Building Equipment Maintenance Scheduling by Lifecycle Cost Modeling
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Solution Overview
Problem
Current maintenance strategies for building equipment, such as run-to-fail and preventative maintenance, often result in increased costs for customers and maintenance providers, necessitating a more economically viable alternative that reduces expenses while generating additional business for maintenance services.
Innovation Solution
A model predictive maintenance system that uses processing circuits to compute the costs of maintaining and replacing building equipment over a life cycle horizon, determining optimal maintenance and replacement decisions based on objective functions that consider operating and maintenance costs, interest rates, and equipment degradation, thereby generating a maintenance schedule that minimizes overall costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If preventative maintenance is performed at regular intervals, then equipment reliability is improved, but operational costs increase
Solution Approach 1:
The patent transitions from static, time-based maintenance schedules to dynamic, condition-based maintenance scheduling. The system continuously monitors equipment degradation in real-time and adjusts maintenance timing based on actual equipment state, allowing maintenance to be performed only when economically optimal rather than at fixed intervals, thus reducing unnecessary operational costs while maintaining reliability
Solution Approach 2:
The system changes the parameter basis for maintenance decisions from time-based parameters to degradation-state parameters. By monitoring equipment degradation levels and using optimization algorithms to determine the economically optimal maintenance timing, the system performs maintenance based on actual equipment condition and economic factors rather than predetermined time intervals, reducing operational costs while maintaining reliability
2Loss of energy
If maintenance is delayed to reduce costs, then operational costs decrease, but equipment degradation increases
Solution Approach 1:
The system implements continuous feedback monitoring of equipment degradation states and uses optimization algorithms to determine the economically optimal maintenance timing. The feedback loop tracks degradation in real-time, compares it against economic models, and dynamically adjusts maintenance schedules, allowing delays only when economically beneficial while preventing excessive degradation that would compromise reliability
Solution Approach 2:
The system performs preliminary economic analysis and degradation monitoring to determine the optimal maintenance timing before equipment failure occurs. By proactively analyzing degradation trends and economic factors, the system schedules maintenance at the economically optimal moment, balancing cost reduction with reliability maintenance
3Loss of energy
If run-to-fail strategy is used, then operational costs decrease, but equipment reliability deteriorates
Solution Approach 1:
The system performs preliminary economic optimization analysis to determine the optimal maintenance timing before equipment failure. By proactively scheduling maintenance based on economic models and real-time degradation monitoring, the system achieves reliability improvements over run-to-fail strategies while minimizing operational costs through economically optimal maintenance timing
Solution Approach 2:
The system enables the equipment to effectively monitor its own degradation state and triggers maintenance automatically when economic optimization indicates it is the optimal time. This self-monitoring and automated decision-making allows the system to balance cost and reliability without continuous human intervention, achieving better outcomes than both run-to-fail and traditional preventative maintenance
Data Source
AI summary
A model predictive maintenance system for building equipment that performs operations including obtaining an objective function defining a cost of operating and performing maintenance on the equipment as a function of operating and maintenance decisions for time steps within a time period of a life cycle horizon and including performing a first computation of the objective function under a first scenario where maintenance is performed on the equipment during the period, a result of the first computation indicating a first cost. The operations include performing a second computation under a second scenario in which maintenance is not performed during the period, a result indicating a second cost. The operations include initiating an automated action to perform maintenance on the equipment in accordance with decisions defined by the first scenario if the first cost is less than or equal to the second cost.