制备氧化锆陶瓷预测最佳烧结温度数据

经温州博远工业设计公司授权本人数据使用证明，将采集到的数据使用一元线性回归模型用来预测制备陶瓷过程中的最佳烧结温度。该模型在泥浆比重、泥浆水分、稠化性、回坯泥比重、釉浆细度等数据为固定量条件下，通过该预测模型来预测最佳坯体收缩率时的烧结温度，从而能够为制备陶瓷预测出最佳的烧结温度，为广大的陶瓷生产企业提高了产品质量和生产效率提供技术支持。将采集到的数据使用一元线性回归模型用来预测制备陶瓷的最佳烧结温度。该模型在泥浆比重、泥浆水分、稠化性、回坯泥比重、釉浆细度等数据为固定量条件下，烧结温度与坯体收缩率构成一元函数关系（y（坯体收缩率）=F(烧结温度)），通过该函数公式来反推根据因变量变化的变化，在最佳坯体收缩率时根据极大似然法取概率分布最大的烧结温度的取值，从而能够为制备陶瓷出最佳的烧结温度。

With the official data usage certificate authorized by Wenzhou Boyuan Industrial Design Co., Ltd., the collected dataset is employed in a univariate linear regression model to predict the optimal sintering temperature during ceramic preparation. Under the condition that control variables including slurry specific gravity, slurry moisture content, thickening property, recycled green mud specific gravity and glaze slurry fineness are fixed, there is a univariate functional relationship between sintering temperature and green body shrinkage rate, formally expressed as y (green body shrinkage rate) = F(sintering temperature). By reversing the variation based on the dependent variable and adopting the maximum likelihood method to select the sintering temperature value with the maximum probability distribution when the green body shrinkage rate reaches the optimal level, the optimal sintering temperature for ceramic preparation can be determined. This approach provides technical support for ceramic production enterprises to improve product quality and production efficiency.

搜集汇总

数据集介绍

特点

该数据集提供了氧化锆陶瓷制备过程中的详细工艺参数和性能数据，旨在通过一元线性回归模型预测最佳烧结温度，以提高陶瓷产品的质量和生产效率。数据集规模为12803条，每年更新，适用于制造业中的陶瓷生产优化。