THE EVALUATION OF QUALUTY GOALS AT THE PROCESS LEVEL IN AN UNCERTAIN ENVIRONMENT
Abstract
Improvement of business processes is achieved, among the other, through improvement of quality goals which are defined on the level of each process. In practice, it is not possible to improve all identified quality goals simultaneously. It is assumed that it is necessary that the quality goals values be determined by applying determined metrics. With respect to given values of quality goals, management team determines the order by which quality goals are improved. In this paper, the relative importance of quality goals are stated by fuzzy pair-wise comparison matrix. The performances of quality goals are described by linguistic expressions. All linguistic expressions are modelled by triangular fuzzy numbers. The new model for evaluation of quality goal values with respect to their relative importance is proposed. The developed model is tested by illustrative example with real life data of development process.3.
Keywords: quality goals, fuzzy sets, evaluation
References
Bass, M.S., Kwakernaak, H. (1977). Rating and Ranking of Multiple-aspect Alternatives using Fuzzy sets. Automatica, 3, 47-58.
Chan, S.T.F., Kumar, N. (2007). Global supplier development considering risk factors using fuzzy extended AHP-based approach. Int. Journal of Production Research, 46, 417-431.
Chang, D.Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95, 649-655.
Chiwoon C., Seungsin, L. (2010) A study on process evaluation and selection model for business process management. School of Industrial Engineering, University of Ulsan, Ulsan 680-749.
Gaben. M., Krčevinac. S., Vujošević. M. (2007): Modelujući sistemi u optimizaciji. Journal of Applied Engineering Science, No.18, pp. 37-46.
Gumus, T.A. (2009). Evaluation of hazardous waste transportation fi rms by using a two step fuzzy-AHP and TOPSIS methodology. Expert System with Applications, 36, 4067-4074.
Kaur, P., Chakrabortyb, S. (2007). A New Approach to Vendor Selection Problem with Impact Factor as an Indirect Measure of Quality. Journal of Modern Mathematics and Statistics, 1, 1-8.
Klir, G.J., Folger, T.A. (1988) Fuzzy Sets, Uncertainty and Information (1st ed.). New Yersy: Prentice-Hall.
Klir G.J., Yuan, B. (1995) Fuzzy sets and fuzzy logic, theory and applications. Prentice Hall. New Jersey.
Kwong, C.K., Bai, H. (2003). Determining the importance weights for the customer requirements in QFD using a fuzzy AHP with an extent analysis approach. IIE Transakcions, 35
(7), 619-625.
Lootsma, F.A. (1997) Fuzzy Logic for Planning and Decision making. Kluwer Academic, Boston, USA.
Milanović, D., Ranđić. D., Ristić. Lj.(2007): Unapređenje sistema upravljanja životne sredine po standardima ISO14000, Journal of Applied Engineering Science, No. 18, pp. 7-12.
Milosavljević, Đ. (2003): “Unapređenje sistema upravljanja životne sredine po standardima” Journal of Applied Engineering Science, Vol. 1, No. 1, pp. 41-48.
Misita. M., Senussia. G., Milovanović. M.(2012): A combining genetic learining algorithm and risk matrix model using in optimal production program”Journal of Applied Engineering
Science, Vol. 10, No. 3, pp. 147-152
Nunes. I.(2012): ”Fuzzy systems to support industrial engineering management”, Journal of Applied Engineering Science, No. 3, Vol. 10, No. 3, pp. 143-146
Popović. M., Vasić. B., Curović. D.(2010): A possible answer to the question: What is asset management? Journal of Applied Engineering Science,Vol. 8, No.4, pp. 205-2014
Saaty, T.L. (1990). How to make a decision: The Analytic Hierarchy Process. European J. Oper., 489-26.
Shih, H.S., Shyur, H.J., Lee, E.S. (2007). An Extension of TOPSIS for Group Decision Making. Mathematical and Computer Modelling, 45, 801-813.
Tadić, D., Milanović, D., Misita, M., Tadić, B. (2011). New integrated approach to the problem of ranking and supplier selection under uncertainties. Proceedings of the Institution of Mechanical Engineers. Part B: Journal of
Engineering manufacture, 225, 1713-1724.
Vesa, H., Heikki, K. (2011) Performance metrics for web-forming processes, Aalto University School of Electrical Engineering, Department of Automation and Systems Technology, P.O. Box 15500, 00076.
WenAn T., Weiming S., Jianmin Z. (2006) A methodology for dynamic enterprise process performance evaluation, a Software Engineering Institute. Zhejiang Normal University,
JinHua, Zhejiang, 321004, PR China.
Zimmermann, H.J. (1978). Results of empirical studies in fuzzy set theory (ed. G.J. Klir). Applied General Systems Research, Plenum Publishing Corporation, 303-311.
