Smart conveyerbelt training equipment

Model: FT – BC025A

  • AI convergence training equipment built a smart factory, which has
  • structure for application implementation and provides connectivity
  • Simulation environment scaled-down conveyor automatic sorting system to be placed on a table
  • HMI with built-in touchscreen to enable sensor and actuator control inGUI environment
  • Machine learning-based classification and data processing experimentally
  • scalable using HMI and AI accelerator
  • Low-level and high-level control possible through MicroPython, Python, Pop plus library
  • Precise conveyor belt speed control using DC motor and driver
  • Accomplishes sophisticated classification quickly reading opticalsensor-based object detection
  • Simplifies complex supply and classification operation using servo motor
  • Provide a user-friendly interface with GUI designed on PySide6
  • Support ModBus and OPC-UA that can be integrated with PLC
  • Practice with real results by detecting and classifying objects on convoyor
  • Similar functions implemented at lower cost as PLC equipment
  • Flexible scalability provided by actively utilizing open-source technologies such as OpenCV and MQTT
  • Support dashboard and remote monitoring through open source IoT
  • platform, analytics and interactive visualization tool
  • Restore data remotely and interacts with cloud collaboration system and
  • Internet messenger in case of error
  • Support factory workflow and performance analysis through real-time data dashboard and graph
  • Add new sensors and actuators easily through software modularization

Description

Smart conveyerbelt training equipment

Technical Specification :

Hardware Specification:
HMI (Human Machine Interface)
Edge Processor
Min_3.4GHz Quad-core 64-bit Arm Cortex-A76 CPU
512KB per-core 12 caches, 2MB shared 1.2 cache
IPDDMK 4227 SDRAM
Dual-band B02.11ac Wi-Fi98, Bluetooth 5.0 / Bluetooth Low
Energy (BLE)
AI Accelerator:
Providing 26 TOPS in influencing performance
Compatible with popular frameworks such as Tensor Flow and PyTorch
Utilizing the neural network accelerator for executing post
processing tasks like
object detection, image segmentation, and pose estimation.
Min.2inch TFT LCD:
IPS,Resolution:1024×600
Capacitance Touch Screen
2ch Speaker
Min.2MP Camera:
Resolution:1080p@30 fps
Field of View:120 degrees diagonal
Convoyer Block:
Auto Controller:
Equipped with dual Cortex-M33 or RISC-V Hazard3 cores that
operate at fequencies reaching 150MHz
520 kB of high-speed multi-bank SRAM
External Quad-SPI flash featuring execute in place capability
alongside a 16kB on-club cache
Safety Block:
Stop Switch- Emergency Power Control for the
Convoyer Block:
Start Switch-Metal / LED Activation
Transfer Block:
Block for product transfer.
DC Motor equipped with an Encoder
Feeding Block:
Block for stacking products and managing supply
Photo Frequency Sensor 1 unit
Serial Bus Servo Motor:1 unit
Processing Block:
Block designed to manufacture the product Stamp (Pew) securing
device
Photo Flexiantly Sensor 1 unit
Serial Bus Servo Motor:1 unit
Sorting Block:
Block responsible for identifying and categorizing products as
either metal or non-metal
Inductive Proximity Sensor:1 unit
Photo Proximity Sensor:3 units
Serial Bus Servo Motor:1 unit
Power:12V/10A Adapter
Machine Holder
Quantity:2
MATERIAL:Compressed Wood panels with laminated melamine
surface
Dimension(mount):24/6X37/0X250 mm
Top surface around:16 mm Laminated board 16 mm top visual
with 1mm edging
Color: BlackWhiteWooden and etc
Surface shaft be scratch proof
Base: Cold rolled Mild Steel tubular frame or Made with
heavy-duty mild steel
PVC be stopper for floor protection
Paint:Mild steel part protected with powder coating heat paint
PVC edge banded with hot melt glue to protect moisture painting
Phosphatized and Ova baked powder paint finish for anti-watt and
longevity
Anti-insects chemicals added to make the board termite-proof
Assembly required
Software Specification:
HMI:
Linux Kernel:aarch64 6.x
Cloud & Connectivity:S$H Server, Huex,Mosquitto,S2M Bridge
Server,OPC-UA
Server: Modbus Server
GUI & Vision: PyStick, OpenCV
Data Science & AI: Natropy, Pandas, SciPy, Seaborn, Scikit-learn,
Mediapipe
Security: SSL/TLS, MQTT, J2A, ALSKDF
Pop plus Library (HMI): Actuator Object: Feeding, Transfer,
Processing, Sorting, Security
Sensor Object: Photo Proximity, Inductive Proximity, Encoder,
Stop Switch
AI: Linear Regression, Logistic Regression, Perceptron, ANN
Auto Controller:
Embedded Runtime: RFFL, Garbage Collection, PIO, Littlet’S,
CDC, MQTT
Pop plus Library (Auto Controller):
Actuator Object: Feeding, Transfer, Processing, Sorting, Security
Sensor Object: Photo Proximity, Inductive Proximity, Encoder,
Stop Switch

Accessories:

Single-phase power cord
4mm Banana Socket-1Set
User Manual

Others:

Brand: FaboTronix
Country of Origin: China, taiwan, japan.
Manufacturing: Assemble in Bangladesh
Training

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