INFORMATION CHANGE THE WORLD

International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.10, No.9, Sep. 2018

Optimization of Process Parameters Using Grey-Taguchi Method for Software Effort Estimation of Software Project

Full Text (PDF, 757KB), PP.10-16


Views:43   Downloads:2

Author(s)

M.Padmaja, D. Haritha

Index Terms

Taguchi method;Grey Relational Analysis;Orthogonal Array;Signal to Noise Ratio;ANOVA;Optimization

Abstract

Optimization is one of the techniques used in the estimation of projects to obtain the optimal parameter sequence at different levels for the best project conditions, such as size, duration and function points. In this paper, to select the significant process parameter sequence at different levels, a combination of Grey Relational Analysis (GRA) and Taguchi method applied during the estimation. This parameter sequence is essential for the industries in producing quality product at a lower cost. Taguchi method is used to improve the product quality and reduce the cost. Among the various methods of Taguchi as a standard Orthogonal Array (OA) produces better parameters to be considered at different levels. This paper uses L16 Orthogonal Array (OA) whose efficiency is proven in the experimental results. Here, a variant of GRA, GRG has been used to assign grades for projects in the dataset. Finally, the optimized process parameter sequence at different levels is obtained through the application of GRG over L16 Orthogonal Array (OA). In this paper, Grey-Taguchi method is implemented to find out the levels of software process parameters such as Duration, KSLOC, Adjustment Function Points and Raw Function Points necessary for minimizing software effort. Experimental results show that parameter levels suggested by Grey-Taguchi method result in improved GRG, which results in better software effort estimation.

Cite This Paper

M.Padmaja, D. Haritha, " Optimization of Process Parameters Using Grey-Taguchi Method for Software Effort Estimation of Software Project", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.10, No.9, pp. 10-16, 2018.DOI: 10.5815/ijigsp.2018.09.02

Reference

[1]Madhav S. Phadke. (1989): Quality engineering using robust design. Prentice Hall, New Jersy.

[2]Deng. J (1989): Introduction to grey system. Journal of Grey System, Vol.1 No.1, pp. 1-24.

[3]Lin. Yi, Liu. Sifeng (2004): A Historical Introduction to Grey Systems Theory. IEEE International Conference on Systems, Man and Cybernetics.

[4]Taguchi.G (1990): Introduction to quality engineering. Asian Productivity Organization, Tokyo.

[5]Genichi Taguchi, Subir Chowdhury, Yuin Wu (2005): Taguchi’s Quality Engineering Handbook. John Wiley & Sons, Inc.

[6]A.S.Hedayat, N.J.A.Sloane, John Stufken (1999): Orthogonal Arrays- Theory and Applications. Springer series in statistics.

[7]Qinbao Song, Martin Shepperd and Carolyn Mair. (2005): Using Grey Relational Analysis to Predict Software Effort with Small Data Set. 11th IEEE International Software Metrics Symposium (METRICS 2005).

[8]Sun-Jen Huang, Nan-Hsing Chiu, Li-Wei Chen. (2008):  Integration of the grey relational analysis with genetic algorithm for software effort estimation. Science Direct, European Journal of Operational Research, pp. 898–909.

[9]Geeta Nagpal, Moin Uddin, Arvinder Kaur (2014): Grey relational effort analysis technique using robust regression methods for individual projects. Int. J. Computational Intelligence Studies. Vol. 3, No. 1.

[10]M.Padmaja, Dr D. Haritha (2017): Software Effort Estimation using Grey Relational Analysis, MECS in International Journal of Information Technology and Computer Science, 2017

[11]Bose, G. K, Mitra, S. (2013): Study of ECG process while machining AI2O3 / AI – IPC using grey – Taguchi methodology. Advances in production Engineering and Management (APEM) journal, Vol. 8, No. 1, pp. 41-51.

[12]P. C. Mishra, D. K. Das, M. Ukamanal, B. C. Routara and A. K. Sahoo (2015): Multi-response optimization of process parameters using Taguchi method and grey relational analysis during turning AA 7075/SiC composite in dry and spray cooling environments. International Journal of Industrial Engineering Computations. Pp. 445–456.

[13]Saikat Kumar Kuila, Goutam Kumar Bose (2015): Process Parameters Optimization of Aluminium by Grey –Taguchi Methodology during AWJM Process. International Journal of Innovative Research in Science, Engineering and Technology. Volume 4, Special Issue 9.

[14]Sumit Raj, Dr. Kaushik Kumar (2015): Application of Grey-Taguchi Technique for Optimization of Overcut and Surface Roughness in Die Sinking Electro-Discharge Machining of EN45 Material. International Journal of Applied Engineering Research. ISSN 0973-4562 Vol. 10 No.55.

[15]Raghuraman S, Thiruppathi K, Panneerselvam T and Santosh S (2013): Optimization of EDM Parameters Using Taguchi Method and Grey Relational Analysis for Mild Steel IS 2026. International Journal of Innovative Research in Science, Engineering and Technology. Vol. 2, Issue 7.

[16]V.Chittaranjan Das, N.V.V.S.Sudheer (2014): Optimization of Multiple Performance Characteristics of the Electrical Discharge Machining Process on Metal Matrix Composite (Al/5%Ticp) using Grey Relational Analysis. 5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014).

[17]Mihir Thakorbhai Patel (2015): Multi Objective Optimization of Machining Parameters during Turning of E250B0 of Standard Is: 2062 Material using Grey Relation Analysis. International Journal of Advanced Research in Engineering and Applied Sciences. Vol. 4, No. 6.  ISSN: 2278-6252.

[18]Ugur Esme (2010): Use of Grey Based Taguchi Method in Ball Burnishing Process for the Optimization of Surface Roughness and Micro Hardness of AA7075 Aluminum Alloy.  MTAEC 9. pp. 129–135.

[19]M.Padmaja, Dr D. Haritha (2017): Software Effort Estimation using Meta Heuristic Algorithm, International Journal of Advanced Research in Computer Science, 8 (5), May-June 2017,196-201

[20]M.Padmaja, Dr D. Haritha (2018): Software Effort Estimation using Grey Relational Analysis with K-Means Clustering, 4th International Conference on Information System Design and Intelligent Applications (INDIA - 2017) 15th - 17th, June, 2017 Duy Tan University, 3 Quang Trung, Da Nang, VietNam, published by Springer AISC Series, March 2018