Thermal spray coating is a critical process in many industries, involving the application of coatings to surfaces to enhance their functionality. This paper proposes a framework for modelling and predicting critical target variables in thermal spray coating processes, based on the application of statistical design of experiments (DoE) and the modelling of the data using generalized linear models (GLMs) and gamma regression. Experimental data obtained from thermal spray coating trials are used to validate the presented approach, demonstrating that it is able to accurately model and predict critical target variables and their intricate relationships. As such, the framework has significant potential for the optimization of thermal spray coating processes, and can contribute to the development of more efficient and effective coating technologies in various industries.

翻译：热喷涂涂层是许多行业中的关键工艺，涉及在表面施加涂层以增强其功能。本文提出一个框架，基于统计实验设计（DoE）的应用以及使用广义线性模型（GLMs）和伽马回归对数据进行建模，用于热喷涂工艺中关键目标变量的建模与预测。通过热喷涂试验获得的实验数据验证了所提出方法的有效性，表明该方法能够准确建模和预测关键目标变量及其复杂关系。因此，该框架在热喷涂工艺优化方面具有显著潜力，有助于各行业开发更高效、更有效的涂层技术。