2013
DOI: 10.4028/www.scientific.net/amm.433-435.1890
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Parameters Optimization for Injection Molding Based on Digital Signal Processing

Abstract: The parameters optimization for injection molding based on digital signal processing is gave in this paper. First, design the optimization program of injection molding parameters with orthogonal test; Second, gating system, cooling systems and related injection molding process parameters are chosen as the experimental analysis factors to optimize injection molding process, and analyze the range and variance of test data by MATLAB, to determine the factors that affect the forming quality of the process signific… Show more

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Cited by 4 publications
(3 citation statements)
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“…In the case of four factors, optimal levels of the factors were achieved by performing a total of 31 experimental runs. After this, stepwise regression and optimization techniques were performed to determine the relationship equation and to find the optimal setting of factors respectively [11], [12], [13], [14], [15]. The experimental factors and their levels are shown in Table 1.…”
Section: Methodsmentioning
confidence: 99%
“…In the case of four factors, optimal levels of the factors were achieved by performing a total of 31 experimental runs. After this, stepwise regression and optimization techniques were performed to determine the relationship equation and to find the optimal setting of factors respectively [11], [12], [13], [14], [15]. The experimental factors and their levels are shown in Table 1.…”
Section: Methodsmentioning
confidence: 99%
“…An experimental design with the use of the stepwise regression technique is a method that can help find the relationship between the interested response and the factors significantly affecting the response. Then, the optimal setting of those significant factors that yield the response value closest to the target could be obtained by using an optimization technique [5], [6], [7], [8], [9], [10], [11].…”
Section: Methodsmentioning
confidence: 99%
“…Then, the Design of Experiment (DOE) with fractional factorial design is introduced in order to screen for significant factors. In the Improve phase, the steepest descent and response surface design are performed to find the optimal setting of significant factors [9], [10], [11], [12], [13]. To remain a well-performed process after improvement, a control plan is carried out in the Control phase.…”
Section: Methodsmentioning
confidence: 99%