Tosoh Hellas is a chemical industry located in Thessaloniki Greece and produces Electrolytic Manganese Dioxide (EMD), the main raw material for the manufacture of alkaline batteries. One of the challenges they faced was unexpected failures. In such an industry, an unexpected failure can mean production downtime, and this translates into a loss of tens of thousands of euros. Or it can have an impact on the quality of the final product. 

The classic approach to reduce unexpected failures is preventive maintenance. For example, every year each critical motor must be dismantled, transported by crane to a workshop, opened and maintained. However, this process does not eliminate failures.

One further step is to use instruments to measure certain parameters such as vibrations. By analyzing such measurements, an engineer can assess the health of the equipment and predict failures before they occur. However, this also does not solve the problem because the interpretation of the measurements is based on human, which means that it is prone to errors and omissions.

TOSOH decided to move forward using AI technology from Siemens. They installed SIMOTICS Connect 400 wireless sensors on critical motors, which measure temperature, radial/tangential/axial vibration, electrical stator frequency and slip frequency and send them to the cloud app Drivetrain Analyzer Cloud. The application estimates the likelihood of a failure occurring in the future and notifies maintenance long before, so they can do the repair at a time that won't affect the production schedule.