MODELING AND OPTIMIZATION OF AN INTERVAL TYPE 2 FUZZY LOGIC SYSTEM FOR A CERAMIC COATING PROCESS - Olvera-Romero, Gerardo Daniel; Praga-Alejo, Rolando Javier; Gonzalez-Gonzalez, David Salvador (International Journal of Industrial Engineering: Theory, Applications and Practice, 2023)
Process control is essential in Industry 4.0, and process modeling is an effective way to achieve it. For complex processes with high variability and uncertainty, Interval Type 2 Fuzzy Logic Systems are an efficient alternative, but they lack an appropriate methodology for selecting the Footprint of Uncertainty width. This work proposes a method that uses a genetic algorithm to optimize the Footprint of Uncertainty width and evaluates various Type-Reduction methods. ANOVA and R^2 and R_prediction^2 statistics are used to verify the model, which is applied to a manufacturing process that adjusts the density of a ceramic coating. The results indicate that the optimized model (R^2=0.886) outperforms the non-optimized model (R^2=0.796), linear regression (R^2=0.498), and backpropagation neural networks (R^2=0.641). Additionally, a stability analysis of the proposed model was performed using cross-validation, obtaining an R_prediction^2=0.758, which indicates that the genetic algorithm-based method can be a suitable option for modeling complex processes.