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Research Paper | Manufacturing Engineering | India | Volume 4 Issue 5, May 2015

Optimization of Injection Molding Process Parameter for Reducing Shrinkage by Using High Density Polyethylene (HDPE) Material

Harshal P. Kale ^[2] | Dr. Umesh V. Hambire ^[2]

Abstract: Injection molding is an important polymer processing operation in the plastic industry. In this process, polymer is injected into a mold cavity, and solidifies to the shape of the mold. Optimizing the parameters of the injection molding process is critical to enhance productivity. For process optimization, parameters must operate at optimum levels for acceptable performance. Taguchi method is one of the methods of optimization, in which orthogonal array is generated based on experimental design. Optimization of injection molding process parameters will be carried out using high density polyethylene (HDPE) as the molding material Injection molding has been a challenging process for many plastic components manufacturers and researchers to produce plastics products meeting the requirements at very economical cost. Since there is global competition in injection molding industry, so using trial and error approach to determine process parameters for injection molding is no longer hold good enough. Since plastic is widely used polymer due to its high production rate, low cost and capability to produce intricate parts with high precision. It is much difficult to set optimal process parameter levels which may cause defects in articles, such as shrinkage, warpage, line defects. Determining optimal process parameter setting critically influences productivity, quality and cost of production in plastic injection molding (PIM) industry. In this paper optimal injection molding condition for minimum shrinkage were determined by the DOE technique of Taguchi methods. The various observation has been taken for material namely HDPE. The determination of optimal process parameters were based on S/N ratios.

Keywords: Injection molding, DOE, Taguchi optimization, design expert

Edition: Volume 4 Issue 5, May 2015,

Pages: 722 - 725

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