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Andoko Andoko
(SCOPUS ID: 56013144100) Mechanical Engineering Department, Faculty of Engineering, State University of Malang, Malang
Automotive Engineering Control & Systems Engineering

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Optimization of Injection Pressure and Time of Injection Molding for Eye Drop Heads Ichlasul Insani; Andoko Andoko; Yanuar Rohmat Aji Pradana
TRANSMISI Vol 19, No 2 (2023): September 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmt.v19i2.10022

Abstract

Injection molding is a plastic production process by injecting liquid plastic into a mold. One of the injection molding products is an eye drop head. Eye drops in its production experienced rejects reaching 37.5% due to defects. The purpose of this optimization is to obtain the optimum setting of injection pressure and time of injection molding machine using RSM. The method to achieve the goal through finite element approach with pre-processing includes design and setting boundary conditions for injection pressure (10.5, 11, and 11.5 MPa) and injection time (1.9, 2.0, and 2.1 seconds). Post processing displays the results of product mass, defects, and quality prediction which are further optimized using RSM to obtain optimum values. The simulation results show that higher injection pressure and lower injection time have given satisfactory results for all three parameters (product mass, defects, and quality prediction) observed. Based on the optimization results, the optimal injection molding settings were obtained at an injection pressure of 11.5 MPa and injection time of 1.9 seconds which resulted in a product mass of 0.429 g, weld line defect of 0.1384, and quality prediction of 80.9%.
Optimization of Melt and Coolant Temperature on Defects of Injection Molded Toothbrush Handle Mochammad Arief Susetyo; Andoko Andoko; Yanuar Rohmat Aji Pradana
TRANSMISI Vol 19, No 2 (2023): September 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmt.v19i2.10021

Abstract

The toothbrush handle is an injection molded product that rejects up to 10%. One of the factors that cause defects is the injection molding process settings, namely melting and cooling temperature. The purpose of this optimization is to obtain the optimum value of melt and cooling temperature parameters on product quality (minimum defects) of toothbrush handles using RSM. The methods used include simulation using ANSYS to obtain mold temperature, Autodesk Moldflow to obtain product defects and quality prediction based on input parameters of melt temperature (190o , 200o , and 210o C) and coolant temperature (22o , 24o , and 26o C), and Minitab 19 for RSM optimization. The simulation results that cooling temperature and melt temperature that are too low and high result in high defect values (weld line and shrinkage) in the product, resulting in low quality prediction values. Based on the results of the optimized simulation, the best injection molding setting is at a melt temperature of 200oC and a cooling temperature of 24oC which obtains a toothbrush handle product quality response variable of 78.04% with a minimum weld line value of 0.0277o and a minimum shrinkage depth of 0.009 mm.
Co-Authors Ichlasul Insani Mochammad Arief Susetyo Pradana, Yanuar Rohmat Aji