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fischertechnik Agile Production Simulation

fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
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fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation
fischertechnik Agile Production Simulation

fischertechnik Agile Production Simulation

fischertechnik Agile Production Simulation 24V incl. 5x PLC S7-1200 and Digital Twin

Top Features
Modular production
Digitality in the production environment
Quality control with artificial intelligence
Automated guided vehicles
Digital twin
Automation and PLC programming

Efficiency, agility and flexibility are indispensable in the construction of current and future factories.

fischertechnik now presents a training model of such a flexible and modular factory - the Agile Production Simulation. The factory consists of individual modules such as incoming and outgoing goods, high-bay warehouse, milling station, drilling station, quality assurance with AI. A driverless transport system flexibly transports workpieces between the individual stations and ensures a flexible production process that can be adapted to customer requirements. The factory can be expanded to include a kiln, additional drilling or milling stations and also additional driverless transport systems.

Each workpiece contains an NFC tag on which production data is written (colour of the workpiece, time of delivery, time of storage and retrieval, production steps carried out, quality inspection carried out). The differently coloured workpieces (white, red, blue) go through different production processes and thus pass through different stations in the factory and have different throughput times.

The factory is controlled by a central controller (Raspberry Pi 4 Model B), which is networked with the controllers of the individual factory modules, PLC Siemens S7 1200 in the 24V version. The central control communicates via the standardised AGV interface VDA 5050 and controls the transport orders for the AGV. The MQTT protocol (Message Queuing Telemetry Transport) is used for communication.

The factory is also connected via a WLAN router to the fischertechnik Cloud, which contains an online shop for ordering workpieces by the customer. Furthermore, dashboards are available for order control, visualisation of the factory status and determination of key figures. To simulate remote maintenance, the images taken by the moving camera in the factory are displayed in the dashboard so that the condition of the factory can be viewed remotely.

Physically, the base plates of individual modules of the factory are connected to each other via a tongue and groove principle to form a coherent base plate. Further modules can be added at the open ends and configured in the dashboard.

The accompanying didactic material offers a detailed introduction to the handling of the factory as well as extensive teaching material. Contents include the basics of Industry 4.0, modular production, intelligent networking, human-technology organisation, Digital Twin, sensor data evaluation in real time and much more.

Content
• Power supply 24V power supply unit 11A
• 1x central control Raspberry Pi 4B
• 5x PLC Siemens S7-1200
• 3x TXT 4.0 controller (1x for sensors and camera as well as cloud access in WE/WA module, 1x for quality assurance with AI, 1x for AGV)
• 1x WLAN router for WLAN network
• Software: PLC programs (structured text)
• JavaScript for central control on the Raspberry Pi
• No-de-RED for communication between PLC and TXT 4.0 controller
• Python for programs on TXT 4.0 controller
• Tensorflow for supervised learning in quality assurance with AI


e-Learning

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