Demand for predictive maintenance in automated manufacturing is rising due to its potential to reduce the risk of malfunction, minimize downtime, and prolong the lifespan of equipment. Smart manufacturing simplifies the maintenance process by applying advanced data analytics with condition monitoring for consumables, wear-and-tear, and performance.
These data translate into significant cost-savings for manufacturers and eliminate the need for labor-intensive, imprecise manual checking methods. In real-time monitoring, sensors are attached to machines to actively detect and obtain accurate data on the condition and environment of workers, vehicles, machinery, and facilities. They also track the levels of consumables such as lubricants or refrigerants, as well as their temperature, viscosity and other variables. Powered dashboards gather and analyze data, promptly sending alerts to key personnel if a change is detected, so that corrective actions can be taken immediately. Detailed downtime analysis and failure reports on key machines, components or process constraints are generated for a holistic view of future maintenance needs, enabling manufacturers to reduce the mean times between malfunctions and repairs.