18547878. CONTROLLER simplified abstract (FANUC CORPORATION)
Contents
- 1 CONTROLLER
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CONTROLLER - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Tension Estimation without Sensors
- 1.13 Original Abstract Submitted
CONTROLLER
Organization Name
Inventor(s)
CONTROLLER - A simplified explanation of the abstract
This abstract first appeared for US patent application 18547878 titled 'CONTROLLER
Simplified Explanation
A controller uses data to create machine learning data for estimating tension in a conveying section of an industrial machine without a tension sensor.
Key Features and Innovation
- Acquires data on mechanical configuration, workpiece, and operating condition.
- Creates machine learning data for tension estimation.
- Adjusts tension in the conveying section based on designated conditions.
- Enables tension adjustment without a tension sensor.
- Improves operational efficiency and accuracy.
Potential Applications
This technology can be applied in various industrial settings where precise tension control is required, such as manufacturing, material handling, and assembly processes.
Problems Solved
This technology addresses the challenge of accurately estimating tension in a conveying section without the need for a tension sensor, leading to more efficient and cost-effective operations.
Benefits
- Enhanced operational efficiency
- Cost savings by eliminating the need for a tension sensor
- Improved accuracy in tension control
- Increased productivity and reduced downtime
Commercial Applications
- Manufacturing automation systems
- Material handling equipment
- Conveyor systems
- Assembly line machinery
Prior Art
Readers interested in exploring prior art related to tension estimation in industrial machines without sensors can start by researching machine learning applications in industrial automation and tension control systems.
Frequently Updated Research
Stay updated on advancements in machine learning applications for industrial automation and tension control systems to leverage the latest technologies for improved operational efficiency.
Questions about Tension Estimation without Sensors
How does this technology impact industrial automation processes?
This technology significantly improves operational efficiency by enabling accurate tension control without the need for a tension sensor, leading to cost savings and increased productivity.
What are the potential cost savings associated with using this technology?
By eliminating the need for a tension sensor, companies can save on equipment costs and maintenance expenses, contributing to overall cost efficiency in industrial operations.
Original Abstract Submitted
A controller acquires data related to a mechanical configuration, data related to a workpiece, and data related to an operating condition of an industrial machine, and creates machine learning data used for processing of machine learning based on the acquired data. A command is given to perform processing of machine learning for estimating data related to tension in a conveying section of the industrial machine based on the created machine learning data. Then, processing of machine learning for estimating data related to tension in the conveying section is performed based on this command. In this way, the controller can adjust tension of the conveying section according to a designated condition during actual operation without a tension sensor.
