Equipment Status Estimation Using Robotic Arm Throughput
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing equipment management systems cannot accurately determine the status of equipment that is not directly sensed in production lines, particularly in scenarios with branching and merging configurations and multiple product processing, as they fail to estimate throughput effectively for unsensed equipment.
Innovation Solution
A method and system that determine the throughput of robotic arms, identify equipment and product pairs by comparing throughput to standard values, and identify idle equipment based on robotic arm topology, using a server connected to PLCs and involving a computer program to execute processes for estimating equipment status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct sensing is used for equipment status monitoring, then measurement precision is improved, but device complexity increases and not all equipment can be sensed
Solution Approach 1:
The patent uses robotic arm throughput as an intermediary indicator to infer the status of unsensed equipment. Instead of directly sensing all equipment, the system monitors robotic arm performance and uses this data to deduce the operational state of upstream and downstream equipment through topology relationships and throughput comparison.
Solution Approach 2:
The patent replaces physical sensing devices with a computational inference system. Rather than installing sensors on every piece of equipment, the system uses algorithmic processing of robotic arm throughput data and topology information to determine equipment status, substituting mechanical sensing with information processing.
2Device complexity
If throughput monitoring of robotic arms is used to estimate equipment status, then device complexity is reduced, but measurement precision deteriorates for unsensed equipment
Solution Approach 1:
The patent segments the equipment monitoring problem into manageable components: robotic arm throughput monitoring, topology relationship analysis, equipment-product pair identification, and status inference. By dividing the complex monitoring task into these discrete steps, the system achieves accurate equipment status estimation without requiring direct sensing of all components.
Solution Approach 2:
The system establishes feedback loops where robotic arm throughput data is continuously monitored, compared against standard values, and used to update equipment status estimates. The topology information provides feedback pathways that allow the system to trace status changes back to specific equipment, improving estimation accuracy through iterative refinement.
3Productivity
If standard throughput comparison is used to identify equipment status, then productivity is improved, but measurement precision decreases for complex configurations with branches and merges
Solution Approach 1:
The patent implements dynamic adaptation for complex configurations by adjusting the throughput comparison methodology based on topology characteristics. For branching and merging configurations, the system dynamically modifies how standard throughput values are applied, considering the specific equipment-product relationships and configuration type to maintain accurate status identification.
Data Source
AI summary
Example implementations described herein estimate parameters for equipment that cannot be sensed directly, including determining if such equipment is running or stopping. Example implementations determine the standard throughput per equipment and product, based on history of equipment production data, extract previous and next equipment of robotic arms on the line by using physical topology information of robot arms and equipment, senses and determines throughput of associated robot arms and compares the robot arm throughput with the standard throughputs of the previous and next equipment, which help determine whether the previous/next equipment have stopped.