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Statistics > Applications

Title: A Statistical Approach for Improving HVOF Coating: Predictive Modelling of Critical Variables using Generalized Linear Models

Abstract: 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.
Comments: 32 pages, 7 figures
Subjects: Applications (stat.AP); Numerical Analysis (math.NA); Applied Physics (physics.app-ph)
Cite as: arXiv:2311.01194 [stat.AP]
  (or arXiv:2311.01194v1 [stat.AP] for this version)

Submission history

From: Simon Hubmer [view email]
[v1] Thu, 2 Nov 2023 12:40:26 GMT (1553kb,D)
[v2] Mon, 6 Nov 2023 11:51:06 GMT (1553kb,D)
[v3] Fri, 26 Apr 2024 12:18:29 GMT (1602kb,D)

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