Building Equipment Maintenance Optimization for Total Cost Control
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Solution Overview
Problem
Existing maintenance strategies for building equipment, such as run-to-fail, preventative, and predictive maintenance, struggle to accurately predict the costs and benefits of various maintenance tasks, making it difficult to determine an optimal maintenance strategy that balances operational and maintenance costs.
Innovation Solution
A model predictive maintenance (MPM) system that predicts operational and maintenance costs over a duration using an objective function optimizer, considering equipment efficiency, reliability, and purchase decisions, to determine an optimal maintenance strategy that minimizes total costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If predictive maintenance strategy is used to perform diagnostics and predict maintenance tasks, then maintenance effectiveness is improved, but difficulty in predicting costs and benefits increases
Solution Approach 1:
The patent replaces complex manual cost-benefit analysis with an automated optimization engine that uses mathematical models and algorithms to determine optimal maintenance strategies. The system substitutes human judgment with computational optimization that processes equipment data, maintenance costs, and operational parameters to automatically identify the most cost-effective maintenance tasks.
Solution Approach 2:
The system enables self-service by allowing the optimization engine to autonomously determine maintenance strategies without requiring external expert intervention. The engine independently evaluates equipment conditions, predicts maintenance needs, calculates cost-benefit ratios, and generates recommended maintenance schedules based on integrated data from multiple sources.
2Reliability
If maintenance tasks are performed to improve equipment performance, then equipment reliability is improved, but operational costs increase
Solution Approach 1:
The patent changes the parameter of maintenance timing from fixed schedules to optimized intervals based on actual equipment conditions and cost-benefit analysis. The system dynamically adjusts maintenance parameters (when to perform tasks, which tasks to perform) to achieve the optimal balance between reliability improvement and cost minimization, rather than using static maintenance schedules.
Solution Approach 2:
The system applies partial action by selectively performing only those maintenance tasks that provide positive net benefit, rather than performing all recommended maintenance tasks. The optimization engine identifies and executes only the subset of maintenance activities where the reliability improvement justifies the operational cost, avoiding unnecessary maintenance expenditures.
3Productivity
If equipment is operated continuously to maximize productivity, then productivity is improved, but equipment reliability deteriorates
Solution Approach 1:
The patent applies dynamics by making maintenance scheduling flexible and adaptive rather than static. The optimization engine continuously monitors equipment conditions and dynamically adjusts maintenance timing to balance productivity and reliability. The system can shift maintenance tasks to periods of lower productivity impact when equipment conditions allow, creating a dynamic balance between operational output and equipment health.
Data Source
AI summary
A model predictive maintenance (MPM) system for building equipment includes an operational cost predictor configured to predict a cost of operating the building equipment over a duration of an optimization period, a maintenance cost predictor configured to predict a cost of performing maintenance on the building equipment over the duration of the optimization period, and an objective function optimizer configured to optimize an objective function to predict a total cost associated with the building equipment over the duration of the optimization period. The objective function includes the predicted cost of operating the building equipment and the predicted cost of performing maintenance on the building equipment. The MPM system includes an equipment controller configured to operate the building equipment to affect a variable state or condition in a building in accordance with values of one or more decision variables obtained by optimizing the objective function.