It’s no wonder maintenance queues are bogged down–a typical building has one PM task every working week of the year, a typical portfolio of buildings has a PM task each working weekday. Solving the dilemma between evenly allocating the tasks while satisfying the maintenance specifications for each piece of equipment is complicated. How can a time-limited team of building operators manage? Gridium’s smart scheduling tool can help.
Mechanically complex systems take time to maintain and operate. 1911’s Benz & Cie race car, with it’s 200HP inline four cylinder engine, takes over six minutes to startup. An engine’s complexity is Legos compared to a modern building–a typical 100,000SF site has around 15 pieces of equipment, each needing a mix of monthly, quarterly, and or annual preventive maintenance tasks performed. Mix the complexity of disparate mechanical systems with corrective maintenance requests inbound from building occupants and add a dash of other responsibilities–such as responding to a peak demand alert or compiling a sustainability report–and your building is left with precious little time. Indeed, our analysis shows buildings spend only 2% of the day on preventive maintenance.
Automatically schedule PM tasks at the right time
One of Gridium’s newest innovations saves time by 1) automatically synchronizing all of the monthly, quarterly, or annual preventive maintenance tasks for a single piece of equipment such that those tasks are opened on the same day, and 2) applying our algorithmic horsepower to load balancing equations such that all of the PM tasks in your buildings are allocated appropriately across the calendar. This is a preview to our PM load balancing, which will soon be available to buildings running on our maintenance software:
If an air handler has both quarterly and annual PM, Tikkit will automatically schedule those tasks on the same day.
Smart preventive maintenance scheduling is made more efficient when connected to a digital asset management application, to the tune of an 8.7% improvement in time-to-resolution, per a Texas A&M study. This isn’t operator error or poor training, instead it is a challenge of mechanical system complexity. If you have questions, let us know.
