Optimization of shrinkage in injection-molding of 40% glass filled nylon 66 using response surface methodology (RSM) and genetic algorithm (GA)

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Paper Details

Paper Title

Optimization of shrinkage in injection-molding of 40% glass filled nylon 66 using response surface methodology (RSM) and genetic algorithm (GA)

Authors

Ashwani Kapoor, Mr. Deepak Kumar

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Abstract

In plastic injection molding, process parameters play a major role in the product quality. The values of process parameters depend on varies thinks like, type of plastics, the dimension of the object, dimensional tolerance, etc., so there is no set values and formula of different process parameters. Two-stage optimization technique, response surface methodology (RSM) and genetic algorithm (GA) used to analyze and optimizing a product, for improving its quality by reducing shrinkage. First with the help of literature survey, find most significant process parameters which profoundly influence the shrinkage, also their level. The level also affected by the type of plastics and injection machine. After that with the help of design of experiment (DOE) tool which is part of RSM, develop a sequence of experiment and perform them. RSM gives an analysis of variance (ANOVA) table, after removing insignificant terms from the quadratic model, got equation. This equation is use in GA, and GA gives best possible values of process parameters to minimize the shrinkage. So after optimization, optimized values of process parameters are Mold temperature (MT) 106.18 °c, Packing time (Pt) 5.16 sec, Packing pressure (PP) 14.53 MPa, Cooling time (Ct) 10 sec. Which results in decreasing Shrinkage by 34.783 %.

Keywords- PIM, RSM, GA, Nylon, Shrinkage, Optimization, DOE

Publication Details

Unique Identification Number - IJEDR1604032
Page Number(s) - 188-193
Pubished in - Volume 4 | Issue 4 | November 2016
DOI (Digital Object Identifier) -
Publisher - IJEDR (ISSN - 2321-9939)

Cite this Article

Ashwani Kapoor, Mr. Deepak Kumar , "Optimization of shrinkage in injection-molding of 40% glass filled nylon 66 using response surface methodology (RSM) and genetic algorithm (GA)", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 4, pp.188-193, November 2016, Available at :http://www.ijedr.org/papers/IJEDR1604032.pdf

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