文章基本信息

标题：A multivariate quality loss function approach for parametric optimization of non-traditional machining processes
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作者：Shankar Chakraborty ; Partha Protim Das
期刊名称：Management Science Letters
印刷版ISSN：1923-9335
电子版ISSN：1923-9343
出版年度：2018
卷号：8
期号：8
页码：873-884
DOI：10.5267/j.msl.2018.6.001
出版社：Growing Science
摘要：Due to various added advantages over the conventional material removal processes, non-traditional machining (NTM) processes have now been widely applied in different manufacturing industries. To achieve the desired response values, it is always recommended to operate these NTM processes at their optimal parametric settings. Various single response optimization techniques are already available to determine the optimal combinations of NTM process parameters for achieving maximum or minimum value of a single response. In this paper, a multivariate quality loss function approach is adopted for simultaneous optimization of responses for three NTM processes. It is observed that this approach outperforms the other multi-response optimization techniques, like desirability function, distance function and mean squared error methods with respect to the achieved response values. With modification of the corresponding objective function and constraints of the developed non-linear programming problem, it can be effectively applied to any non-traditional as well as conventional machining process as a multi-objective optimization tool.
关键词：Multivariate loss function Quality Non;traditional machining process Process parameter Response Optimization