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IJSTR >> Volume 3- Issue 2, February 2014 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Problem Solving Management Using Six Sigma Tools & Techniques

[Full Text]

 

AUTHOR(S)

Mallikarjun Koripadu, K. Venkata Subbaiah

 

KEYWORDS

Index Terms: Lean, Six Sigma, Process Quality Control, Fishbone, Pareto, Why-why analysis, problem solving.

 

ABSTRACT

Abstract: Problem Management is one of the most important process areas in today’s service sectors (e.g. IT, Healthcare, and Non IT business) apart from production & manufacturing sectors. Problem management ensures to streamline and identify the root causes (main reasons) and provide permanent and temporary solutions to recurring incidents there by reducing the infrastructure downtime/productivity loss. Proactive problem solving management can eliminate reducing incidents from occurring. However, many times due to improper usage or not using any tools and techniques of problem management is ineffective. This paper explains how Lean and six sigma tools and techniques can be effectively used for doing a proactive problem solving management with higher benefits along with improved efficiency and effectiveness. In this paper one IT IS environment of incident management problem has been resolved using problem solving management tools.

 

REFERENCES

[1] http://fishbonediagram.org/limitations/

[2] http://www.processexcellencenetwork.com/six-sigma-quality/articles/the-fishbone-diagram-and-the-reverse-fishbone-diag/

[3] http://project-management.learningtree.com/tag/fishbone-diagram/

[4] http://project-management.learningtree.com/2011/10/11/pareto-analysis-and-the-8020-rule/

[5] http://www.spcconsulting.org/2012/06/6sigma-tools-pareto-analysis/

[6] http://www.mt-online.com/january2005/using-pareto-analysis-to-focus-reliability-improvements

[7] https://www.moresteam.com/toolbox/5-why-analysis.cfm

[8] http://www.iwise2.com/why-why-analysisJ.S. Bridle, “Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition,” Neurocomputing—Algorithms, Architectures and Applications, F. Fogelman-Soulie and J. Herault, eds., NATO ASI Series F68, Berlin: Springer-Verlag, pp. 227-236, 1989. (Book style with paper title and editor)