In the welding process of the future, everything will be connected. The welding control system is a key element here. In order to allow it to be connected to and communicate with other devices and systems, middleware in the form of a hardware gateway has often been used in the past. Thanks to Bosch Rexroth, this intermediate device is no longer necessary: the intelligence is integrated directly into the PRC7000 welding control system. As a result, an Industry 4.0-capable “all-in-one” solution, the first of its kind on the market with the MQTT and OPC UA protocols fully integrated, is now available for resistance spot welding. This reduces costs and ensures that connectivity requirements can easily be met. On this basis, AI applications for example are possible too.
Huge quantities of data are produced during the welding process. These data can form the basis for process optimization, machine learning and value creation in Industry 4.0. However, they need to be collected, analyzed and further processed first. This is the only way to produce detailed information which is relevant for decision-making purposes and automatically defined actions can then be initiated.
Via the OPC UA protocol, data can then be sent to the cloud and analyzed and feedback can be output to the control system. On this basis, applications with machine learning or artificial intelligence (AI) for example are possible. By collecting and analyzing data, the right conclusions can be drawn for the purposes of machine learning. Improvements can be made and quality control costs can be reduced significantly.
The OPC UA open communication standard is becoming increasingly important in digital factories. It is one of the most important communication protocols for the IoT and is now becoming the industry standard. OPC UA can not only transport machine data – it can also describe them semantically in a machine-readable manner. This supports AI and machine learning applications.
With the PRC7000 welding control system, Bosch Rexroth offers the first solution of its type on the market with fully integrated OPC UA. More and more automotive manufacturing companies are demanding this – along with use of the MQTT open network protocol.
In addition to the OPC UA server, an MQTT publisher is fully integrated into the PRC7000. Both are available as licensed software. MQTT is designed for environments with a low bandwidth and high latency. It is ideal in situations where enormous quantities of data need to be sent in packages. With a control system for example, up to 30,000 welding spots a day can be recorded and the data transmitted. The control system transmits the data in JSON format – a text-based, self-describing format which can be interpreted by people.
Another JSON-based protocol is PPMP, a new, open industry standard developed by Bosch for exchanging data in connected industry. With PPMP, manufacturing execution systems (MES) such as the Nexeed Production Performance Manager (PPM) from Bosch can be connected. Previous welding control systems were not designed to implement protocols such as OPC UA and MQTT as they were not powerful enough. Middleware or gateway software, which may or may not have required hardware of its own, had to be provided between the device and the edge or cloud layer. The data were collected, aggregated and sent off by the middleware.
With the PRC7000, there is no need for any intermediate hardware because OPC UA and MQTT are integrated directly into the control system. Data integrity is crucial for the automated factories of the future. It must therefore be possible to encrypt data on a certificate basis.
With the MQTT and OPC UA interfaces, the new PRC7000 welding control system offers the IoT connectivity needed for Industry 4.0. However, it has other capabilities when it comes to connectivity and intelligent applications too. As a piece of high-performance hardware, the PRC7000 offers the performance needed to replicate AI use cases.
The PRC7000’s Industry 4.0 functions support numerous use cases and new business models. With OPC UA access, small machine manufacturing companies can easily develop and provide their own user interface. Alternatively, trends in system downtimes or the causes of faults can be identified and predictive applications can be put in place as a basis for optimizing processes and reducing costs.