Supporting Structure For Prioritizing And Assigning Six Sigma Software Projects Using Fuzzy Logic Topsis And Fuzzy Logic Expert System

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2020 by IJCTT Journal
Volume-68 Issue-2
Year of Publication : 2020
Authors : Dr.Chandrakanth G Pujari
DOI :  10.14445/22312803/IJCTT-V68I2P105

MLA

MLA Style:Dr.Chandrakanth G Pujari "Supporting Structure For Prioritizing And Assigning Six Sigma Software Projects Using Fuzzy Logic Topsis And Fuzzy Logic Expert System" International Journal of Computer Trends and Technology 68.2 (2020):25-33.

APA Style: Dr.Chandrakanth G Pujari (2020). Supporting Structure For Prioritizing And Assigning Six Sigma Software Projects Using Fuzzy Logic Topsis And Fuzzy Logic Expert System  International Journal of Computer Trends and Technology, 68(2),25-33.

Abstract
The software project selection process system can be encountered as the very important action in the success of six sigma software projects. Such a manner that prioritizing and assigning software projects to execute software development teams is recognized, the very important step in software process plentiful research studies has been under going into six sigma software project selection, no one has been concentrate on selecting and assigning software projects as an articulate process occurring simultaneously. In this concern, this paper presents a supporting structure for decision making choosing and allocating the six sigma software projects to execute software project development teams, the main important action of six sigma software project selection process are selected. Coming after, recognizing six sigma potential software projects in the small and medium scale industries. The fuzzy logic TOPSIS methodology is used to ranking them. Further, the strong effect and effort indices for every software projects are computed. After words fuzzy logic expert system is used to assigning the software projects to six sigma champions. Finally, a case study in the software organizations is presented and the supporting structure is discussed to illustrate its software developed application.

Reference
[1] Chandrakanth G Pujari and Dr. Seetharam K., “An Evaluation of Effectiveness of the Software Projects Developed Through Six Sigma Methodology”, American Journal of Mathematical and Management Sciences, 34(1) · January 2015-16
[2] Buglione, L., Trudel, S. (2010), “Guideline for sizing Agile projects with COSMIC”, In: Proceedings of the IWSM / MetriKon / Mensura 2010, Stuttgart, Germany
[3] Bhasin, S. (2011), “Performance of organizations treating lean as an ideology”, Business Process Management Journal, Vol. 17 No. 6, pp. 986-1011.
[4] Bergmiller, G.G. and McCright, P.R. (2009), “Parallel models for lean and green operations”, paper presented at Industrial Engineering Research Conference, Miami, FL.
[5] Furlan, A., Vinelli, A. and Dal Pont, G. (2011), “Complementory and lean manufacturing bundles: an empirical analysis”, International Journal of Operations & Production Management, Vol. 31 No. 8, pp. 835-850.
[6] George, M. ed. (2010), “The Lean Six Sigma Guide to Doing More with Less cost”, John Wiley & Sons, Hoboken,NJ
[7] Stone, K.B. (2012), “Four decades of lean: a systematic literature review”, International Journal of Lean Six Sigma, Vol. 3 No. 2, pp. 112-132.
[8] Vinodh, S. and Balaji, S. (2011), “Fuzzy logic based Leanness assessment and its decision support system”, International Journal of Production Research, Vol. 49, pp. 40-67.
[9] Zhang, Q., bbas, J., Zhu, X. and Shah, M. (2012), “Critical success factors for successful Lean Six Sigma implementation in Pakistan”, Interdisciplinary Journal of Contemporary Research in Business, Vol. 4 No.1, pp. 117-124.
[10] S.M. Kazemi, (16-18 July 2012). Six Sigma project selection by using a fuzzy multiple criteria decision making approach a case study in poly acryl corp. CIE42 proceedings, Cape Town, South Africa 2012 CIE & SAIIE.
[11] Snee, Ronald: Leading Six Sigma: A Step-by-Step Guide Based on Experience with GE and Other Six Sigma Companies, Financial Times Prentice Hall 2002
[12] Stone, K.B. (2012), “Four decades of lean: a systematic literature review”, ternational Journal of Lean Six Sigma, Vol. 3 No. 2, pp.112-132.
[13] Vinodh, S. and Balaji, S. (2011), “Fuzzy logic based Leanness assessment and its decision support system”, International Journal of Production Research, Vol. 49, pp. 40-67.
[14] Furlan, A., Vinelli, A. and Dal Pont, G. (2011), “Complementory and lean manufacturing bundles: an empiricalanalysis”, International Journal of Operations & Production Management, Vol. 31 No. 8, pp. 835-850.
[15] Maroofi, F. and Dehghan, S. (2012), “Performing lean manufacturing system in small and medium enterprises”, International Journal of Academic Research in Accounting, Finance and Management Sciences, Vol. 2 No. 3 pp. 156-163.
[16] Nordin, N., Deros, B.M. and AbdWahab, D. (2012), “A framework for managing change in lean manufacturing implementation”, International Journal of Services and Operations Management, Vol. 12 No. 1, pp. 101-117. [17] Stone, K.B. (2012), “Four decades of lean: a systematic literature review”, International Journal of Lean Six Sigma, Vol. 3 No. 2, pp. 112-132.
[18] Chandrakanth G Pujari and Dr. Seetharam K.,” Top Priority of Software Success Factor for Six Sigma Execution by a Fuzzy Hierarchical Process”, International Journal of Multimedia and Ubiquitous Engineering 9 (11), 171-180, 2014-15
[19] Chandrakanth G Pujari and Dr. Seetharam K.,”Evaluation for Defective Density in All the Right Places”, Indian journal of engineering, 2014, 11(26), 30-37
[20] Chandrakanth G Pujari and Dr. Seetharam K.”Ranking of Tools use, software logical complexity, Requirement volatility, Quality requirements, Efficiency Requirements in software development”, 2009 IEEE International Advance Computing Conference, DOI: 10.1109/IADCC.2009.4809258,Date Added to IEEE Xplore: 31 March 2009
[21] Chandrakanth G Pujari, “Software Information Flexibility for Lean Six sigma Software Development Using Multiple Regression Analysis”, Indian Journal of Engineering, 2017, 14(36), 95-107
[22] Chandrakanth G pujari, Dr.SeetharamK,”Investigating the Effects of Factors on Software Development”,International Journal of Computer Applications, vol. 1, issue 6, pp. 56-65, February 2010, 10.5120/142-261
[23] Chandrakanth G Pujari and Dr. SeetharamK.,Article: “Estimation of Growth Parameters for a Software Development”. International Journal of Computer Applications 35(12):38-42, December 2011.
[24] Chandrakanth G Pujari, Kavyashree N, Dr.Supriya M C ”Enhancement of Indian Software Quality Management Using Multi Criteria Objects and Six Sigma Methodology”, International Journal on Future Revolution in Computer Science & Communication Engineering ISSN: 2454-4248 Volume: 4 Issue: 4 806 – 81 2019.
[25] Chandrakanth G Pujari, Dr SeetharamK ,”Detection and valuation of major error trends of software projects using pareto principle and fuzzy model”, National journal on advances in computing & Management, vol 3 no. 2 october 2012.
[26] Chandrakanth G Pujari, Kavyashree N, Dr.Supriya M C, “Development of a Methodology for Software Small and Medium Scale Industries in the Selection of Suitable Lean Six Sigma Tools”, JASC: Journal of Applied Science and Computations Volume VI, Issue II, February/2019 ISSN NO: 1076-5131
[27] Chandrakanth G Pujari and Dr. Seetharam K, “Software Defects Identification Using Principles of Data Gathering and Pareto Analysis” ,DOI: 10.5176/2251-2217_SEA12.36, 2012
[28] Chandrakanth G Pujari and Dr. Seetharam K,” Software Defects Identification Using Principles of Data Gathering and Pareto Analysis”, DOI: 10.5176/2251-2217_SEA12.36 2012
[29] Chandrakanth G Pujari , “Modeling Software Project Defects With Fuzzy Logic Maps”, International Journal on Future Revolution in Computer Science & Communication Engineering ISSN: 2454-4248 Volume: 4 Issue: 4 103 – 107, IJFRCSCE | April 2018, Available @ http://www.ijfrcsce.org
[30] Chandrakanth G Pujari and Dr. Seetharam K,” Implementation of Multivariate Clustering Methods for Software Development”, https://www.bvicam.ac.in

Keywords
Six Sigma Project Selection, Fuzzy Logic Expert System, TOPSIS, Software Project Allocation, Multiple Criteria Decision Making