Although most machine operators and builders have a precise idea of their desired application, very few have the training to program the applications themselves. With low-code tools, non-programmers can now create their apps and digital services. This is made possible by so-called low-code platforms, which support development with visual user interfaces and other graphic modeling methods instead of using classic text-based programming languages.
A lack of budget, internal know-how and a high level of development effort – according to a recent survey by the market research company IDC, are three of the biggest obstacles to the Industrial Internet of Things (IIoT ). Medium-sized machine builders, in particular, often see the advantages of data-supported processes and new digital business models but fear high initial investments and long development phases. As a result, IIoT initiatives in companies often progress slowly or need to be started. As the most important raw material for the IIoT, data is plentiful.
This is made possible by the high degree of automation and networking in medium-sized industrial companies. Almost all machine builders now use Ethernet-based communication protocols to connect their programmable logic controllers (PLC). This way, many machine data and measured values can be collected and made available via corresponding interfaces for real-time analysis. Companies do not have to employ their programmers or hire external service providers to convert this data into added value for the company and its customers. With low-code tools, the employees in the specialist departments can create their apps and configure them precisely according to their requirements.
How Mechanical Engineers Turn Ideas Into Data-Based Apps
Low-Code offers a visual interface with which users can very easily define functionalities of applications based on graphic editors with predefined templates and function modules. Similar to a construction kit, users can flexibly combine the individual elements and thus create a large number of tailor-made applications. The employees’ ideas are then automatically translated into program code. Machine and plant manufacturers are thus able to build their data apps based on machine data in the shortest possible time and thus offer digital value-added services for their products.
This can be, for example, visualizations of key figures, monitoring dashboards for 24/7 monitoring or even complete machine learning workflows. The advantage of the low-code concept: The apps are developed directly by the specialists who know the machines best. The often time-consuming detour via internal or external IT experts, who were previously responsible for the creation, is largely eliminated. Thus, IT departments can concentrate on their core competence: the control of digital company processes.
Low-Code-Based IIoT Platforms
If digitization proceeds at the same speed as before, a machine’s added value could soon shift to the data area. Industrial IoT platforms form the ideal basis for this because they connect the machines to the Internet. With the help of suitable tools, users can now access their systems and get a precise insight into their machine data. Based on the data, which can be called up around the clock, they can, for example, analyze very precisely which error messages have occurred in which context and when.
Platform-as-a-Service solutions are particularly suitable for implementing Industrial IoT projects. The architecture was consistently designed based on a low-code strategy and provided users with many tools for generating their applications. The machine data is read directly from the database using simple graphic operations. Users can perform an initial statistical analysis supported by functions such as data filtering, grouping, sorting or aggregation. Users can then switch to a data app builder using parameterized dashboards and graphical widgets to create their data-based apps.
The more in-depth analysis of the machine data then takes place in a so-called low-code formula editor, Low code tools can also be used for machine learning applications to make precise predictions, provided the IIoT platform offers in-product, real-time capable, AI-supported development. Based on graphical interfaces, users can create and train their machine-learning algorithms and later identify typical patterns in the alarm data.
Intelligent Monitoring And Needs-Based Maintenance
There are several use cases for intelligent low-code platforms. Companies often use them for real-time monitoring and predictive maintenance of the systems. For example, service employees use a simple graphical interface to put together monitoring boards using drag-and-drop. These bring together the measured values recorded by sensors in the networked systems – such as temperature, vibrations, material jams, capacity utilization, or wear and tear. With just a few clicks, limit values can be set that automatically trigger certain actions.
For example, if a set temperature is exceeded, the machine sends a notification by email or SMS. Based on intelligent low-code platforms, the experts in the specialist departments can not only create tailor-made applications but also evaluate the status data accordingly and thus achieve greater efficiency along the entire value chain. As a supplement to text-based programming, low-code platforms have the potential to advance digital transformation in companies decisively.
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