An analysis on energy consumption of injection moulding process using neural network

Ahmad Siaman, Muhamad Afiq Hakimi (2023) An analysis on energy consumption of injection moulding process using neural network. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

This paper presents a hybrid optimization method for optimizing the process parameters during injection moulding. This proposed method neural network to find the best parameter in injection moulding. A multi-objective optimization model is established to optimize the process parameters during injection moulding on the basis of Orthogonal experiment method, and neural network. Optimization goals and design variables (process parameters during injection moulding) are specified by the requirement of manufacture. A neural network model is developed to obtain the mathematical relationship between process parameters and the power value. The best parameter will find out after the experiments occured. A case study of a plastic article is presented. Clamp meter as well as clamp force during injection moulding are investigated as the optimization objectives. Mold temperature, melting temperature, packing pressure and cooling time are considered to be the design variables. The case study demonstrates that the proposed model neural network method can adjust the process parameters accurately and effectively to satisfy the demand of real manufacture.

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