Optimization of self-colored dental zirconia block parameters for an effective machining performance using response...

Self-colored dental zirconia blocks eliminate the drawbacks of the coloring process of traditional blocks and ensure disposal time and cost in dental prosthesis laboratories. Like traditional dental zirconia frameworks, self-colored dental zirconia frameworks are produced by grinding pre-sintered zirconia blocks via manual or CAD/CAM operating devices. The process parameters such as powder type, pre-sintering temperature and doping amount of coloring powder affect the machining performance of blocks through microhardness, bulk density and shrinkage values (diameter and thickness) during fabrication. In this study, we propose the response surface methodology (RSM) based artificial bee colony (ABC) algorithm to adjust the suitable combination of process parameters on the machining performance for self-colored dental zirconia blocks.

The optimum machining performance of the self-colored dental zirconia blocks is investigated using a multi-objective model named as RSM integrated ABC algorithm. Sensitivity analysis is utilized to identify the effects of objectives on the responses considering the different importance weights of each objective.

After obtaining the optimized parameters of pre-sintering temperature= 1066.546 ℃, doping amount of coloring powder= 10.638 (wt%) and powder type=TZP-1 by multi-objective ABC algorithm, the machining performance-related properties are found out Hυ1= 44.918 MPa, bulk density= 3.098 g/cm³, and shrinkage (%) (diameter)= 0.197, shrinkage (thickness)= 0.254.

Process parameters that directly affect the machining performance of the self-colored dental zirconia blocks were investigated with a multi-objective method for the first time in the literature. The results provide a base for further research on optimizing the self-colored dental zirconia block parameters for an effective machining performance.