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Abstract Thermal Spraying of tungsten carbide is usually performed to optimize surface hardness. However, often there are additional coating or process requirements, e.g., low porosity, low roughness, or high deposition efficiency, that must be met to satisfy the customer or increase the process efficiency. Such optimizations are difficult because various influencing factors, e.g., lambda (λ), standoff-distance, or powder feed rate, have different effects on the individual coating and process properties. In this study, several trials were performed and analyzed (technically & databased) to understand how each influencing factor affects these coating and process properties. It could be determined that there is no general best performance parameter but that only individual solutions depending on prioritized importance of the properties can be obtained. Using data, one way of solving the challenge is the performance of multi-objective optimization. With the help of this method, the challenges of optimization can be solved using test data. The simultaneous optimization can be visualized in a 2D/3D graph. A boundary line can be observed where different process and coating characteristics are optimized. Applying such databased methods can help to work more efficiently as well as more sustainable in development and application.
Rannetbauer et al. (Mon,) studied this question.