Improving Quality of Statistical Process Control by Dealing with Non-Normal Data in Automotive Industry

• Autorzy: Zuzana Andrássyová , Tomáš Pauliček , Pavol Pichňa , Martin Kotus , Maria del Carmen Bas Cerdá

Warianty tytułu

Test statystyczny sprawozdający hipotezę dobroci Pearsona

• Języki publikacji: EN

Abstrakty

EN

Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability) although, there are constantly more approaches to non-normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation -S/R) individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution) therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes. (original abstract)

W artykule przedstawiono analizę danych, która to poprawia jakość stosowanych narzędzi statystycznych w procesach montażu siedzeń samochodowych.

Słowa kluczowe

EN

Hypothesis testing; Quality inspection; Statistical methods for quality control; Probability distributions; Data processing

PL

Testowanie hipotez; Kontrola jakości; Statystyczne metody kontroli jakości; Rozkład prawdopodobieństwa; Przetwarzanie danych

• Czasopismo: Management Systems in Production Engineering
• Rocznik: 2012
• Tom: 3(7)
• Strony: 26--30

Twórcy

autor

Zuzana Andrássyová

• Slovak Agricultural University in Nitra

autor

Tomáš Pauliček

• Slovak Agricultural University in Nitra

autor

Pavol Pichňa

• Slovak Agricultural University in Nitra

autor

Martin Kotus

• Slovak Agricultural University in Nitra

autor

Maria del Carmen Bas Cerdá

• Universidad Politécnica de Valencia, Spain

Bibliografia

• Haridy S., Wua Z., Castagliola P.: Univariate and multivariate approaches for evaluating the capability of dynamic-behaviour processes. Statistical Methodology. Vol. 8, Issue 2, 2011, pp 185-203.
• Sherman J. P.: Tips for Recognizing and Transforming Non-normal Data. iSixSigma. http://www.isixsigma.com/ tools-templates/normality/tips-recognizing-andtransforming-non-normal-data/ (23.03. 2012).
• Osborne J.: Notes on the use of data transformations. Practical Assessment, Research & Evaluation. Vol. 8, Issue 6, 2002. http://PAREonline.net/getvn.asp?v=8&n=6 (25.03.2012).
• STN ISO 8258: 1995 (010271) Shewhart control charts. SR: Slovak Standards Institute (SUTN). 1995.
• Johnson L.: Modelling non-normal data using statistical software. Process control and process capability can now be modelled using non-normal distributions. R&D Magazine. http://rdmag.com/Featured-Articles/2007/08/Modeling-Non-Normal-Data-Using-Statistical-Software/ (26.03.2012).
• Osborne, J.: Improving your data transformations: Applying the Box-Cox transformation. Practical Assessment, Research & Evaluation. Vol. 15, Issue 12, 2010. http://pareonline.net/pdf/v15n12.pdf (18.05.2012).