Production Management Apparatus for Worker State Estimation
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Solution Overview
Problem
Existing methods for determining the physical and mental states of workers in production lines rely on managerial experience and intuition, leading to inaccurate assessments and inappropriate interventions, which can negatively impact productivity.
Innovation Solution
A production management apparatus, method, and program that utilize activity sensors to obtain information on a worker's activity, estimate their emotion and cognition using learning data, and determine appropriate interventions based on productivity estimates to enhance productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If managerial experience and intuition are used to determine worker states, then subjective judgment is available, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent replaces the mechanical/manual system of managerial observation and intuition with an automated information processing system. Sensors collect objective data about worker activities, and a computer automatically processes this data to determine worker states (attention, emotion, fatigue levels), eliminating the need for subjective human judgment while maintaining simplicity through algorithmic processing.
2Productivity
If visual observation by manager is used to monitor worker states, then intervention can be provided, but productivity and time efficiency worsen due to inaccurate and delayed assessment
Solution Approach 1:
The system implements continuous monitoring of worker states through sensors that constantly collect data about worker activities. The computer processes this data in real-time, enabling continuous assessment of worker conditions without interruption to production work. This allows for timely interventions that maintain productivity while eliminating the time loss associated with periodic manual checks.
Solution Approach 2:
The system establishes a feedback loop where sensor data about worker states is continuously fed to the computer, which processes this information and provides feedback about worker conditions (attention levels, emotion, fatigue). This feedback mechanism enables the manager to make informed decisions about interventions, ensuring that productivity enhancement actions are based on current, accurate worker state information rather than delayed or inaccurate observations.
3Reliability
If manual observation and intervention decisions are used, then flexibility in judgment is available, but reliability and consistency of intervention deteriorate
Solution Approach 1:
The patent replaces the manual decision-making system with an automated computer-based system that processes sensor data according to predetermined criteria. This substitution ensures that intervention decisions are made consistently based on objective measurements rather than varying human judgments, thereby improving reliability while introducing automation to the assessment process.
Solution Approach 2:
The system transforms subjective worker states (attention, emotion, fatigue) into measurable parameters through sensor data collection. By converting intangible psychological states into quantifiable data points that can be processed objectively, the system achieves reliable and consistent intervention determination through automated parameter analysis rather than subjective human assessment.
Data Source
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AI summary
An appropriate intervention is constantly provided for a worker without relying on the experience or the intuition of a manager for improving and enhancing the productivity. Vital sign measurement data and motion measurement data obtained from workers WK1, WK2, and WK3 during operation are used as primary indicators. The primary indicators and learning data generated separately are used to estimate the emotion and the cognition of the worker. The estimated emotion and cognition are used as secondary indicators. The secondary indicators and relational expressions generated separately are used to estimate the productivity of the worker. The variation of the productivity estimate is compared with a threshold that defines the condition for providing an intervention. When the variation of the productivity estimate is determined to exceed the threshold, the intervention is provided for the worker.