Modern Approaches for Optimization of Process Parameters of Plastic Injection Moulding – A Review

Authors

  • Dr. Chandni Kirpalani

Abstract

In plastic injection moulding, process parameters have an effect on production. The value of the process parameters depends on different ideas, such as plastic type, object size, dimensional tolerances, etc., so there are no set values ​​and formulas for different process parameters. For many manufacturers, injection moulding has always been a process to produce Lui that meets the requirements at the lowest cost. In the face of global competition in the injection moulding industry, it is no longer sufficient to use the trial and error method to determine the injection moulding process parameters. The factors that affect the quality of moulded parts are divided into four categories: part design, mould machine performance, and processing conditions. Parts and moulds are assumed to have been established and fixed during the production process due to machine wear, environmental changes, changes in the environment, changes in the environment, changes in the environment, or changes in the environment caused by the fatigue of the processing conditions drift or deviation, quality characteristics may appear deviation. Determining the optimal process parameter settings is critical to the productivity, quality and production cost of the plastic injection moulding (PIM) industry. . In the past, trial-and-error methods or Taguchi's parameter design method were used to determine the optimal process parameter settings for PIM. However, these methods are not suitable for the current PIM [1-6] due to the requirements of complex production and multi-response quality characteristics.

 

This review article aims to the recent research in designing the mould and determining the various important process parameters of plastic injection moulding. For improvement of part quality, a number of research works based on various approaches have conducted in the domain of the parameter setting for injection moulding. These approaches, including nonlinear mathematical models, Taguchi method, Artificial Neural Networks (ANN), Genetic Algorithms (GA), Fuzzy logic, Finite Element Method(FEM), Response Surface Methodology,Grey Rational Analysis and Principle Component Analysis (PCA) are described in this review article. Effect of various parameters on the concern defects are also discussed.

 

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Published

2021-06-10

How to Cite

Dr. Chandni Kirpalani. (2021). Modern Approaches for Optimization of Process Parameters of Plastic Injection Moulding – A Review. International Journal of Modern Agriculture, 10(1), 1092 - 1103. Retrieved from http://www.modern-journals.com/index.php/ijma/article/view/1325

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