2022
DOI: 10.1007/s11071-022-07861-1
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Modeling and prediction of spindle dynamic precision using the Kriging-based response surface method with a novel sampling strategy

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Cited by 6 publications
(2 citation statements)
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“…To create an optimized product with superior attributes and quality, software-based optimization methods are used (Thirunavukkarasu et al 2023 ). Response surface methodology (RSM) is an efficient statistical tool that uses lower-order polynomial equations to develop, improve, and optimize a process with many factors that influence the response (Chen et al 2023 ). RSM reduces the overall number of possible combinations, saving time and materials during experimentation (El-Sayed et al 2020b ).…”
Section: Introductionmentioning
confidence: 99%
“…To create an optimized product with superior attributes and quality, software-based optimization methods are used (Thirunavukkarasu et al 2023 ). Response surface methodology (RSM) is an efficient statistical tool that uses lower-order polynomial equations to develop, improve, and optimize a process with many factors that influence the response (Chen et al 2023 ). RSM reduces the overall number of possible combinations, saving time and materials during experimentation (El-Sayed et al 2020b ).…”
Section: Introductionmentioning
confidence: 99%
“…To create an optimized product with superior attributes and quality, software-based optimization methods are used [26]. Response surface methodology (RSM) is a statistical tool that applies lower-order polynomial equations to develop, improve, and optimize a process with many factors that influence the response [27]. RSM reduces the overall number of possible combinations, saving time and materials during experimentation [28].…”
Section: Introductionmentioning
confidence: 99%