

DOI: 10.1007/978-3-319-02054-9_52

Google Scholar

[6] Y. Klochkov, A. Gazizulina, Improvement of methodology of evaluation of efficiency of the metal-lurgical complex processes development, Key Engineering Materials. 684 (2016) 453 – 460.

DOI: 10.4028/www.scientific.net/kem.684.453

Google Scholar

[7] Y. Yao, L. Zhao, Y. Qin, Processing quality dynamic control based on quality state, Applied Mechanics and Materials. 37-38 (2010) 905-909.

DOI: 10.4028/www.scientific.net/amm.37-38.905

Google Scholar

[8] Z. Jiang, The intelligent quality control technology system based on the integration methods of SPC and EPC, Applied Mechanics and Materials. 263-266 (2013) 839-842.

DOI: 10.4028/www.scientific.net/amm.263-266.839

Google Scholar

[9] L. Jun, K. Shulin, L. Pengyu, The study of PNN quality control method based on genetic algorithm, Key Engineering Materials. 467-469 (2011) 2103-2108.

DOI: 10.4028/www.scientific.net/kem.467-469.2103

Google Scholar

[10] Z. Yu, J. Zhou, Quality control model for manufacturing process based on GQMM, Advanced Materials Research. 214 (2011) 612-617.

DOI: 10.4028/www.scientific.net/amr.214.612

Google Scholar

[11] Z. Sener, E.E. Karsak, A decision model for setting target levels in quality function deployment using non-linear programming-based fuzzy regression and optimization, International Journal of Advanced Manufacturing Technologies. 48 (2010).

DOI: 10.1007/s00170-009-2330-2

Google Scholar

[12] G. Rubin, M. Polyakova, M. Chukin, G. Gun Protipology - a new stage in the development of standardization of hardware production, Steel in Translation. 43 (10) (2013) 666 – 669.

DOI: 10.3103/s0967091213100094

Google Scholar

[13] G. Rubin, M. Polyakova, G. Gun Simulation of technological parameters changing with the satiation effect, Proceedings of the 2015 International Conference on Modeling, Simulation and Applied Mathematics. 122 (2015) 178 - 181.

DOI: 10.2991/msam-15.2015.40

Google Scholar