In industrial settings, few things are feared more than equipment failures. These failures frequently lead to costly downtime, production delays, and even safety hazards. To combat these challenges, many organizations have turned to predictive maintenance as a proactive solution. Predictive maintenance involves using data analytics, machine learning algorithms, and sensors to anticipate equipment failures before they occur. By continuously monitoring equipment condition and performance in this way, organizations can detect abnormalities or signs of wear and tear early on, allowing them to schedule maintenance before it is too late.
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/pump-up-the-predictions/