عنوان مقاله [English]
Nowadays, quality is known as a commercial strategy to increase the market share and as it comes off, it will end up causing important problems such as customers’ dissatisfaction, reduced market share, and elimination from the competition. Therefore, the topics related to quality engineering have a vital importance in the industry. Several methods have been proposed in this regard, one of which is the response surface methodology. When the relation among the variables of a process is not clear, and the experimenter is interested in finding the optimal adjustments of the input variables, then the response surface methodology is utilized to optimize the process parameters. In this study, the response surface methodology has been exploited with the robust designing approach in order to optimize the quality characteristics of the product and affecting variables so that in the beginning the control variables and response variables must be identified and then the model should be optimized by designing the experiment and finding the intended regression equations. This research has been conducted on the industrial candy production process. For this purpose, using expert opinion, among the parameters affecting the production process of the candy, the two parameters of the brix and the temperature of the incubator as control parameters and the three parameters of the output of the candy and the time of storage in the incubator and the diameter of the candy were selected as the response variables. Then, the design of the experiments and the required data were analyzed by the statistical analysis software and the model was written based on a form of stochastic goal programming. In order to fix the problem of dimensions in solving the model by existing optimization software, the variance-covariance matrix is used for reducing the number of scenarios. Finally, after solving the model, the values of the control variables and the value of the objective function were obtained.