XV-102-B3-35TQR-10-PLC Human Machine Interaction

XV-102-B3-35TQR-10-PLC Human Machine Interaction

Brand: EATON

model: XV-102-B3-35TQR-10-PLC
The main features of a touch screen include:

Easy to operate: Users can directly operate on the screen without using a keyboard or mouse.

Intuitive: Through a graphical interface, users can intuitively understand the operation content and results.

Multifunctional: Touchscreens can integrate multiple functions such as display, input, control, etc., making devices more compact and efficient.

Aesthetics: The appearance of the touch screen is beautiful and can enhance the overall image of the device.

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  • Email:sauldcsplc@outlook.com
  • Phone:+86 18350224834
  • WhatsApp:+8618350224834

Description

XV-102-B3-35TQR-10-PLC Human Machine Interaction

XV-102-B3-35TQR-10-PLC Product Introduction
  • 32-bit DSP digital control mode
  • Low vibration, low noise, low power consumption
  • Maximum output current 3A/phase
  • Adopting CAN bus and supporting standard CANopen communication protocol, it can load up to 127 devices
  • Supports three modes: protocol position control, speed control, and periodic position control
  • Current setting, subdivision, motor start stop control, and real-time monitoring of motor operation can be achieved through the bus
  • 2-channel optoelectronic isolation programmable input interface
XV-102-B3-35TQR-10-PLC has a small size, high cost-effectiveness, convenient networking, and simple wiring. It can be widely used in industries such as textile machinery, laser processing machinery,
medical equipment, various types of robots, robotic arms, automated production lines, and various CNC machine tools.
The XV-102-B3-35TQR-10-PLC series servo drive is a universal servo drive.
Can be used in conjunction with various PLCs, CNCs, motion controllers, and computer boards,
Or it can be combined with XVS-440-10MPI-1-1U series drivers to form a multi axis control system through the DBUS bus.
It has the characteristics of high positioning accuracy, fast response, high reliability, and simple use.
Product features:
The servo motor encoder can be selected with 20BIT, 17BIT resolution, and comes standard with 2500 wires.
The pulse input frequency can reach 4MPPS. The speed frequency should reach 1200Hz. Overload can reach three times.
Customized parameter factory settings enable the servo system to be “plug and play”.
Enhanced vibration suppression function improves the system”s responsiveness.
Inertia automatic identification, after identification, most of the parameter settings can reach the optimal state.
Built in 24V power supply, built-in 1.2K resistor, no series resistor for upper computer position command, more convenient for on-site application.

Contact Us
 
Mobile phone: 18350224834
 
E-mail： sauldcsplc@outlook.com
 
WhatsApp：+86 18350224834

0 PrefaceGermany”s “Industry 4.0″ and the United States” “Industrial Internet” will restructure the world”s industrial layout and economic structure, bringing different challenges and opportunities to countries around the world. The State Council of China issued “Made in China 2025” as an action plan for the first ten years of implementing the strategy of manufacturing a strong country, which will accelerate the integrated development of IoT technology and manufacturing technology [1]. IoT collects data on machine operations, material usage, facility logistics, etc., bringing transparency to operators. This transparency is brought about by the application of data analytics, which refers to the use of statistical and machine learning methods to discover different data characteristics and patterns. Machine learning technology is increasingly used in various manufacturing applications, such as predictive maintenance, test time reduction, supply chain optimization, and process optimization, etc. [2-4]. The manufacturing process of enterprises has gradually developed from the traditional “black box” model to the “multi-dimensional, transparent and ubiquitous perception” model [5].1 Challenges facing manufacturing analysisThe goal of manufacturing analytics is to increase productivity by reducing costs without compromising quality:(1) Reduce test time and calibration, including predicting test results and calibration parameters;(2) Improve quality and reduce the cost of producing scrap (bad parts) by identifying the root causes of scrap and optimizing the production line on its own;(3) Reduce warranty costs, use quality testing and process data to predict field failures, and cross-value stream analysis;(4) Increase throughput, benchmark across production lines and plants, improve first-pass rates, improve first-pass throughput, and identify the cause of performance bottlenecks such as overall equipment effectiveness (OEE) or cycle time;

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