Industrial Automation - Smart Factory to increase efficiency

In the course of industrial automation, the manufacturing industry is developing digital strategies to optimize communication between people, machines and systems. Automated production enables the smart factory to improve efficiency through its self-adaptive adaptability, for example, by processing smaller batch sizes.

Innovative concepts such as digital twin space, resilient software architectures, smart sensors and predictive maintenance are used as part of the digitalization of processes. This allows for more efficient maintenance and increased efficiency, which enables the smart factory to maintain operations even in the event of component failures or changing environmental conditions such as material quality, tool wear or unexpected logistics goods.

Great expectations are also placed on artificial intelligence to increase efficiency and ensure sustainable, resource-conserving production. In particular, the vision is for the automated smart factory to function in a resilient and sustainable manner. The implementation of this new, holistic digital strategy requires new approaches to flexible and self-organized automation for production systems.

No contradiction: technology and people work hand in hand

In addition to social challenges such as the increasing shortage of skilled workers, industrial production is currently experiencing a paradigm shift - also driven by European Union measures to promote the digitalization of processes and digital strategies under the umbrella term "Industry 5.0": people are seen as an integral part of the system and the production chain and are being placed at the center of automation. This is because when experts are relieved of manual or repetitive tasks, expertise can be deployed where it delivers the greatest added value.

Although technology-driven change is often said to make people obsolete, the need for a close connection between man and machine is particularly evident in approaches to reliable, human-centered automation. This innovative human-machine interaction, such as with safe and adaptive cobots in an intelligent factory, requires reliable perception of objects and the environment and self-optimizing cyber-physical systems - while at the same time ensuring safe and robust integration of the individual components.

To this end, Fraunhofer IKS develops solutions in which system automation interactively adapts to individual people, taking into account their capabilities and measurable performance levels. Our aim is to offer efficient, reliable and safe solutions for the manufacturing industry of the future.

In reliable, human-oriented automation, artificial intelligence plays a decisive role in the digitalization of processes. In order to increase the level of autonomy in production processes and prevent risks for people, Fraunhofer IKS is working on AI-based solutions to reliably and resource-efficiently detect people and objects. This allows skilled workers to easily stay in control of autonomous production processes and, thanks to the flexibility this brings to their day-to-day work, apply their skills where they are most needed.

Advanced algorithms and machine learning can be used to recognize human behavior and patterns in the production process to implement and adapt automated, digital processes accordingly. This enables adaptive and reliable automation that integrates seamlessly into the workflows of the manufacturing industry, increasing efficiency and ensuring safety at the same time.

Fraunhofer IKS Automation Focus topics of the digital strategy

As a pioneer for safe, intelligent cognitive systems for production automation, Fraunhofer IKS focuses on the following topics:

Flexilient automation

In the area of flexilient automation, we adapt production systems so that they can react quickly and efficiently to dynamic requirements. This includes the implementation of adaptive automation solutions that enable retooling and adaptation to make the production process more flexible and resilient. 

Reliable Human Centered Automation

Reliable Human Centered Automation ensures that automation systems in the manufacturing industry interact closely with the needs and capabilities of users to increase efficiency. Advanced AI algorithms and machine learning make it possible to adapt automated, digital processes to the individual preferences and behaviors of users. We offer a variety of services to implement these focus topics, including consulting on the use of digital twins, support with the integration of AI into the smart factory and the development of innovative concepts at various levels of production for the digitalization of processes.

Safe Person Detection

As part of Safe Person Detection, the combination of ML components and safety concepts enables the comprehensive and reliable detection of objects and people based on a wide range of sensor data, for example, on the shop floor where a hybrid human-machine working environment poses certain challenges.

Flexible Quality Inspection Systems

With Flexible Quality Inspection Systems, we are also redefining quality assurance. Companies can benefit from low-code engineering systems with data-efficient approaches such as concept learning throughout the production lifecycle. Sensors can detect errors at an early stage and take countermeasures. The resulting flexibility of the inspection systems means that inspections can be reliably generated and adapted even for smaller production batches and varying raw materials.

Automation Systems as a digital strategy - Fraunhofer IKS service portfolio

We aim to increase efficiency in the manufacturing industry by prioritizing the importance of human needs and values. By adapting processes and software solutions and promoting flexible and adaptable automation, we help to create a working environment that is in line with the values of the manufacturing industry's digital strategy.

Our services include:

  • Development of a system for reliable product quality testing that offers flexibility and adaptability for different production requirements.
  • Integration of novel techniques, including machine learning, into production processes.
  • Advice on the use of digital twins and SW architectures.
  • Advice on the use of cognitive systems in the automation framework, including engineering, SW architectures, digital twins, ML use, new programming, cooperation and operating concepts.
  • Support in the development of adaptive human-centered interaction concepts.
  • Use of a low-code engineering system for reliable person and object recognition.
  • Help with the development of human models for virtual validation and dynamic adaptation to human users.
  • Consulting and support in the design of human-centered machines / robot behaviors, including subject studies.
  • Advice on solutions with AI-based self-organization and optimization of automation.

Safeguarding autonomous mobile robotic systems

Fraunhofer IKS and Magazino GmbH are conducting the research project “RoboDevOps – Continuous development and safeguarding of autonomous, mobile robotic systems” to research new DevOps concepts and evaluate them based on specific scenarios.


Cloud-Based Production Controls

In the Cloud-based Industrial Services (CICS) project the Fraunhofer IKS researchers shape the production steering to be interoperable and flexible, by transferring part of it into the cloud.


Simple AI integration for Industry 4.0

In the joint project REMORA, Fraunhofer IKS works on the simple integration of AI services in Industry 4.0. Its goal is to simplify the integration of AI for the real-time analysis of machine data and to develop tools for high-quality, dynamic machine data.


Infrastructure sensors for safe, automated forklifts

Together with Hitachi, Fraunhofer IKS has investigated whether infrastructure sensors increase safety in a warehouse with automated forklifts. To do this, the researchers created a simulation framework for the movements of automated guided vehicles in warehouses based on Webots.


Industry 4.0:
Blog articles

Would you like to learn more about our research on Industry 4.0? Then take a look at our blog. Here you will find all blog articles regarding Industry 4.0.