Why talk about maintenance, a topic that should be a matter of course for entrepreneurs, production managers and operators?
Because our times, unfortunately, are characterized by such a speed that any slowdown in the production line has strong repercussions on business performance.
Until recently, it was believed that production defects, repair costs, raw material waste, downtime and slowdowns in the production cycle were part of the "natural law" of plant management.
It was normal to think that until a machine breaks down, it is not replaced. Nothing to say about the inevitable production delays caused by an unplanned repair. You had learned to accept with resignation the waiting time for a spare part and the inevitable inefficiency of the production line. Logic led you to think "if the part breaks, there's nothing I can do about it, it's certainly not my responsibility." That was until recently....
Now we are seeing a corporate cultural shift. Predicting the future is no longer pure magic, but thanks to predictive maintenance it is a factual phenomenon, usable by everyone, given the ease of use of its tools.
Predictive maintenance uses machine learning (artificial intelligence) algorithms to learn how machinery works and predict when and if there will be problems.
With predictive maintenance, you can challenge the "natural law" of downtime. It's a new modus operandi in which production defects are predicted before they arise. For the first time, it is possible to truly control the factory!
It's like having an analyst in your staff, who collects data, learns how the machine works, highlights the events that affect the workmanship and thus configures the scenarios that will be realized on the basis of the current production process. By being able to intervene before damage occurs, part breakages or production defects are avoided, production waste is reduced, and the efficiency of the plant itself is maximized.
Predictive maintenance therefore allows to improve the production process, thanks to the traceability of all process data and the possibility to intervene in real time to modify and improve the setting of the machinery.
We are witnessing an upgrading of the production structure, in which the new natural law is no longer "the inevitability of events" but "the ability to analyze and use the counter-efforts of the machines to one's own advantage".