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一种关键工艺，涉及在表面施加涂层以增强其功能性。本文提出了一种基于统计实验设计（DoE）应用，并利用广义线性模型（GLMs）和伽马回归对数据进行建模的框架，用于对热喷涂工艺中的关键目标变量进行建模与预测。通过热喷涂试验获得的实验数据验证了所提出的方法，证明了其能够准确建模和预测关键目标变量及其复杂关系。因此，该框架在优化热喷涂工艺方面具有显著潜力，并可促进各行业开发更高效、更有效的涂层技术。