Horizons Update!
What’s new
FLoCK™ now includes a Predictive Maintenance layer that turns your existing machine records, fitted history, and replacement clock into fleet-wide learning.
Instead of only calculating due dates from the intervals you set on each machine, the system now analyzes real-world data across the fleet - how components actually fail, under what conditions, and how long they last in different positions and operating environments. From that it:
Refines replacement date predictions (more accurate than fixed intervals alone)
Flags machines and components that are trending toward earlier failure
Surfaces patterns that suggest design, part, or process improvements
Gives manufacturers and operators clear, actionable insights they can learn from
How it works (building on what you already have)
Fitted history remains the source of truth — every part fitted, where, and when.
Replacement clock still calculates the baseline due date from start date + last fit + position-specific interval.
New predictive layer compares actual failure and replacement events across similar machines in the fleet. It adjusts the expected remaining life and highlights outliers or systemic issues.
The Watcher continues to raise service-due and dependency alerts, now informed by the refined predictions.
Insights are available to the right roles (staff, distributors, customers) according to existing permissions.
Result: companies can see not only “this seal is due in March” but “seals of this type in this position are lasting 30 % less than expected across the fleet - here are the machines affected and the likely contributing factors.”