Building Equipment Predictive Maintenance With Cost-Reliability Optimization
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Solution Overview
Problem
Current maintenance strategies for building equipment, such as run-to-fail and preventative maintenance, often fail to optimize the total cost of operating and maintaining equipment over time, as they do not account for varying costs and equipment degradation effectively.
Innovation Solution
A model predictive maintenance system that uses processing circuits to optimize an objective function defining the total cost of operating and maintaining building equipment, incorporating costs, maintenance decisions, and equipment replacement, with feedback loops to update efficiency and reliability, thereby determining an optimal maintenance strategy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If run-to-fail strategy is used, then maintenance cost is reduced, but equipment reliability deteriorates
Solution Approach 1:
The system performs preliminary assessment of equipment condition using multiple sensors and predictive models before failure occurs. By predicting remaining useful life and potential failures in advance, the system enables proactive maintenance scheduling that balances cost reduction with reliability maintenance, avoiding both premature maintenance and catastrophic failures
Solution Approach 2:
The system continuously monitors equipment condition through sensor data and feeds this information back to update predictive models and maintenance recommendations. This closed-loop feedback mechanism allows the system to adapt maintenance strategies based on actual equipment performance, optimizing the balance between maintenance costs and reliability
2Reliability
If preventative maintenance is performed at regular intervals, then equipment reliability is improved, but total cost increases
Solution Approach 1:
The system transitions from static, time-based maintenance schedules to dynamic, condition-based maintenance intervals. By continuously assessing equipment health status and adjusting maintenance timing accordingly, the system performs maintenance only when necessary, reducing unnecessary maintenance costs while maintaining reliability
Solution Approach 2:
The system changes the maintenance parameter from fixed time intervals to variable intervals based on equipment condition parameters. By monitoring parameters such as vibration, temperature, and performance degradation, the system adjusts maintenance timing to match actual equipment needs, optimizing the reliability-cost tradeoff
3Loss of energy
If model predictive maintenance with financial analysis is implemented, then total cost optimization is improved, but system complexity increases
Solution Approach 1:
The system integrates multiple functions including condition monitoring, predictive modeling, financial analysis, and maintenance scheduling into a single unified platform. By consolidating these functions, the system achieves total cost optimization while managing complexity through integration rather than separate systems
Solution Approach 2:
The system introduces a financial analysis layer that acts as an intermediary between technical maintenance data and decision-making. This intermediary translates complex predictive models and sensor data into financial metrics and cost-benefit analyses, making the system more accessible to stakeholders while maintaining optimization capabilities
Data Source
AI summary
A model predictive maintenance system for building equipment. The system includes one or more processing circuits including one or more processors and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include performing an optimization of an objective function that defines a present value of a total cost of operating the building equipment and performing maintenance on the building equipment as a function of operating decisions and maintenance decisions for the building equipment for time steps within a time period. The total cost includes one or more costs incurred during one or more future time steps of the time period. The operations include operating the building equipment and performing maintenance on the building equipment in accordance with decisions defined by the result of the optimization.