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5 THings your PLC can't do but should


Marcel Luhmann

Technology Manager


In current time it's hard to find skilled staff for automation engineering. The challenges in automation are getting more and more complex. The way to meet these challenges is equally complex and different than in the past. Due to the complexity, automation engineers get an even wider range of tasks like maintenance and support.

5 THings your PLC can't do but should


Zachary Stank

Product Manager Control, Safety, I/Os


Programmable logic controllers (PLCs) are extremely common across a variety of industries, including manufacturing, oil/gas, and transportation. Essentially, they are just another type of computer. Though they differ from PCs in many ways, Machine Design provides a succinct definition that highlights their differences: “a programmable logic controller is a digital computer designed for automation and industrial controls. It was created to resist to a wide range of operating conditions, including temperature, pressure, electrical noises, and vibrations. The most important feature that truly led to its success is that it is a hard real-time system.”

A PLC collects inputs, analyzes them with its internal logic, and then creates outputs based on that analysis. It repeats this cycle ad infinitum, all the while withstanding harsh environments. This makes PLCs dependable tools, and so businesses around the world rely on them in production environments.

Everything, however, has a limit. PLCs are no different. In fact, as we move towards Industrie 4.0 with the Industrial Internet of Things (IIoT), these limitations are becoming even more pronounced.

These are the top five things that PLCs can’t do.

Safety and Industry 4.0


Steffen Horn

Master Specialist Safety Technology, PLCnext Technology


Functional safety is a property of a machine or system that guarantees that it does not pose an unacceptable risk to human health during operation. Dangers can arise, for example, at direct physical human-machine interfaces due to unforeseeable or undetected technical faults in the machine. Organizational and technical measures of functional safety are designed to avoid systematic errors during development and to detect and control random errors (e.g. due to hardware failures) during operation at an early stage. This article describes the challenges related to industry 4.0 and the resulting opportunities for functional safety, based on the principles of functional safety and its design principles.

Anomaly Detection


Alexander von Birgelen M.Sc.

Software Engineer


No manual programming of complex rules and algorithms


In automation, the use of machine learning is becoming increasingly widespread, with the application often focusing on already familiar subject areas: Condition Monitoring (CM) and Predictive Maintenance (PM). In a use case, data from normal plant operation is used to learn a model that, compared with live data, indicates anomalies and indicates wear.

Hello world


Anne Breuer, M.A.

PLCnext Technology  / Technical Documentation


A virus shakes the world and the world as we know it is now a different one. The changes affect our everyday life, our work and private life, our plans for the future and sometimes our view of the past. We are facing new challenges. Challenges for which we do not yet have solutions. What really matters now is above all: technology and kindness.

The basics of Cloud Computing


Christian Vilsbeck


Applications with AI


Artificial intelligence can be used very quickly and easily for the quality control of products. There are ready-to-use AI-based software solutions that evaluate image material from industrial cameras in real time. Based on the images, the AI system learns what the product looks like in ideal condition and which tolerances and irregularities are still permissible. In this way, even the smallest scratches or deviations are reliably detected. Compared to manual inspection by employees, which requires high concentration and is tiring, the error rate can be significantly reduced and the inspection throughput increased.

The basics of Cloud Computing


Christian Vilsbeck



Modern machines and production facilities supply vast amounts of data. The art lies in generating added value from this information. With artificial intelligence, correlations can be formed and processes can be optimized by self-learning. To do this, however, mechanical engineers and plant operators need a future-proof technological basis on which they can introduce their AI competence step-by-step and in a scalable manner. A powerful and open control platform is the basis for the implementation of artificial intelligence.

The basics of Cloud Computing


Arno Martin Fast, B.Eng.,

Product Manager Digital Services


Cloud-native vs. cloud-agnostic: What's the mystery behind the hype?


Speed seems to be the order of the day in digitization. Service providers and customers seem to compete with each other in this digital space. We see huge, successful solution providers switching from rigid monolithic structures to loosely coupled, service-oriented architectures. Cloud-based solutions along with API-based communications and container-centric applications seem to have helped with this transition. For some time now, cloud vendors, especially the best-known ones like Amazon, Microsoft Azure and Google Cloud, have been driving business processes worldwide. As the technology matures, the company's business processes are now asking which cloud platform is more efficient, what could be easily maintained, which option is potentially more advantageous in the long run. At this point, the question arises: cloud native or cloud agnostic? This is where companies decide whether to stick to one vendor or be present in all clouds.

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