The fischertechnik learning environment is used for learning and defining industrial 4.0 applications in vocational schools and training as well as for 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 digitized and networked process steps.Factory imageThe learning factory consists of the factory modules for storage and storage, vacuum suction gripper, high-bay warehouse, multi-processing station with kiln, a sorting line with color recognition, an environmental sensor as well as a swiveling camera. Once raw materials have been delivered, storage is carried out in the high-bay warehouse and after ordering in the dashboard, the workpieces go through the respective factory modules and the current status is immediately visible in the dashboard.The integrated environmental sensor reports values for temperature, air humidity, air pressure and air quality. The camera sees the entire system through the vertical as well as the horizontal swivel range and can thus be used for a web-based remote monitoring.The individual workpieces are tracked by NFC (Near Field Communication): Each workpiece receives a unique identification number (ID). This enables the tracking and visibility of the current status of the workpieces in the machining process.ControlThe Lernfabrik 4.0 24V set comes with a PLC (brand-independent, not included) and includes a pre-written sample program (as structured text, ST). The program has been created on the basis of a Siemens S7-1500 (see “Downloads” on this page for details).The newly developed 24V adapter boards, as an interface to the PLC, are pre-assembled in the learning factory and are connected to the PLC via terminals. Among other things, you can use this latest generation of adapter circuit board- The encoder motors are controlled at the speed via PWM- There are push/pull output levels for photo transistors and buttonsIn addition, a fischertechnik TXT controller is installed. It is powered via the adapter board and connects to the fischertechnik cloud. In addition, the TXT controller communicates in MQTT to the IOT gateway (Raspberry Pi), which in turn translates into OPC UA to the PLC control. On the one hand, the 9V-based components such as the environmental sensor, the USB camera, the brightness sensor and the NFC reader can be addressed via the MQTT interface and read out from the PLC. More interesting, however, is another feature of the IOT gateway, namely the possibility of an optional connection to a separate cloud. Thus the Lernfabrik 4.0 offers maximum flexibility for the respective user.SoftwareThe PLC program for controlling the fischertechnik Learning Factory 4.0 was created as structured text (ST) on the basis of a Siemens S7-1500 and can be called up in the eLearning portal. It can also be viewed on Github.com/fischertechnik, used and downloaded free of charge. Naturally, the Lernfabrik can be set up with other PLC models and brands, and individual solutions can be programmed and implemented manually. It may then be necessary to make small adjustments to the sample program, which must be implemented independently.fischertechnik cloudVia the WLAN router included in the delivery and integrated in the learning factory, the connection to the fischertechnik cloud is established. It is recommended to use the web browser Chrome or Firefox. www.fischertechnik-cloud.com. Cloud servers are located in Germany and ensure that data storage is subject to strict European requirements. 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).2 dashboards, Raspberry Pi and node REDThe fischertechnik dashboard in the cloud can be accessed and operated via mobile devices such as a tablet or smartphone as well as by laptops and PCs. In addition, a local dashboard, created with Node RED, is implemented on the Raspberry Pi (IOT gateway), and it can also create its own dashboards via Node RED.The dashboards contained in the Learning Factory 4.0 allow platforms to be displayed from three different perspectives:- Customer view- Supplier view- Production viewIn the customer's view, a webshop interface with shopping basket is shown, on which one can order a workpiece and track the current status of the order in the shopping basket. This history is displayed on the interface for the customer so that they know the status of their order.The process for ordering the raw material is displayed and visualized in the supplier view.In the production view, the factory status, the production process, the inventory, the NFC/RFID reader as well as 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 via the menu.In the factory status, the status of the respective module is visualized using a traffic light display. If a fault occurs in the production, it is acknowledged via a button after the cause has been corrected and production is continued.In the Production process view, the individual production steps are shown visually simplified by connected nodes. The active node (=production module) lights up green or red when the respective process step is being processed live or an error is present and is waiting for resolution.The production view inventory shows the current stock level of the workpieces including minimum and maximum stock. An order point procedure is stored. This production view is used exclusively for visualization.The production view of the NFC/RFID reader shows the data of the workpiece and can be used to manually read or delete workpieces. The raw data of the NFC tags can be read from mobile devices with NFC readers using a standard NFC app. Each workpiece has its own unique ID and displays the following data: Status, color and time stamp from delivery to dispatch.The camera is also controlled via the production view and the values read out from the environmental sensor can also be viewed here.
This text is machine translated.