Open Access Open Access  Restricted Access Subscription or Fee Access

Investigation of Optimal Process Parameters of Extrusion Blow Molding Process Using Grey Taguchi Analysis

Jyoti Dohare, Vedansh Chaturvedi, Jyoti Vimal

Abstract


Optimization of machining processes is essential for achieving higher productivity and high-quality products in order to remain competitive. The objective of this study is to optimize the process parameter of extrusion blow molding process for making a plastic container of high density polyethylene (HDPE) grade B52A003 produced by the extrusion blow molding process at CIPET Gwalior. Quality of plastic container of HDPE B52A003 material depends on various parameters. In this paper three process parameters namely Barrel temp. (°C), Cooling/cycle time (sec.) and extruder speed (rpm) and three responses haze and clarity, hardness and compressive strength were selected as a quality target. Taguchi Method is a statistical method to improve the process parameters and improve the quality of components that are manufactured. Nine experimental runs based on Taguchi’s L9 (33) orthogonal array were performed followed by the Grey relational analysis to solve the three response optimization problem. Based on the Grey relational grade value and signal to noise ratio based on the higher is better criterion, optimum levels of parameters have been identified. The significance of parameters on overall quality characteristics of the extrusion blow molding process has been evaluated by the analysis of variance (ANOVA). The optimal parameter values obtained during the study have been validated by confirmation experiment.

Full Text:

PDF

References


V. Agrawal, J. Vimal, V. Chaturvedi. Optimisation of extrusion blow molding process parameters using grey relational analysis and taguchi, IJREAS. 2012; 2(2): 407–17p.

S.S. Subramanian, S. Durga, K.R. Loshni, V.D. Kumar. A review on control of plastic extrusion process, Int J Adv Res Electr Electr Instrum Eng. 2016; 5(1): 167–71p.

M.J. Barot, T.B. Mehta, C.E.V. Parekh. Review on finite element analysis and optimization of PVC window profile, Int J Eng Technol Sci Res. 2015; 2(1): 1–6p.

R. Denysiuk, F.M. Duarte, J.P. Nunes, A.G. Cunha. Evolving neural networks to optimize Material usage in blow molded containers, EUROGEN. 2017.

J.C. Yu, X.X. Chen, T.R. Hung, F. Thibault. Optimization of extrusion blow molding processes using soft computing and Taguchi’s method, J Intell Manuf. 2004; 15: 625–34p.

G.V.S.S. Sharma, R.U. Rao, P.S. Rao. A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process, J Ind Eng Int. 2017; 13: 215–28p.

A. Duita, M.E. Ryan. Parison inflation in extrusion blow molding a theoretical analysis for identifying critical process parameters, Intern J Polym Mater. 1982; 11: 201–15p.

C.D. Golghate, M.S. Pawar. Adopting best practices in blown film extrusion process: need of the hour to control environmental burdens, Int J Ind Eng Technol. 2013; 3(1): 63–80p.

M. Bordival, F.M. Schmidt, Y.L. Maoult, V. Velay. Optimization of preform temperature distribution for the stretch-blow molding of PET bottles: infrared heating and blowing modeling, Soc Plast Eng. 2009; 49: 783–93p.

G.Q. Huang, H.X. Huang. Optimizing parison thickness for extrusion blow molding by hybrid method, J Mater Process Technol. 2007; 182: 512–8p.

H.X. Huang, J.C. Li, D. Li, G.Q. Huang. New strategies for predicting parison dimensions in extrusion blow molding, Polym-Plast Technol Eng. 2011; 50: 1329–37p.

S. Kamaruddin, N.S. Zakarria, N.M. Mehat. The influence of plastic extrusion blow molding, ARPN J Eng Appl Sci. 2016; 11(20): 12029–32p.


Refbacks

  • There are currently no refbacks.