A common pain point is machine downtime for maintenance purposes. By leveraging data produced by sensors embedded inside plant equipment, operators can manage when it is best to schedule maintenance—obviously not during peak customer demand.
“Sensors and statistical-process controls can tell you if you’re making the cuts at the precise dimensions—right down to one one-millionth of an inch.”
Product quality is another challenge. “Say you are making a widget for an aircraft engine at a particular density, weight and size and the machine is cutting to these parameters,” Busiek says. “Sensors and statistical-process controls can tell you if you’re making the cuts at the precise dimensions—right down to one one-millionth of an inch, for instance.”
Throughput is another problem area—knowing why there are bottlenecks and where—to ensure manufacturing schedules are optimized across the plant. Again, sensors and software can provide this vital information, which typically required physical inspections in the past.
Supply chains can be optimized by integrating the plant IT systems with enterprise systems managing suppliers, procurement, inventory and working capital. “You can look from the front end to the back end into everything on a dashboard, whereas you didn’t have that capability 10 years ago,” Busiek says.