Maintenance in a Facility has almost become as critical as on a jetliner. People’s schedules, lives, business meetings, are being affected. Now granted, failure to repair the closer on the front door of your building won’t shut the building down like it could a jetliner. But it still affects our customers, they might not miss connecting flights, a conference, cruise, etc. but it still affects them negatively.
LEARN FROM THE PAST:
Data. We have it in each work order in our software. Have we found the trip point for that failure? How many hours of operation? Or every fifth oil change… happens, or when we have this issue, X follows within this time…
The past can prevent the future. Leverage your work orders, Equipment fault codes, and full IOT sensor data. But why only look at your own equipment when the manufacturer has the history on untold numbers? Their data can make your make more sense. Analytics like that can save huge amounts of downtime, failures by being predictive, preventative, fixing it before it happens, magic!
ACTION THE PRESENT:
Equipment will break unexpectedly, systems will fail out of the blue, however, does that mean repairing it should take so long, inconveniencing employees, disrupting schedules?
By using big data technologies and analyzing historical maintenance and operational data, we can more accurately predict each step of the return-to-service process, enabling us to make informed strategic maintenance decisions, minimize downtime, and enhance operational efficiency.
Do not wait to have the failure, plan to have the failure, know it will happen, analytics can tell you when, have the parts there, staff ready, get it back up and running to minimize the disruptions to employee routines.
PREDICT THE FUTURE:
Once we have Learned the Past, and add that to Actioning the Present, Predicting the Future becomes less of a crystal ball and more of a roadmap. It is not a perfect science, but it is sure getting close. We are the scientists of our domain, analyze, create, ask what if. What if I had known that what could I have done to prevent that? You know it, it is in your work orders, your data, your past, uncover it, use it, Predict with it.
