Cross-sectional technology for the All Electric Society

Automation means that technical systems perform tasks independently – especially rule-based, repetitive tasks that necessitate precision. This basic definition will remain valid in the future, while the requirements made by an All Electric Society (AES) are changing rapidly.

In the AES, where all sectors are electrified and networked, automation is central to efficient energy and data flows. Only automated processes enable energy to be controlled across all sectors: an electric car charges when renewable energy is available; a machine adapts its operation to the current supply.

Data plays a key role here. Forecasts for energy generation and utilisation serve to optimise process planning – from households to industry. When is the best time for the dishwasher to run? When should energy-intensive production steps take place? Such decisions are based on automated data analyses.

In a production line, the digital twin of a milling machine recognises that a subsequent machining step is temporarily blocked due to a tool change. Instead of stopping the entire line, the system draws on flexible skills: other machines automatically check whether they can take over the next production step. A suitable machine reports back capability and availability – and the process continues without interruption. In this way, the digital twin enables genuine, flexible and reconfigurable automation.

Conventional automation is designed for long, stable processes. Today, however, solutions are required for small batch sizes or frequent product changes – right down to batch size 1. The aim is to significantly reduce the effort required for customisation.

At the same time, programming is undergoing shifts and changes. While PLC programming still dominates in the industrial arena, high-level languages are taught at universities. High-level languages are modern programming languages featuring a higher level of abstraction. They are easier to read, object-orientated and enable faster, more flexible development than traditional PLC‑languages. Consequently, safety and real-time critical functions should remain on the PLC, while other tasks can be outsourced to high-level languages.

This separation not only facilitates the integration of new skilled employees, but also supports sector coupling. Standardised interfaces and high-level language-based functions can be used across all sectors.

The skill‑based architecture is a central component of this new automation world. A skill describes a clearly defined ability of an asset – for example, "drill hole", "grip component" or "start heat generation". Each machine encapsulates its skills in a standardised form and makes them available to the digital twin.

Key advantages:

• Skills make assets interchangeable – regardless of the manufacturer.

• Automation logic can be flexibly reconfigured.

• Machines can decide for themselves whether they are able to perform a task – or pass it on to another asset.

In this way, skill‑based architectures form the backbone of highly flexible, networked automation.

Many components for modern automation already exist: image processing, multi-agent systems, automated control systems. But reliability remains the key challenge - especially for AI‑systems.

As opposed to consumer‑applications, 85 % accuracy is totally unacceptable in industrial processes. An incorrectly classified component, faulty recognition or a probabilistic decision can incur production downtimes, quality losses or safety risks.

Reliability therefore entails

• Stable AI‑Models with traceable decisions,

• Valid and complete training data,

• Certifiability with regard to standards, safety‑requirements and liability regulations.

AI can do a lot today – but safe, verifiable reliability in complex production environments has not been fully achieved to date.

The vision of a fully skill‑based, AI‑supported, universal automation landscape will not materialise in the span of 3 to 5 years, but rather within a period of some 10 to 15 years. This time horizon is realistic in order to establish standards, certifications, data quality, industrial adoption and technology integration.

Along with advancing electrification, the significance of connectivity is also on the rise. Connectors secure the power supply and data transfer – and become intelligent interfaces that can be used to record energy consumption, for example. If a connector fails, the system comes to a standstill. Their role as the backbone of modern automation will certainly continue to grow.

Automation remains the right term – but calls for advanced, leading-edge technologies and not the solutions from the past. The future of automation lies in flexibility, data expertise, reliability, skill‑based architecture and universal connectivity – and represents the central cross-sectional technology of the All Electric Society.