Terahertz waveform selection of a pharmaceutical film coating process using a recurrent network

Waveform selection plays an important role in the processing of in-line terahertz measurements of pharmaceutical tablet coating processes. This paper presents an approach to optimise waveform selection by utilising an artificial recurrent neural network and transfer learning. The results show that the averaged coating thickness gradually increases throughout the coating process. In comparison with the conventional method, our approach allows more than double the number of waveforms to be selected without compromising on the accuracy when compared against off-line measurements. Moreover, the processing time of waveform selection decreases so that it can be applied for real-time coating monitor in the pharmaceutical industry.