Optimization of research and manufacturing processes in product and service

Bezerra et al. (2008) referred optimizing as a means to enhance the performance of a system or a process in order to acquire the maximum benefit from it. There are two ways how the performance of a system of process will be optimized. The common method is using classical method. Classical. optimization has been done by observing the influence of one factor at a time on an experimental response. This technique is called one-variable-at-atime where only one parameter is changed, others are kept at a constant level (Bezerra et al., 2008). However, this technique does not include the interactive effects among the variables studied and hence, does not portray the entire impacts of the parameter on the response. Another disadvantage of the one-factor optimization is the increase in the number of experiments which leads to an increase of time and expenses (Figure 1) as well as an increase in the consumption of reagents and materials (Bezerra et al., 2008). In order to overcome this problem, the optimization has been carried out by using response surface methodology (RSM), a multivariate statistic technique