Application of multi criteria decision making methods to select sheet hydroforming process parameters

Abstract: The present study endeavors to show an application of the multi objective optimization on the basis of ratio analysis (MOORA) method and technique for order performance by similarity to ideal solution (TOPSIS) method to select optimal process parameters in sheet hydroforming process. The right choice of the process parameters is critical to produce a final part with proper quality. In order to meet this characteristic, the important properties are the cup final thickness (FT), required forming force (FF) and radial stress (RS) at cup wall region. Nine alternatives for selecting the process parameters were taken into consideration based on Taguchi L9 orthogonal array. The limit drawing ratio (LDR), maximum pressure and prebulge pressure were selected as input variables. To solve the problem of process parameters’ selection, the two mentioned methods were used. A compromised weighting approach composed of Entropy and analytic hierarchy process (AHP) methods were used to weight all criteria. The alternatives ranking were performed using MOORA and TOPSIS methods and then the results were compared. The results achieved in both of the assessment represent that the alternative number 3, leads to the best multi performance features of the process among the 9 experiments. In this experiment LDR is 1.81, maximum pressure and prebulge pressure are 37 MPa and 15 MPa, respectively.

How to cite this paper

 Modanloo, V., Doniavi, A & Hasanzadeh, R. (2016). Application of multi criteria decision making methods to select sheet hydroforming process parameters.Decision Science Letters , 5(3), 349-360.

Refrences

Amiri, M. P. (2010). Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods. Expert Systems with Applications, 37(9), 6218-6224.

Brooghani, S. A., Khalili, K., Shahri, S. E., & Kang, B. S. (2014). Loading path optimization of a hydroformed part using multilevel response surface method. The International Journal of Advanced Manufacturing Technology,70(5-8), 1523-1531.

Cal??kan, H., Kur?uncu, B., Kurbano?lu, C., & Güven, ?. Y. (2013). Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods. Materials & Design, 45, 473-479.

Chatterjee, P., & Chakraborty, S. (2012). Material selection using preferential ranking methods. Materials & Design, 35, 384-393.

Yoon, K., & Hwang, C L. (1980). Multiple Attribute Decision Making Methods and Applications. A State of the Art Survey, Springer Verlag, Berlin.

Chu, J., & Su, Y. (2012). The application of TOPSIS method in selecting fixed seismic shelter for evacuation in cities. Systems Engineering Procedia, 3, 391-397.

Jahan, A., Mustapha, F., Ismail, M. Y., Sapuan, S. M., & Bahraminasab, M. (2011). A comprehensive VIKOR method for material selection. Materials & Design, 32(3), 1215-1221.

Karande, P., & Chakraborty, S. (2012). Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection. Materials & Design, 37, 317-324.

Lang, L., Danckert, J., & Nielsen, K. B. (2005). Investigation into hydrodynamic deep drawing assisted by radial pressure Part II. Numerical analysis of the drawing mechanism and the process parameters. Journal of Materials Processing Technology, 166, 150-161.

Modanloo, V., Gorji, A., & Bakhshi, M. (2015). Experimental and numerical investigation of the sheet forming in hydroforming process. Journal of Solid and Fluid Mechanics, 5(4).

Palumbo, G., Zhang, S. H., Tricarico, L., Xu, C., & Zhou, L. X. (2006). Numerical/experimental investigations for enhancing the sheet hydroforming process. International Journal of Machine Tools and Manufacture, 46(11), 1212-1221.

Patel, J. D., & Maniya, K. D. (2015). Application of AHP/MOORA Method to Select Wire Cut Electrical Discharge Machining Process Parameter to Cut EN31 Alloys Steel with Brasswire. Materials Today: Proceedings, 2(4), 2496-2503.

Peng, L., Lai, X., Hu, P., & Ni, J. (2008). Flow channel shape optimum design for hydroformed metal bipolar plate in PEM fuel cell. Journal of Power Sources, 178(1), 223-230.

Qi, Y., Wen, F., Wang, K., Li, L., & Singh, S. (2010). A fuzzy comprehensive evaluation and entropy weight decision-making based method for power network structure assessment. International Journal of Engineering, Science and Technology, 2(5), 92-99.

Rao, R. V. (2007). Decision making in the manufacturing environment: using graph theory and fuzzy multiple attribute decision making methods. Springer Science & Business Media.

Rashedi, A., Sridhar, I., & Tseng, K. J. (2012). Multi-objective material selection for wind turbine blade and tower: Ashby’s approach. Materials & Design, 37, 521-532.

Razali, N. M., & Wah, Y. B. (2011). Power comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests. Journal of Statistical Modeling and Analytics, 2(1), 21-33.

Saaty, T. L. (1988). What is the analytic hierarchy process? (pp. 109-121). Springer Berlin Heidelberg.
Shahrajabian, H., Khalili, K., & Khalili, M. S. (2011, June). Modeling and Optimization of Pressure Profile in Hydroforming of St12 Conic Part with RSM and Genetic Algorithm. Key Engineering Materials, 473, 587-593.

Shanian, A., & Savadogo, O. (2006). A material selection model based on the concept of multiple attribute decision making. Materials & Design, 27(4), 329-337.

Shanian, A., & Savadogo, O. (2006). TOPSIS multiple-criteria decision support analysis for material selection of metallic bipolar plates for polymer electrolyte fuel cell. Journal of Power Sources, 159(2), 1095-1104.

Sharma, A. K., & Rout, D. K. (2009). Finite element analysis of sheet Hydromechanical forming of circular cup. Journal of Materials Processing Technology, 209(3), 1445-1453.

Singh, S. K., & Kumar, D. R. (2004). A comparison of different neural network training algorithms for hydromechanical deep drawing. International Journal of Materials and Product Technology, 21(1-3), 186-199.

Wei, C. C., Chien, C. F., & Wang, M. J. J. (2005). An AHP-based approach to ERP system selection. International Journal of Production Economics, 96(1), 47-62.

Zhang, Y., & Ge, L. (2013). Parameter Optimization in the Process of Hydroforming Based on Genetic Algorithm. International Journal of Applied Mathematics and Statistics™, 50(20), 295-301.

Zhang, H. P. (2015). Application on the entropy method for determination of weight of evaluating index in fuzzy mathematics for wine quality assessment. Advance Journal of Food Science and Technology, 7(3), 195-198.