This experiment introduces predictive maintenance technologies into a UK SME, Gadsden Tea Merchants, who manufactures teabags in their Portsmouth tea factory but also flavour teas and add spices & herbs as required, handling the entire process from receipt of raw teas to packing and labeling of the finished product.

This state of the art experiment uses BEinCPPS architecture to develop an understanding of the sensor and actuator data onsite in order to analyse the impact of vibration on several teabag filling machines to develop a sophisticated early warning system for preventing catastrophic failure of the process on the shop floor (not just scheduled maintenance).

Thisexperiment has been supported under the second open call of BEinCPPS project.

Benefits to Gadsden Teas Merchants include the reduction in the number of catastrophic machine failures enabling them to maintain a robust supply of goods to customers, and reduce waste through improved quality control. In addition, the project offer insight to how changes in the production process – more tea producers are under pressure to switch from plastic heat sealed teabags to more environmentally friendly solutions – may impact on machine productivity and health.



University of Portsmouth, Britpip, Gadsden Tea Merchants

Food & Beverage