The Importance of Quality Control within the Relationship between the Quality Engineering and Taguchi Methodology

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Nowadays there is a strong relationship between the quality control and quality engineering in the modern advanced manufacturing. Quality engineering is an interdisciplinary science which is concerned with not only producing satisfactory products for customers but also reducing the total loss. Quality engineering involves engineering design, process operations, after-sales services, economics and statistics. Although the Taguchi Robust Design is the first concept comes to mind when thinking of quality engineering, the definition of this major has been used in different manners in the literature. There are also differences on the definition of the quality which has been made by experts. The aim of this study is to contribute to the literature to avoid deviations on definition of the concept of "Quality Engineering", which has not been defined yet by ISO - International Organization for Standardization. This study pointed out that the process of quality control is a part of on-line quality engineering rather than off-line phase and tries to ensure planned and/or improved values are satisfied during mass production.

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27-35

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February 2015

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[1] Sower E.V., Essentials of quality with cases and experiential exercises, NJ: John Wiley & Sons, Inc., (2011).

Google Scholar

[2] Robust design for quality engineering and Six Sigma. World Scientific Publishing Co. http: /www. worldscibooks. com/engineering/6655. html 1 1 Introduction to Quality Engineering. http: /search-pdf-files. com/pdf/2346025-product-1986-definition-characteristics-serice (accessed 24 February 2013).

Google Scholar

[3] Durakbasa M.N., Osanna P.H. Intelligent tolerancing and advanced metrology to support total quality management and modern industrial fabrication. International Journal 'Total Quality Management and Excelence', 2011 ( 39) (1): 27-31.

Google Scholar

[4] Feng Q., Kapur K. C., Quality Engineering: Control, Design and Optimization, Handbook of Performability Engineering, 2008, pp.171-186.

DOI: 10.1007/978-1-84800-131-2_13

Google Scholar

[5] Montgomery DC., Introduction to statistical quality control, 5th ed. New York: Wiley, (2005).

Google Scholar

[6] Crow K. Optimization and variation reduction in quality. McGraw Hill, (1991).

Google Scholar

[7] Weckenmann A., Hartmann W., Function-oriented method for the definition and verification of microstructured surfaces. Precision Engineering, (2013), 37(3), 684-693.

DOI: 10.1016/j.precisioneng.2013.01.013

Google Scholar

[8] Torng C-C, Chau C-Y., Liu H-R., Applying quality engineering technique to improve wastewater treatment. Journal of Industrial Technology, (1999); 15: 1-7.

Google Scholar

[9] Misra K. B., Quality Engineering and Management.

Google Scholar

[10] Thompson F., Logue S., An exploration of common student misconceptions in science, International Education Journal, 2006, 7(4), 553-559.

Google Scholar

[11] Taylor W.A., Optimization and variation reduction on quality, 1991, McGraw Hill, US.

Google Scholar

[12] Taguchi G, Chowdury S, Wu Y (2005) Taguchi's quality engineering handbook. ASI Consulting Group, Livonia, Michigan.

Google Scholar

[13] Kirby E. D., A parameter design study in a turning operation using the Taguchi method. The Technology Interface/Fall (2006).

Google Scholar

[14] Subulan K., Cakmakci M., A feasibility study using simulation-based optimization and Taguchi experimental design method for material handling-transfer system in the automobile industry. International Journal of Advanced Manufacturing Technology, (2012).

DOI: 10.1007/s00170-011-3514-0

Google Scholar

[15] Ross PJ (1989) Taguchi techniques for quality engineering, loss function, orthogonal experiments, parameter and tolerance design. McGraw Hill, New York.

Google Scholar

[16] Montgomery DC (2005) Design and Analysis of Experiments. Wiley, NJ.

Google Scholar

[17] Maghsoodloo S., Ozdemir G., Jordan V., Huang C-H. Strengths and Limitations of Taguchi's Contributions to Quality, Manufacturing, and Process Engineering. Journal of Mam~Jacturing Systems. (2004); 23(2) 73-126.

DOI: 10.1016/s0278-6125(05)00004-x

Google Scholar

[18] Taguchi G., Tsai S. -C., Quality Engineering (Taguchi Methods) For The Development Of Electronic Circuit Technology, IEEE Transactions on Reliability. Vol. 44, No. 2. 1995, 225-229.

DOI: 10.1109/24.387375

Google Scholar

[19] http: /www. efcog. org/wg/ism/docs/QE_Roles_and_Responsibilities_9-4-09. pdf, (accessed 06 May 2013).

Google Scholar

[20] De Mast J. Quality improvement from the viewpoint of statistical method. Quality and Reliability Engineering International. (2003); 19: 255-264.

DOI: 10.1002/qre.580

Google Scholar

[21] Juran J.M., Blanton Godfrey A., Juran's quality handbook, Fifth Edition, NY: McGraw-Hill Companies, (1999).

Google Scholar

[22] Subulan, K., Cakmakci, M. A feasibility study using simulation based optimization and Taguchi experimental design method for material handling - transfer system in the automobile industry, International Journal of Advanced Manufacturing Technology, (2012).

DOI: 10.1007/s00170-011-3514-0

Google Scholar

[23] Karasu, M.K., Cakmakci, M., Cakiroglu M. B., Ayva E., Demirel-Ortabas N., Improvement of Changeover Times via Taguchi Empowered SMED / Case Study on Injection Molding Production, Measurement, (2013) Measurement 47 (2014) 741–748.

DOI: 10.1016/j.measurement.2013.09.035

Google Scholar

[24] Dustin, J., Haas, P.E., QC Model Guidebook, ODOT Roadway engineering Unit, NE. http: /www. oregon. gov/ODOT/HWY/OPL/docs/SEOPL/qa_guidebook. pdf (accessed 22 October 2013).

Google Scholar

[25] Steve H.K., Some Misconceptions about Attribute Sampling Plans. Teaching Statistics. (2001); 23(3): 90-93.

DOI: 10.1111/1467-9639.00064

Google Scholar

[26] Chandrupatla, T.R., Quality Concepts, Cambridge University Press, 978-0-521-51522-1 - Quality and Reliability in Engineering http: /assets. cambridge. org/97805215/15221/excerpt/9780521515221_excerpt. pdf, (accessed 06 May 2013).

Google Scholar

[27] Winiwarter, W., Mangino, J., Ajavon, A-L. N., McCulloch, A., Quality Assurance / Quality Control and Verification, IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 1. (2006), General Guidance and Reporting.

Google Scholar

[28] Vlasceanu, L., Grünberg, L., Parlea, D., Quality Assurance and Accreditation: A Glossary of Basic Terms and Definitions, UNESCO (2007), ISBN 92‐{TTP}8208 9069‐{TTP}8208 186‐{TTP}8208 1.

Google Scholar

[29] Montgomery, D.C., Introduction to Statistical Quality Control, Sixth Edition, John Wiley & Sons, NJ, (2009).

Google Scholar

[30] Laurie, C.C. et al., Quality Control and Quality Assurance in Genotypic Data for Genome-Wide Association Studies, Genetic Epidemiology, Wiley-Liss, Inc., (2010).

Google Scholar

[31] Cakmakci, M., Durakbasa, M.N., Karasu, M.K., Bas, The Relationship Between the Quality Engineering and Taguchi Methodology, 11th International Symposium on Measurement and Quality Control, (2013), Cracow - Kielce, Poland.

DOI: 10.4028/www.scientific.net/kem.637.27

Google Scholar