AbstractAccurate and responsive non-invasive temperature measurements are enablers for process monitoring and plant optimization use cases in the context of Industry 4.0. If their performance is proven for large classes of applications, such measurement principles can replace traditional invasive measurements. In this paper we describe a two-step model to estimate the process temperature from a pipe surface temperature measurement. This static case model is compared to and enhanced by computational fluid dynamic (CFD) calculations to predict transient situations. The predictions of the approach are validated by means of controlled experiments in a laboratory environment. The experimental results demonstrate the efficacy of the model, the responsiveness of the pipe surface temperature, and that state of the art industrial non-invasive sensors can achieve the performance of invasive thermowells. The non-invasive sensors are then used to demonstrate the performance of the model in industrial applications for cooling fluids and steam.