In the manufacturing space, IoT technology is a crucial enabler for predictive maintenance. Through the use of IoT sensors, smart factories are coming to life, with connected machines that can communicate with each other and with humans, who can take action when necessary.
This technology can catch changes and faults that are unseen by the human eye. Instead of solving a problem after it happens, predictive maintenance will alert the system ahead of time, so humans (or machines) can take the necessary action to ensure no problem occurs at all. The two key criteria in the context of predictive maintenance are technical assistance and decentralized decision-making.
Regarding the first, predictive maintenance drastically improves technical support by catching errors that no humans can see. Not only does this eliminate machine downtime, but it increases the safety of all people who use the device. Regarding the second, a machine doesn’t lie or have a gut feeling, instead predictive maintenance decisions are solely based on data, eliminating a centralized decision-maker—though it should be noted that bias can still be a problem for AI.
Nevertheless, the combination of machine-to-machine (M2M) communication and AI will soon enable entire factories to make data-driven decisions with minimal human intervention.