Human Digital Profiles for Virtual Manufacturing Performance Prediction
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Solution Overview
Problem
In manufacturing processes involving human activities, obtaining quantitative information on performance, efficiency, throughput, and quality is difficult, leading to inaccurate predictions and costly, time-consuming physical measurements.
Innovation Solution
Generating human digital profiles using AI/ML models from standardized tests, performing virtual simulations, and optimizing operations based on performance predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical measurement in a testing environment is used to obtain performance and throughput data, then measurement precision is improved, but loss of time and loss of energy increase significantly
Solution Approach 1:
The patent creates digital twins (virtual copies) of human workers that replicate their physical characteristics, capabilities, and performance patterns. These digital copies enable virtual simulation of manufacturing operations without requiring physical testing setups, thereby maintaining measurement precision while eliminating time-consuming physical testing.
Solution Approach 2:
The system performs preliminary data collection and analysis to create comprehensive digital profiles of workers before actual manufacturing operations begin. This preliminary action includes gathering biometric data, skill levels, and performance metrics, which are then used for virtual simulation, avoiding the need for time-consuming on-site physical testing.
2Measurement precision
If physical measurement in a testing environment is used to obtain performance and throughput data, then measurement precision is improved, but cost increases
Solution Approach 1:
By using digital twins instead of physical testing setups, the system eliminates costs associated with physical testing environments, equipment, and personnel. The virtual simulation maintains measurement precision while significantly reducing the energy and financial resources required for physical testing.
3Loss of time
If estimation methods are used to generate performance and throughput data, then loss of time is reduced, but measurement precision deteriorates
Solution Approach 1:
The digital twin copies not only physical characteristics but also the complex behavioral patterns and performance variability of human workers. This enables the system to generate performance predictions quickly through virtual simulation while maintaining high accuracy, avoiding both the time-cost of physical testing and the inaccuracy of simple estimation methods.
Solution Approach 2:
The system transforms qualitative human characteristics (skills, experience, capabilities) into quantifiable parameters within the digital twin model. This parameter transformation enables accurate mathematical simulation of human performance, providing both speed and precision that neither estimation nor physical testing alone can achieve.
Data Source
AI summary
A method for performing operation optimization through virtual simulation, the method comprising generating, by a processor, human digital profiles associated with a plurality of persons; performing, by the processor, virtual simulation using the human digital profiles as input to a first model; generating, by the processor, performance prediction as output from the first model; and performing operation optimization based on the performance prediction.