Development of a software framework for experimental design in the chemical industry

Cost reduction is very important for the companies as competition increases in the market. Experimental Design Methods are used in various units of enterprises are a major factor for businesses in this direction and provide a way to reach the most accurate desired results by using shortest path with a minimum cost. In this thesis, a new framework for experimental design and a system, called DOExpert, is proposed and implemented to use at several industries. In particular, we provide several tasks (a) designing a model with Unified Modeling Language (UML) and creating a database (b) implementation of the framework and DOExpert system (c) applying experimental works at chemical industry. Proposed framework contains two Design of Experiment (DOE) approaches: Taguchi Method and Regression Analysis. In this study, we provide the following new contributions: (i) supporting several DOE methods at the same time, (ii) calculating more than one response values at the same time, (iii) ordering main factors and the effects of their interactions and (iv) finding optimum values of factors for one response variable and (v) finding optimum values of the factors for more than one response variables. In this thesis, experimental studies were applied at chemical industry. Taguchi experimental method and regression analysis were used to set optimum windows profiles color levels or values during product recipe preparation to reach the desired results. These experimental design methods can be also used for different purposes in different industries. Experimental results obtained at chemical industry show the effectiveness of the proposed framework. The results show that our framework has a good performance in time and cost. Results obtained in this study shows that approximately 75 percent process recovery can be provided by using experimental design methods. Keywords: Design of experiment, Taguchi method, regression analysis, chemical industry