in design of experiments, analysis and identifying those variables that affect the outputs are of interest. response surface methodology is a mathematical-statistical method to optimize the experiment outputs. this method tries to find the best response levels by optimizing the design variables called factors. in many engineering applications, robust design has become the most important issues....

saturated fat consumption increases the risk of both coronary and cancer diseases. therefore, fat reduction in uf-feta cheese (≈ 45% fdm) is favorable but, unfortunately, it has some negative effects on the texture and sensory characteristics of the cheese. in this research, response surface methodology was employed to study the probably improving effects of wpc80 (0-20 gr kg-1), lecithin (0-2 ...

The quality of manufactured products is characterized by many controllable quality factors. These factors should be optimized to reach high quality products. In this paper we try to find the controllable factors levels with minimum deviation from the target and with a least variation. To solve the problem a simple aggregation function is used to aggregate the multiple responses functions then a...

There are many real problems in which multiple responses should be optimized simultaneously by setting of process variables. One of the common approaches for optimization of multi-response problems is desirability function. In most real cases, there is a correlation structure between responses so ignoring the correlation may lead to mistake results. Hence, in this paper a robust approach based ...

gelatin is a protein hydrocolloid. because of its unique characteristics such as gel forming, thickening, stabilizing, emulsifiing, foam and film forming, is widely used in food industries. in this research, in order to optimize the factors which affect enzymatic extraction method of gelatin ,the effects of three variables, enzyme concentrations(2-10 ppm), time(8-16 hours) and temperature(60-80...

optimization through simulation is considered anefficient tool in dealing with optimization problems. it’s a tool that iscapable to cover real world problems to a much more complete way than the otheroptimization tools. the problem of this tool is the necessity of heavyprocessing computations. this problem is caused not only since the simulationprocess is time consuming, but the objective funct...