25 Apr 2019 - Peter
Manufacturing in all sectors is carried out on a diversity of machines that all have one thing in common; at some time, some critical component will need to be replaced.
You could put it off until it breaks and forces the issue with unplanned downtime. Then you find there isn't a spare in stores, the part is on a six week lead time, and the board will want an explanation why production is being hit.
You could implement a rigorous maintenance schedule so that nothing ever gets close to wearing out, and the board will ask why so much money is being spent on spares stockholding and plant upkeep.
Or you could watch, and wait, gathering data to predict when wear is becoming critical and failure is approaching, but is not imminent.
Data acquisition from modern CNC machines is easy with IIoT connectivity already integrated, but a fifty year old lathe, milling machine or packaging line should not be ruled out. Current transformers on the power supply, temperature probes and vibration detectors on a tool carrier, motor speed and torque measurement on a conveyor, connected to an I/O outstation enable communication with 'mature' equipment.
The old can sit on the same network as the new, generating historian data for machine learning automated analysis. Scheduled reports would reveal when conditions are deteriorating, but before failure occurs and damages production. Parts can be ordered on a just in time basis, the shutdown planned and impact on production minimised.
Data acquisition is a wide spectrum. Talk to Op-tec about getting the best out of data you never knew you could access.
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