Main Article Content
designs of experiments, models, loss function, optimization multi–response, graphic method.
Many problems of optimization are characterized by the ﬂexibility to establish the utility among the functions objectives. Experimental strategy plays a very important part for generating theses functions. This speciﬁc strategy has also been applied in an important way to reduce costs when desiring quality and its continuous improvement in processes and products. It is common to ﬁnd many industrial applications with several responses whose purpose is to reach the global level of quality of a product. Therefore it is necessary to simultaneously optimize in a simultaneous the responses that the researcher desires. In essence, the problem of optimization of various responses involves the selection of a set of conditions or independent variables such that give a product or some convenient service an ideal result. The wish is to select the levels of independent variables that optimize all the responses at the same time. Two procedures will be displayed here in order to build a function that represents a combination of the objectives of the individual responses. The ﬁrst method is a model of optimization multiplicativo and the second additive. These will be applied to two cases of study which will be carried out in the industry for the purpose of pointing out the processes of continuous improvement and the decrease in costs. The simultaneous optimization, using these two procedures, will be illustrated by graphical means. This will allow a generation of several scenarios showing possible optimum solutions. In these examples it was observed that both methods produce similar results when generating the optimum one, however when comparing them in a global way by means of the loss function a slight diﬀerence it exists among them.
MSC: 62-XX, 62Kxx
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