2020
DOI: 10.1155/2020/1309209
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Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time

Abstract: This paper presents a framework for optimizing injection molding process parameters for minimum product cycle time subjected to constraints on the product defects. Two product defects, namely, volumetric shrinkage and warpage, as well as seven process parameters including injection speed, injection pressure, cooling time, packing pressure, mold temperature, packing time, and melt temperature, were considered. Injection molding experiments were conducted on specifically chosen test points and results were used … Show more

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Cited by 17 publications
(5 citation statements)
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References 47 publications
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“…As proof of this, the use of additive manufacturing in forming, castings, etc. industries has increased gradually [40]. It consists of seven methods as shown in Figure 3 with its modern technology and raw materials.…”
Section: Doe (Design Of Experimentsmentioning
confidence: 99%
“…As proof of this, the use of additive manufacturing in forming, castings, etc. industries has increased gradually [40]. It consists of seven methods as shown in Figure 3 with its modern technology and raw materials.…”
Section: Doe (Design Of Experimentsmentioning
confidence: 99%
“…Ahmad et al [22] applied the Taguchi method to analyze experimental data and find the operating conditions that minimize shrinkage. Mukras [23] proposed a framework for optimizing the operating conditions that minimize cycle time while assuming volumetric shrinkage and warpage as constraints. The operating conditions were experimentally related with the objective and constraints by means of the Kriging model (also known as Gaussian process regression, which is an interpolation method based on a Gaussian process), and the selection of the optimal solution was made graphically.…”
Section: Single Objective Optimizationmentioning
confidence: 99%
“…(Ayun et al, 2022) employed the Taguchi technique on polylactic and polyglycolic acid to optimize shrinkage and warpage of injection molded bone screw designed from the material using particle swarm optimization. (Mukras, 2020) employed the kriging technique, an optimization approach to minimize the product cycle time generated by volumetric shrinkage and warpage of injection molded products using an experimentalbased optimization approach. (Ramesh et al, 2021) employed Taguchi orthogonal parameter design and particle swarm optimization to measure the shrinkage volume and warpage amount rate for automobile molded parts.…”
Section: Literature Reviewmentioning
confidence: 99%