Training and simulation on a realistic production image, in-depth learning through haptic grasping
Optical and sensory applications, digital traceability with NFC/RFID
Integrated cloud connection, control via smart devices, as well as use and operation of dashboards
Remote monitoring via camera possible as well as linking of production and disposition data
Connection of upstream/downstream logistics processes
The digitally driven change in industrial production demands stronger networking and more intelligent information at all production levels. With the fischertechnik Learning Factory 4.0, these digitalisation activities can be simulated, learned and applied on a small scale before they are implemented on a large scale. A highly flexible, modular as well as cost-effective and robust training and simulation model that can be put to exceedingly good use. The fischertechnik learning environment is used for learning and grasping Industry 4.0 applications in vocational schools and training as well as for use in research, teaching and development at universities, in companies and IT departments. The simulation maps the ordering process, the production process and the delivery process in digitalised and networked process steps.
This consists of the factory modules storage and retrieval station, vacuum suction gripper, high-bay warehouse, multi-machining station with kiln, a sorting line with colour recognition, an environmental sensor and a swivelling camera. After an order has been placed in the dashboard, the workpieces pass through the respective factory modules and the current status is immediately visible in the dashboard. The integrated environmental sensor reports values for temperature, humidity, air pressure and air quality. The camera's vertical and horizontal swivel range allows it to see the entire plant, making it suitable for web-based remote monitoring. The individual workpieces are immediately visible in the dashboard. The individual workpieces are tracked by NFC (Near Field Communication): each workpiece receives a unique identification number (ID). This enables the current status of the workpieces in the machining process to be traced and visible. The workpieces are tracked by NFC (Near Field Communication).
The Learning Factory 4.0 is controlled by the fischertechnik TXT 4.0 controllers on a 9V basis, of which six are installed. These are connected within the factory according to the master-slave principle and communicate via an internal bus system. The complete performance data of the TXT 4.0 controller can be viewed at the TXT 4.0 Controller, here are the most important features:
4 fast count inputs: digital, frequency up to 1kHz
4 motor outputs 9V/250mA (max. 1 A): Speed infinitely variable, short-circuit proof, alternatively 8 individual outputs e.g. for LEDs
3 servo outputs 5V (max. 2A), short-circuit proof
Combined Bluetooth / WLAN radio module: Bluetooth 5.0 (BR, LE & EDR), WLAN dual band 2.4 GHz and 5 GHz 802.11 a/b/g/n
USB 2.0 client: mini USB socket for connection to PC
USB host interface: USB-A socket e.g. for fischertechnik USB camera or USB sticks
Camera interface: via USB host, Linux camera driver integrated in operating system
2x pin header 6-pin: for expansion of inputs and outputs (up to 9 TXT 4. 0 controllers can be coupled) as well as I²C interface
Integrated loudspeaker for playing sounds (WAV files
Linux-based open-source operating system, firmware update via cloud, USB stick or micro SD card
Programming with ROBO Pro Coding (graphical and Python), C/C++ compiler (not included)
further programming options via REST interface. Available output voltages 9V, 5V and 3.3V. Power supply: 9V DC socket 3.45 mm, or fischertechnik sockets 2.5 mm (for battery pack). Incl. USB connection cable and extension cable 6-pin.
Software: ROBO Pro Coding / Python programming interface
The software application is written in ROBO Pro Coding or in Python and is loaded onto the controller ready to start. The current versions of the corresponding programs can be imported directly into the ROBO Pro Coding platform via fischertechnik GitLab The ROBO Pro Coding / Python programs supplied can be modified and you can also write your own ROBO Pro Coding / Python programs for the Learning Factory. Furthermore, Node-RED on the TXT 4.0 controller provides a local dashboard with which the factory can be controlled as an alternative to the fischertechnik Cloud. This implementation can also be modified. Communication between Node-RED and the programme takes place using MQTT. MQTT (Message Queuing Telemetry Transport) is an open messaging protocol that enables the transmission of data in the form of messages between devices.
The TXT 4.0 controller, which is set as the master, is used to establish the connection to the fischertechnik Cloud via WLAN. We recommend using the Chrome or Firefox web browsers. The cloud can be used via a personal account that is created once (www.fischertechnik-cloud.com). The servers of the cloud are located in Germany and ensure that the strict European requirements apply to the storage of data. Personal data is protected in an account with password access that uses the very secure "OAuth2" industry standard. All data sent to the cloud is encrypted with certificates (https standard, green lock in the web browser).
The dashboard can be accessed and operated via mobile devices such as tablets and smartphones as well as on laptops and PCs. It enables the display from three different perspectives:
In the Customer view, a webshop interface with shopping cart is displayed, where one can order a workpiece and track the current status of the order in the shopping cart. This history is displayed on the interface for the customer so that they are informed about the status of their order. In the supplier view, the process for ordering the raw material is displayed and visualised. In the production view, the factory status, the production process, the stock level, the NFC/RFID reader and the sensor values can be queried. In addition, the camera that monitors the production line can also be controlled here. All these functions are controlled within a window and switched over via the menu. In the FID window, the NFC/RFID reader and the sensor values can be queried. In the factory status, the status of the respective module is visualised via a traffic light display. If a malfunction occurs in production, it is acknowledged via a button after the cause has been eliminated and production continues. In the Production Process view, the individual production steps are visually simplified by connected nodes. The respective active node (=production module) lights up green or red when the respective process step is live or there is an error waiting to be rectified. The production view Stock visualises the current stock of workpieces including minimum and maximum stock. A reorder point procedure is stored. This production view is for visualisation purposes only. The production view of the NFC/RFID reader displays the data of the workpiece and can be used to manually read or delete workpieces. The raw data from the NFC tags can be read by mobile devices with an NFC reader using a standard NFC app. Each workpiece has its own unique ID and maps the following data: Status, colour and timestamp from delivery to dispatch. The camera is also controlled via the production view and the read-out values of the environmental sensor can also be viewed here.