Predicting maintenance before repairs
All equipment ultimately requires some maintenance. That’s when ServiceMax kicks into gear, dispatching a service engineer to make the necessary fixes before a machine needs to be taken completely offline for repairs. Additionally, within moments of a service call, SIG field service workers can find out everything needed to fix the problem.
First, the dispatcher can scan each technician’s work history to identify the nearest person with the right skills for the job. Next, he or she lays out a step-by-step guide for execution, even lining up the right spare parts for the technician to bring to the site. When the technician signs into his or her tablet or laptop for work that morning, everything needed to perform the job appears as a daily diary that’s accessible offline—a major benefit given the remote locations of some factories, including those in developing nations.
At day’s end, the technician synchronizes his or her day’s experience back to the software, teaching the machine-learning algorithm even more about maintenance—be it how long the procedure took or any additional tweaks the worker had to make.
Such feedback closes the loop on a virtuous cycle for SIG. Based on past ServiceMax customer experience, the company could achieve a 13% average increase in machine uptime and a 12% reduction in repair time. All of this culminates in a 19% improvement in productivity—enough to deliver customers to a land of milk and honey.
Read more about how GE Digital is helping accelerate SIG's digital transformation journey.