Abstract
With the rapid growth of competition in the market, the companies have to guarantee customers a reliable, sustainable and quality proofing production system. In this paper we consider a KM framework that extracts “Six Sigma” knowledge on the basis of the data gathered from production facilities. The KM framework enables to assess the performance of a company’s production and quality system by sigma value. The result will help the company to select a new development strategy in order to increase the profitability and customer satisfaction. KM framework includes well known tools like PDM, ERP system, PDM-ERP middleware and DM. The core of our framework is the DM that combines production route card data, Faults Classification standard DOE-NE-STD-1004-92 and the data from FMEA table. The combination and application of different tools and methods in the general KM framework allows the data flow between different systems, analysis of production operation and the failures occurring in the production process.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Koch, R.: Living the 80/20 Way: Work Less, Worry Less, Succeed More, Enjoy More illustrated edition. Nicholas Brealey Publishing (2004)
Matzler, K., Hinterhuber, H.H.: How to make product development projects more successful by integrating Kano’s model of customer satisfaction into quality function deployment. Technovation 18(1), 25–38 (1998)
Gunasekaran, A.: Agile manufacturing: enablers and an implementation framework. Int. J. Prod. Res. 36(5), 1223–1247 (1998)
Lõun, K., Riives, J., Otto, T.: Evaluation of the operation expedience of technological resources in a manufacturing network. Estonian Journal of Engineering, 51–65 (2011)
Teece, D.J.: Capturing Value from Knowledge Assets. California Management Review 40(3), 55–79 (1998)
Becerra-Fernandez, I., Gonzalez, A., Sabherwal, R.: Knowledge Management. Pearson Education, Inc., Upper Saddle River (2004)
Davenport, T.H., De Long, D.W., Beers, M.C.: Successful Knowledge Management Projects. Sloan Management Review, 43–57 (1998)
O’Brien, J.A., Marakas, G.M.: Management Information Systems. The McGraw-Hill Companies, Inc. (2008)
Blake, I., Gerard, P.L.: The information system as a competitive weapon. Communications of the ACM - Special Section on Management of Information Systems 27(12), 1193–1201 (1984)
Saaksvuori, A., Immonen, A.: Product Lifecycle Management, 3rd edn. Springer, Heidelberg (2008)
Shevtshenko, E., Karaulova, T., Kramarenko, S., Wang, Y.: IDSS used as a framework for collaborative projects in conglomerate enterprises. Journal of Achievements in Materials and Manufacturing Engineering, 89–92 (2007)
PDM-ERP Middleware (December 2012), http://plmware.tesis.de/index.php?page=1043
Berson, A., Smith, S.J.: Data Warehousing, Data Mining & OLAP. McGraw Hill (1997)
Arnrich, B., Walter, J., Albert, A., Ennker, J., Ritter, H.: Data Mart based research in heart surgery: challenges and benefits, September 7-11. MedInfo, San Francisco (2004)
Wang, K.: Applying data mart to manufacturing: the nature and implications. Journal of Intelligent Manufacturing 18, 487–495 (2007)
Production Route Card (October 2012), http://www.enotes.com/american-scholar/q-and-a/what-meant-by-job-card-route-card-used-production-99397
Sharon, K.J.: Combing QFD and FMEA to optimize performance. ASQC Quality Congress 52, 564–575 (1998)
Mcdermott, R.E., Mikulak, R.J., Beauregard, M.R.: The basics of FMEA. Resources Engineering, Inc., USA (1996)
Stamatis, D.H.: Failure mode and effect analysis: FMEA from theory to execution, 2nd edn. ASQ Quality Press (2003)
DOE-NE-STD-1004-92, Root Cause Analysis Guidance Document, US (1992), http://www.everyspec.com/DOE/DOE+PUBS/DOE_NE_STD_1004_92_262 (November 2012)
Anbari, F.T.: Six Sigma Method and Its Applications in Project Management. In: Proceedings of the Project Management Institute Annual Seminars and Symposium, San Antonio, Texas. Project Management Institute, Newtown Square (2002)
Rancour, T., McCracken, M.: Applying six sigma methods for breakthrough safety performance, pp. 31–34. American Society of Safety Engineers (2000)
Antony, J.: Some pros and cons of Six Sigma: an academic perspective. The TQM Magazine 16(4), 303–306 (2004)
Sahno, J., Opik, R., Kostina, M., Paavel, M., Shevtshenko, E., Wang, Y.: Knowledge Management Framework for Production Route Selection in Manufacturing Enterprises. In: 8th International DAAAM Baltic Conference Industrial Engineering, pp. 567–572 (2012)
Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd edn. John Wiley & Sons, New York (2002)
Antony, J., Banuelas, R.: Key ingredients for the effective implementation of six sigma program. Measuring Business Excellence 6, 20–27 (2002)
Gregory, H.W.: Six Sigma for Business Leaders, 1st edn. Business Systems Solutions, Inc., USA (2004)
McClusky, R.: The Rise, fall, and revival of six sigma. Measuring Business Excellence 4, 6–17 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sahno, J., Sevtsenko, E., Karaulova, T. (2013). Knowledge Management Framework for Six Sigma Performance Level Assessment. In: Rocha, Á., Correia, A., Wilson, T., Stroetmann, K. (eds) Advances in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36981-0_25
Download citation
DOI: https://doi.org/10.1007/978-3-642-36981-0_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36980-3
Online ISBN: 978-3-642-36981-0
eBook Packages: EngineeringEngineering (R0)