To design a mechanism with better overall equipment effectiveness (OEE), we need to identify a suitable system for the machine to perform to its optimum under a set of constraints; this could be challenging.
What’s more, in modern machine operation, many motion actions such as the automated sorting process or the pick-and-place of parcels are triggered by sensors – the timing of each motion varies. When the exact time sequence for element changes are unknown, it is hard to have a better grasp on the equipment performance, e.g., its cycle time, prior to actual testing of the machine.
In general, one of the biggest challenges the machine designers have is to understand and test how a design will interact in real life before it goes into production. There are usually many rounds of trial-and-error required in ensuring the equipment performance requirements are achieved – the machine is moving the way we wanted it to.
How can we shorten the (sometimes endless) trial-and-error process?
