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Probabilistic commodity price projections for unbiased techno-economic analyses (2023)
Journal Article
Rodgers, S., Bowler, A., Meng, F., Poulston, S., McKechnie, J., & Conradie, A. (2023). Probabilistic commodity price projections for unbiased techno-economic analyses. Engineering Applications of Artificial Intelligence, 122, Article 106065. https://doi.org/10.1016/j.engappai.2023.106065

Techno-economic analysis is a core methodology for assessing the feasibility of new technologies and processes. The outcome of an analysis is largely dictated by the product's price, as selected by the practitioner. Representative future price distri... Read More about Probabilistic commodity price projections for unbiased techno-economic analyses.

Machine learning and domain adaptation to monitor yoghurt fermentation using ultrasonic measurements (2023)
Journal Article
Bowler, A., Ozturk, S., di Bari, V., Glover, Z. J., & Watson, N. J. (2023). Machine learning and domain adaptation to monitor yoghurt fermentation using ultrasonic measurements. Food Control, 147, Article 109622. https://doi.org/10.1016/j.foodcont.2023.109622

In manufacturing environments, real-time monitoring of yoghurt fermentation is required to maintain an optimal production schedule, ensure product quality, and prevent the growth of pathogenic bacteria. Ultrasonic sensors combined with machine learni... Read More about Machine learning and domain adaptation to monitor yoghurt fermentation using ultrasonic measurements.

A review of ultrasonic sensing and machine learning methods to monitor industrial processes (2022)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2022). A review of ultrasonic sensing and machine learning methods to monitor industrial processes. Ultrasonics, 124, Article 106776. https://doi.org/10.1016/j.ultras.2022.106776

Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved general... Read More about A review of ultrasonic sensing and machine learning methods to monitor industrial processes.

Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation (2021)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2021). Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation. Fermentation, 7(4), Article 253. https://doi.org/10.3390/fermentation7040253

Beer fermentation processes are traditionally monitored through sampling and off-line wort density measurements. In-line and on-line sensors would provide real-time data on the fermentation progress whilst minimising human involvement, enabling ident... Read More about Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation.

Convolutional feature extraction for process monitoring using ultrasonic sensors (2021)
Journal Article
Bowler, A., Pound, M., & Watson, N. (2021). Convolutional feature extraction for process monitoring using ultrasonic sensors. Computers and Chemical Engineering, 155, Article 107508. https://doi.org/10.1016/j.compchemeng.2021.107508

Ultrasonic sensors are a low-cost and in-line technique and can be combined with machine learning for industrial process monitoring. However, training accurate machine learning models for process monitoring using sensor data is dependant on the featu... Read More about Convolutional feature extraction for process monitoring using ultrasonic sensors.