Robot-Human Picking Workflow for Mixed Article Throughput
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Solution Overview
Problem
Existing systems face decreased throughput due to the need to call an operator to a station when articles that cannot be picked by a robot are placed in a dispensing case with articles that can be picked by a robot.
Innovation Solution
An information processing method that transfers storage cases to both robot and human stations, allowing robots to pick articles at robot stations and operators to pick articles at human stations, thereby separating the handling of pickable and non-pickable items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If articles that can and cannot be picked by a robot are put into the same dispensing case, then the system can handle mixed article types, but the throughput decreases because an operator must be called to the station to pick non-pickable articles
Solution Approach 1:
The system segments the picking process by separating articles into different dispensing cases based on pickability. Robot-pickable articles are placed in dispensing cases at robot stations, while non-pickable articles are placed in dispensing cases at human stations. This segmentation allows the system to maintain high throughput by enabling robots to operate autonomously without requiring operator intervention, while still accommodating mixed article types through the segmented arrangement of multiple dispensing cases.
2Adaptability or versatility
If an operator is called to a robot station to pick non-pickable articles, then all article types can be processed at a single station, but the system efficiency decreases due to operator intervention requirements
Solution Approach 1:
The system extracts the non-pickable articles from the robot's workload by providing a separate dispensing case at the human station. The transfer device automatically transfers these articles to the human station's dispensing case, removing the need for operators to intervene at robot stations. This extraction principle eliminates time loss while maintaining the ability to process all article types through the distributed station network.
3Extent of automation
If robots are used for picking, then automation level increases, but the system cannot handle articles that require human dexterity and judgment
Solution Approach 1:
The transfer device acts as an intermediary that bridges the capabilities of robots and human operators. It automatically transfers storage cases and dispensing cases between robot stations and human stations based on article pickability. This intermediary mechanism allows the system to maintain high automation levels for robot-pickable articles while seamlessly integrating human operators for complex articles that require human dexterity and judgment, without compromising overall system automation.
Data Source
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AI summary
An information processing method, an information processing device and a system capable of effectively picking articles are provided. According to an embodiment, an information processing method executed by a processor includes transferring a storage case which stores an article to a robot station where the article is picked by a robot, causing the robot to pick the article from the storage case and put the article into a dispensing case, transferring the dispensing case to a human station where an operator picks the article, transferring the storage case to the human station, and causing the operator to pick the article from the storage case and put the article into the dispensing case.