Predictive Modelling of Critical Variables for Improving HVOF Coating using Gamma Regression Models
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866909182530158592 |
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| author | Rannetbauer, Wolfgang Hubmer, Simon Hambrock, Carina Ramlau, Ronny |
| author_facet | Rannetbauer, Wolfgang Hubmer, Simon Hambrock, Carina Ramlau, Ronny |
| contents | 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) with a particular emphasis on 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. 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_01194 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Predictive Modelling of Critical Variables for Improving HVOF Coating using Gamma Regression Models Rannetbauer, Wolfgang Hubmer, Simon Hambrock, Carina Ramlau, Ronny Applications Numerical Analysis Applied Physics 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) with a particular emphasis on 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. 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. |
| title | Predictive Modelling of Critical Variables for Improving HVOF Coating using Gamma Regression Models |
| topic | Applications Numerical Analysis Applied Physics |
| url | https://arxiv.org/abs/2311.01194 |