Orthogonal Experiment Data Analysis Based on Optimal Discrimination Plane and Its Application

It is difficult for conventional methods to analyze accurately the data of orthogonal experiment with multiple indexes and/or without blank lists. In this research, a new analysis method based on optimal discrimination plane (ODP) was proposed. For this method, two orthogonal vectors were firstly built up based on the Fisher´s criterion, and then the experiment data were projected onto the two vectors, thus, two-dimensional feature vectors were extracted as criteria to determine the factors effect degree on the indexes of orthogonal experiment. As an example, the experimental data of SIS hot-melt pressure sensitive adhesive properties were analyzed using this method. Results show that the proposed method can achieve results according with the practice, no matter how many indexes in orthogonal table and whether there are blank lists or not. Therefore, the ODP analysis method is effective to deal with orthogonal experiment data and can be applied widely to many fields.