Asset Value Models for Digital Twin Maintenance
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Solution Overview
Problem
Existing digital twin systems fail to effectively utilize relevant data to guide asset management, making it difficult to predict asset degradation and generate maintenance solutions.
Innovation Solution
A construction method and system for asset value models in a digital twin engine that measures business importance, establishes correlations between energy consumption assets and productivity, and calculates energy use efficiency to predict asset degradation and generate maintenance solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If digital twin systems store comprehensive building data, then data availability improves, but the ability to effectively utilize data for asset management guidance deteriorates
Solution Approach 1:
The patent introduces asset value models as an intermediary layer between the digital twin data storage system and asset management decision-making. These models process comprehensive building data through standardized frameworks that incorporate business importance weights, productivity correlations, and degradation predictions, transforming raw data into actionable asset management guidance.
Solution Approach 2:
The patent transforms comprehensive building data into meaningful asset management insights by applying parameter changes through asset value models. These models adjust and weight different data parameters based on business importance, correlate energy consumption with productivity metrics, and predict asset degradation trends, thereby converting abundant raw data into effective management guidance.
2Measurement precision
If asset management uses comprehensive building data, then decision accuracy improves, but computational complexity increases
Solution Approach 1:
The patent segments the complex task of asset management decision-making into distinct computational modules within asset value models. These modules separately handle business importance assessment, productivity correlation analysis, energy consumption evaluation, and degradation prediction, allowing each sub-task to be processed independently and efficiently while maintaining overall decision accuracy.
Solution Approach 2:
The patent applies preliminary action by pre-establishing asset value models with embedded business importance weights, productivity correlations, and degradation algorithms before actual asset management decisions are needed. This preprocessing of analytical frameworks reduces real-time computational complexity while preserving decision accuracy when these pre-configured models are deployed.
3Use of energy by moving object
If building operations optimize energy consumption, then energy efficiency improves, but asset productivity may deteriorate
Solution Approach 1:
The patent resolves this contradiction by dynamically adjusting operational parameters through asset value models that correlate energy consumption with productivity metrics. Rather than simply minimizing energy use, the models optimize energy parameters to achieve the best balance between energy efficiency and asset productivity, using weighted correlations to guide decisions that maintain productive output while improving energy performance.
Solution Approach 2:
The patent applies dynamics by making energy optimization strategies adaptive rather than static. The asset value models continuously adjust energy consumption recommendations based on real-time correlations between energy use and productivity metrics, allowing the system to dynamically balance energy efficiency improvements with productivity maintenance or enhancement.
Data Source
AI summary
A construction method and system for asset value models in a digital twin engine includes: measuring the level of business importance based on a business model of building energy consumption assets, and constructing a first asset value model according to the business importance; establishing a correlation between the assets and productivity, and constructing a second asset value model according to productivity loss caused by the assets; and calculating the energy use efficiency of a building according to optimal decision variables, predicting the degradation index of the assets through the energy use efficiency, the first asset value model and the second asset value model, and generating a maintenance solution of the assets. The disclosed has ingenious conception and excellent effect, and realizes the accurate evaluation of the asset value by establishing the correlation between the assets and different businesses and different efficiency, generating the optimal and most accurate asset maintenance solution.