Understanding Predictive Maintenance in Manufacturing

Putting this idea into practice is anything but simple. Even two of the same pieces of equipment (i.e. two of the same model of drill in a manufacturing operation) can have unique patterns of data – and thus require unique calibration and diagnosis. Sensors to detect heat may not work well in colder seasons, or may fall off or lose their sensitivity when exposed to extreme conditions. Determining precisely what data should be used as the diagnostic data stream for a specific piece of equipment is also not easy, and may require expensive and time-consuming iteration. Even the most well-funded firms in industrial AI are still pivoting in order to find the right applications for machine learning in order to deliver consistent results for clients.