Weidmüller is committed to supporting its customers on the journey from data acquisition to business model. The new slogan "Enabler from Data to Value" reflects this. The Detmold-based company has defined four stages to achieve this: Data acquisition, data pre-processing, data communication as well as data analysis and business logic. Weidmüller is building and expanding a suitable product portfolio along these four points.

Enter data in the field

The company has developed the u-sense sensor series for data acquisition in the field. As one of the first representatives of the series, u-sense vibration monitors motors, gears and pumps. It records mechanical parameters as well as temperature and other electrical variables. The sensor module in an IP66/IP67 housing is connected directly to the rotating device to be monitored by means of an adapter plate or a borehole and detects vibrations in accordance with ISO 10816. The measuring range covers 2 to 16 g at a sampling rate of 1 kHz. Wiring is not required. If there are deviations from the standard behavior, the sensor module reports this to a higher-level unit via Bluetooth Low Energy 5.0. Data preparation, i.e. pre-processing, already takes place in the sensor module. An AA battery, which can be replaced, serves as the power supply. The sensor works at ambient temperatures from -20 to +85 °C and has FCC, cULusx, ATEX, IECEX (Zone 2 / 22) certificates.

Forwarding the right data

Data provides important information in the production environment and usually finds its way into an ERP system without detours via gateways. Pre-selection is crucial to ensure that this is not flooded with irrelevant data. The data pre-processing itself takes place at different levels depending on the effort and performance requirements: directly in the sensor module, in the gateway or in the IPC. However, the data must also be visualized. This is where HMIs (Human Machine Interfaces) come into play, enabling simple visualization and operation on any end device.

With u-create Procon-Web, an HMI/SCADA software, dynamic user interfaces can be parameterized and configured. It is based on open and manufacturer-independent web platforms such as HTML5, CSS3 or JavaScript. The system is configured in the browser. This not only makes it possible to use different end devices, but also has the advantage that the software does not need to be installed on the client.

Web-based systems are also an interesting tool for remote maintenance. Remote access applications enable service technicians to get a remote picture of the problem if necessary. With u-link, Weidmüller offers a tool with which secure access to machines and systems can be guaranteed and which also enables efficient management of production systems, user clients, access rights or firmware versions. If a user wants to access a system remotely, various steps are carried out in the background. A VPN client is installed on the user's computer, which is used to establish a secure, outgoing connection with a meeting point server (cloud server) (step 1). A VPN tunnel is also established from an industrial security router to a meeting point server (step 2). Both tunnels are connected internally (step 3) and the user is virtually connected to the network. Via the web-based u-link portal, the user can now view the system visualization and parameters of the control system and identify at which program step, for example, a machine has failed.

Added value from data analysis

In order to generate added value from data, it must be analyzed and interpreted. Artificial intelligence or machine learning plays a central role in this context. As not every company has a data scientist on hand, Weidmüller has developed an industrial automated machine learning tool. This enables domain experts, i.e. an application specialist, to develop ML solutions independently without specific knowledge in the field of data science.

The software essentially provides the user with two modules. With the "Model Builder", the domain expert can create ML solutions for anomaly detection, classification and error prediction. In the second module, the AutoML software, the models are executed on the machine - on premise or cloud-based - in the runtime environment.