2020
DOI: 10.1016/j.jmapro.2020.06.004
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Optimization of the pulsating curve for servo stamping of rectangular cup

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Cited by 11 publications
(5 citation statements)
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“…The designed curves are shown in Table 3. 1 The result of thickness ratio in drawing molding is recorded by using orthogonal array and DEFORM-3D software analysis simulation. Then the S/N ratios of various groups are worked out, as shown in Table 4.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The designed curves are shown in Table 3. 1 The result of thickness ratio in drawing molding is recorded by using orthogonal array and DEFORM-3D software analysis simulation. Then the S/N ratios of various groups are worked out, as shown in Table 4.…”
Section: Resultsmentioning
confidence: 99%
“…The variation trend of material thickness and ultimate draw ratio are observed and the tensility higher than connecting rod actuation is obtained. [1][2][3] Then, the moldability for material draw ratio in different conditions is analyzed. The flow of material, drawing ratio, and load are discussed.…”
Section: Introductionmentioning
confidence: 99%
“…studied the SUS304 rectangular cup stamping and optimized the pulsating curve for a servo press using the finite element method. Meanwhile, they applied the Taguchi method to obtain the optimal parameter combinations and the optimization results showed that a shorter forming time (0.06 s less), a lower thinning ratio lower (0.1425% less), and a smaller forming force (808 N smaller) [12]. Kriechenbauer et al proposed a systematic design of deep-drawing processes with free force and motion functions on servo presses based on computational science methods.…”
Section: Strengths Weaknesses Traditional Methodsmentioning
confidence: 99%
“…The main parameters that infl uence quality characteristics can be pre-dictable or unpredictable. 71 It is a measure of robustness used in Taguchi designs to identify control factors that reduce variability in a product or process by minimizing the effects of uncontrollable factors (noise factors). Control factors are independent (input) parameters that can be controlled.…”
Section: Signal To Noise Ratio (S/n) Analysismentioning
confidence: 99%