Worker Motion Pattern Analysis with Execution-Count-Based Evaluation
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Solution Overview
Problem
Existing work analysis methods do not consider the proficiency level of workers when evaluating their motion patterns, leading to inadequate assessments.
Innovation Solution
A work analysis assistance device that acquires and evaluates motion patterns based on an evaluation standard set according to the number of times a worker has executed a specific task, incorporating video analysis, biometric data, and acceptability determination to provide a proficiency-level-based evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed evaluation standard is used for all workers regardless of their experience, then the evaluation process is simple and consistent, but the evaluation does not reflect the actual proficiency level of workers
Solution Approach 1:
The evaluation standard is made dynamic by adjusting it according to the worker's proficiency level, which is determined by the number of times they have executed the work. As workers gain experience and their motion patterns improve, the evaluation standard automatically adapts to reflect their higher proficiency, thereby improving measurement accuracy without requiring a completely new evaluation system
Solution Approach 2:
The evaluation standard changes its parameters based on the worker's execution count. By monitoring how many times a worker has performed the task and analyzing improvements in their motion patterns, the system modifies evaluation parameters to match the worker's current proficiency level, resolving the contradiction between evaluation accuracy and system complexity
2Measurement precision
If the evaluation standard is adjusted according to worker proficiency, then the evaluation becomes more accurate and meaningful, but it requires tracking and analyzing multiple variables about each worker
Solution Approach 1:
Instead of directly measuring complex proficiency concepts, the system creates a simplified copy or representation of proficiency through the execution count metric. This numerical proxy captures the essential aspect of worker experience and skill development without requiring complex direct measurement of proficiency, thereby reducing detection and measurement difficulty while maintaining evaluation accuracy
Solution Approach 2:
The system replaces complex manual assessment of worker proficiency with automated video analysis and pattern recognition. By using computer vision to objectively measure motion patterns and compare them against standards, the system eliminates the need for subjective human judgment and complex data collection methods, simplifying the overall measurement process
3Reliability
If video analysis and multiple data sources are used to capture motion patterns, then the data quality and comprehensiveness improve, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing key motion features during video capture, rather than analyzing the entire video dataset in real-time. By extracting and saving essential motion parameters as they are captured, the system ensures data reliability is maintained while significantly reducing the computational burden and processing time during evaluation
Solution Approach 2:
The system extracts only the essential and relevant features from the comprehensive video data, separating critical motion pattern information from redundant details. By focusing analysis on key extracted features rather than processing all raw video data, the system maintains high data reliability while minimizing processing time and computational resource requirements
Data Source
AI summary
A motion pattern of a worker is evaluated in consideration of a proficiency level of the worker with respect to a work. A pattern acquisition unit (12) that acquires a motion pattern when a worker executes a work, an evaluation standard setting unit (15) that sets an evaluation standard for the motion pattern, and a pattern evaluation unit (18) that evaluates the motion pattern on the basis of the evaluation standard are provided, and the evaluation standard setting unit (18) sets the evaluation standard for the motion pattern when a certain worker executes certain work according to the number of times of execution of the certain work executed by the certain worker.