Predictive Maintenance

Business Problem

According to the Central Pulp & Paper Research Institute, maintenance costs account for 10% of sales in the industry, a substantially higher rate than in the chemical industry, car manufacturing, and engine manufacturing, and the losses for an entire paper and pulp plant from unscheduled downtime could exceed $1 million per hour.


Pulp and paper plants face many distinct challenges in production. With feeds of data coming from DCS or SCADA plus newer IoT sensors, the challenge is to analyze the data in context to discover anomalies and make predictions.

SentianController solution

SentianController is set up to monitor processes continuously. The system can be trained to issue alerts for anomalies as they occur while instantly compensating for them in the optimization of the process. In addition, the system can be trained to predict remaining useful life expectation (RUL). In this way, the capabilities of SentianController can extend to predictive maintenance.