2010
DOI: 10.1007/s00170-010-2945-3
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Multi-response design of Nd:YAG laser drilling of Ni-based superalloy sheets using Taguchi’s quality loss function, multivariate statistical methods and artificial intelligence

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Cited by 55 publications
(18 citation statements)
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“…In this paper, we propose an integrated and generic approach for robust multiresponse process optimisation based on SA algorithm that extends our previous research [36][37][38][39] in terms of the improvement of the quality of a final solution obtained by the method, the robustness of the method and a feasibility of its practical application. The intention was to develop a generic framework that could be applied to various static multiresponse optimisation problems, disregarding the type of process, its parameters and/or responses and their mutual interrelations.…”
Section: Introductionmentioning
confidence: 71%
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“…In this paper, we propose an integrated and generic approach for robust multiresponse process optimisation based on SA algorithm that extends our previous research [36][37][38][39] in terms of the improvement of the quality of a final solution obtained by the method, the robustness of the method and a feasibility of its practical application. The intention was to develop a generic framework that could be applied to various static multiresponse optimisation problems, disregarding the type of process, its parameters and/or responses and their mutual interrelations.…”
Section: Introductionmentioning
confidence: 71%
“…This research presents an extension of our previously published methodology for multiresponse process parameter optimisation [36][37][38][39] in terms of the improvement of the quality of a final solution, the robustness of a method and feasibility of application. The presented methodology consists of two stages.…”
Section: Resultsmentioning
confidence: 99%
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