The following takes place between 6:00 a.m. and 7:00 a.m. on Monday, October 6, 2017. Events occur in real time.
06:00:27 a.m. Pacific Time
PACIFIC HOSPITAL, LOS ANGELES.
In the basement of the largest hospital in Los Angeles, Jack Bowzer, Chief Engineer and Reliability Manager clocks in for the day.
Beginning to brew his morning coffee, he changes into his uniform.
06:02:44
Jack sips his coffee as he turns on his computer and looks over the maintenance plan he has set for the day.
With routes that include the thirteenth floor operating room ventilation fan, he grabs an Auguscope, his portable machine vibration analysis tool, and straps it to his belt.
06:07:32
CHINATOWN, LOS ANGELES.
Mindy Cantalone exits the bus in a hurry and a few minutes late for work. She doesn’t notice the oncoming car that strikes her in the side. Panic ensues as the vehicle delivers a crushing blow. Onlookers immediately call 9-1-1.
06:13:07… 06:13:08… 06:13:09…
06:15:14
PACIFIC HOSPITAL, LOS ANGELES.
Jack Bowzer arrives on the thirteenth floor at the Operating Room ventilation fan. He recalls struggling in the past with predefined preventive maintenance checklists, endlessly wasting time checking for problems that aren’t there. Breathing a sigh of relief that their team moved towards a predictive maintenance strategy, he pulls out his Auguscope to begin recording vibration and ultrasound emissions from each bearing point to pinpoint any developing malfunctions.
06:20:25
Completing the vibration recording, Jack submits the data to Augury for immediate machine diagnostics.
06:20:55
AUGURY HQ, NEW YORK CITY.
Data recorded from Jack’s operating room fan is securely streamed to Augury’s database where machine learning algorithms run full diagnostics across all recordings. Noticing high vibrations and ultrasonic sounds being produced at the horizontal axis of a motor bearing, Augury’s algorithm immediately flags an issue.
CHINATOWN, LOS ANGELES.
Mindy Cantalone is ushered into an ambulance as medics rush to save her life. With every minute counting and morning rush hour traffic building, they take off for the nearest hospital.
06:21:54… 06:21:55… 06:21:56…
06:22:25
PACIFIC HOSPITAL, LOS ANGELES.
Jack’s phone alarm sounds; it’s a report from his submission from the Auguscope. Looking at the report, he notices that Augury’s diagnostic algorithm has flagged his operating room exhaust fan as “DANGER.” Jack’s heart rate rises. He immediately opens the app to find the issue is calling out a faulty bearing located on the non-driven end of the motor. Calling his maintenance office from the thirteenth floor mechanical room, he asks his team for an update on spare bearings. Hearing they have just one left, he issues the request to replace the fan bearing immediately.
06:30:43
Jack’s team shuts down the operating room exhaust fan. Implementing Augury’s suggested repair, they begin dismantling the rear of the motor. With no time to lose, they utilize a bearing puller to remove the bearing with minimal hammering. As they remove the faulty bearing and replace it with the spare, they notice visual bearing wear, confirming the diagnostic report. Had they not fixed it, it would have shut down mid-operation. Adding lubrication and slipping on the new bearing, the team rushes to get the fan back online.
06:55:12
HOSPITAL ICU.
Mindy is wheeled into the ICU, as doctors begin to suit up and prepare for immediate operation. Her vitals are rapidly diminishing. With the only available operating room open being currently shut down due to loss of an exhaust fan, staff call the maintenance office requesting expedited onboarding of the exhaust fan.
06:57:01
Putting the final motor components back in place, and now with a new bearing, Jack and his team start up the operating room exhaust fan. They are relieved to see it’s running smoothly and with minimal vibrations. Jack returns to the maintenance office, logs onto Augury’s machine health platform, and records a successful repair.
Seconds later, Mindy enters the operating room and staff begin performing immediate measures to save her life.
06:59:57… 06:59:58… 06:59:59… 07:00:00
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