Collaborative Robot Task Allocation for Worker-Robot Time Balance
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Solution Overview
Problem
In collaborative robot systems, existing technologies fail to efficiently manage task distribution between robots and workers, leading to inefficiencies and decreased production efficiency due to variations in work time, especially when worker fatigue or changes in task load occur.
Innovation Solution
A collaborative robot system that includes a work-time measurement unit, a difference-at-increase/decrease prediction unit, an assigned-location adjustment unit, and an assigned-location indication unit to dynamically adjust the number of locations assigned to workers and robots based on predicted work time differences, ensuring minimal time discrepancies and optimizing task distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of locations assigned to the worker is increased, then the robot can perform more tasks, but the worker's work time increases leading to decreased efficiency
Solution Approach 1:
The system dynamically adjusts the number of locations assigned to the worker based on real-time work time measurements and predicted differences. The control device continuously monitors actual work times and modifies task allocation in subsequent cycles, transforming a static assignment into a dynamic adaptive process that optimizes productivity while preventing worker overload
Solution Approach 2:
The system implements a feedback loop where the work-time measurement unit continuously measures actual work times for both worker and robot, the difference-at-increase/decrease prediction unit predicts time differences for potential assignment changes, and the assigned-location adjustment unit uses this information to optimize future assignments. This closed-loop feedback ensures productivity improvements without excessive worker burden
2Loss of time
If the number of locations assigned to the worker is decreased, then the worker's work time decreases, but the robot must perform more tasks increasing system complexity
Solution Approach 1:
The system segments the total tasks into discrete locations that can be independently assigned to either worker or robot. This segmentation allows flexible reconfiguration of task allocation without requiring complete system redesign, managing complexity by treating each location as an independent assignable unit rather than a monolithic task block
Solution Approach 2:
The task allocation is made dynamic through continuous measurement and adjustment. The control device adapts the division of labor between worker and robot based on measured performance data, allowing the system to optimize the balance between worker workload and robot task load without fixed rigid assignments
3Ease of operation
If task assignments are fixed, then system operation is simple, but efficiency decreases when worker fatigue or task difficulty changes
Solution Approach 1:
The system performs self-optimization by automatically measuring work times, predicting differences, and adjusting task assignments without external intervention. The control device autonomously adapts to changing conditions such as worker fatigue or task difficulty variations, maintaining high efficiency while requiring minimal manual reconfiguration
Solution Approach 2:
The system transitions from static fixed assignments to dynamic adaptive assignments that automatically respond to changing conditions. The control device continuously adjusts task distribution based on measured performance data, enabling the system to maintain optimal efficiency despite variations in worker state or task characteristics
Data Source
AI summary
The present invention provides a collaborative robot system in which a robot and a worker share tasks and perform the tasks. The collaborative robot system including: a work-time-measurement-unit that measures work time for locations assigned to the worker and the robot; a difference-at-increase/decrease-prediction-unit that predicts a difference between the work time of the worker and the robot, when the number of locations assigned to the worker is increased or decreased; an assigned-location-adjustment-unit that increases or decreases the number of locations so that the difference in the work time becomes smaller, in a case in which a predicted-difference-value based on the work time of the worker and the robot, when the number of locations assigned to the worker is maintained is greater than the predicted-difference-value; and an assigned-location-indication-unit that indicates the locations assigned to the worker after the number of assigned locations is increased or decreased.