Scheduling maintenance for load control systems
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Solution Overview
Problem
Maintenance tasks in load control systems often disrupt occupant activities and can be challenging to perform without interrupting the intended operation of electrical loads, especially when specific timing is required, such as during occupancy or at specific times of day.
Innovation Solution
A system and method for scheduling and executing maintenance tasks, such as programming updates, firmware updates, recalibration, and system performance verification, using local and cloud maintenance supervisors that identify and trigger maintenance based on criteria like occupancy status, time of day, and device status, ensuring minimal disruption to occupants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maintenance tasks are performed on load control devices, then system reliability is improved, but occupancy disruption increases
Solution Approach 1:
The system performs preliminary actions by scheduling maintenance tasks in advance during predicted unoccupied periods. The maintenance supervisor determines triggering criteria including time of day and occupancy status, then schedules maintenance to occur before occupancy is expected, thus preparing the system for maintenance without disrupting actual occupancy.
Solution Approach 2:
The maintenance scheduling system dynamically adjusts maintenance timing based on real-time and predicted occupancy data. Instead of fixed schedules, the system adapts maintenance execution timing according to actual occupancy patterns, making the maintenance process flexible and responsive to changing conditions to minimize disruption.
2Reliability
If maintenance tasks are scheduled at specific times, then system performance is maintained, but operational flexibility is reduced
Solution Approach 1:
The system employs dynamic scheduling where maintenance tasks are assigned flexible time windows rather than fixed times. The maintenance supervisor can adjust scheduling based on multiple triggering criteria including occupancy predictions, task priority levels, and device criticality, allowing the system to adapt to changing operational requirements while maintaining performance standards.
Solution Approach 2:
The system changes scheduling parameters dynamically by adjusting maintenance task timing, duration, and priority based on varying conditions. Parameters such as scheduled time, execution window, and rescheduling criteria are modified according to occupancy patterns and system state, enabling flexible adaptation without compromising maintenance effectiveness.
3Productivity
If maintenance tasks are performed during occupancy, then maintenance efficiency is improved, but occupant experience deteriorates
Solution Approach 1:
The system performs preliminary analysis of occupancy patterns to identify optimal maintenance windows before scheduling actual maintenance tasks. By predicting unoccupied periods in advance and preparing maintenance schedules during these times, the system achieves efficient maintenance execution without the need to rush or extend maintenance into occupied periods, thus protecting occupant experience.
Solution Approach 2:
The system uses feedback from occupancy sensors and historical data to continuously refine maintenance scheduling. Occupancy information feeds back into the maintenance supervisor algorithm, which adjusts future maintenance schedules based on actual occupancy patterns observed, thereby progressively optimizing the balance between maintenance efficiency and occupant experience.
Data Source
AI summary
Systems, methods, and apparatus are described herein for enabling performance of maintenance tasks on one or more load control devices in a load control system. An indication of maintenance task may be received, from a cloud server, at a local controller configured to control the one or more load control devices in one or more rooms of a building. The local controller may identify triggering criteria for triggering a performance of the maintenance task on one or more load control devices in the one or more rooms of the building. The local controller may determine that the triggering criteria of the at least one rule has been met and perform the maintenance task on the one or more load control devices in the one or more rooms of the building.