Our client, a contract manufacturing organisation (CMO), operates a pharmaceutical manufacturing plant which generates bulk drug materials for other manufacturers. As part of their contract manufacturing process, toxins are present which have to be treated in a wastewater treatment plant (WWTP) connected to the manufacturing site. From there, treated wastewater flows to the public authority waste treatment network.
During 2019 and early 2020 the manufacturing plant faced rising levels of toxins and asked Wyoming to use data analysis and data modelling to identify the root cause and from there to prepare monitoring and prediction dashboards to inform remediation activity. The WWTP is a complex environment with several processing stages, several large vessels (circa. 13,000 cubic meters) and two communities of bacterial organisms that synthesise waste to safe levels of toxins.
The WWTP tracks approximately 150 metrics such as temperature, acidity, dissolved oxygen and flow rate. Together in certain combinations, these metrics lead to stable plant operation (i.e. low toxins) or in other combinations, there can be excursions beyond desired rages and some instability in plant operation which can yield high levels of toxins.
Data quality was noted as a challenge as metrics were subject to different collection and transcription methods so required normalisation prior to use. Some data came directly from a distributed control system (DCS), some data came from standalone adjacent systems, some came from inline meters placed at key points in the plant and other data came from manual probes inserted to certain vessels and pools by staff on an irregular basis.