Leverage predictive maintenance to grow your revenue
09 August 2021
MANY MACHINES and lines have critical components with a long design lifetime, but often these parts will fail within the machine lifetime. Breakdown of those critical parts is devastating for the production process, since most companies don’t have these critical parts in stock. The results are long downtimes and high costs for your customers, paired with the need for experienced service engineers on-site for replacement.
Such risks can be reduced with a predictive maintenance service for critical equipment where the condition is continuously monitored. By predicting such failures before they occur, you can increase the machine’s availability and grade of your service contracts.
A predictive maintenance strategy will lead to early warnings to prevent machine equipment failures
Data science in manufacturing to predict part failures
Experienced service engineers can often decide if the machine is running well by feeling the vibrations or just by listening to the machine to identify the cause. Machine builders can use their expertise and combine it with machine data to determine when parts are at the end of life by measuring symptoms to uncover the causes of faults. Monitoring the right data and comparing it with known patterns is the link bringing your combined service experience out on each machine 24/7/365.
Find out where to start when building a critical equipment monitoring strategy and read the use case for predictive monitoring of the vibration of a pump. Read the full article here.