Factory software LSWI

Factory software

Key areas: Industry 4.0, Hybrid Simulation, Industrial Internet of Things, Manufacturing Analytis, Research and Application Center Industry 4.0

The Industry 4.0 challenge and our research goal: Factory software

We are in the middle of the 4th Industrial Revolution. But the transition from the theoretical approaches to the practical phase still poses a major challenge for many companies. In the course of the digital transformation, they are faced with the task of harmonizing current processes with future strategies, parallel to their everyday business. In this context, factory software has the task of adequately transferring these new ideas and technologies into practice. However, the research objective must not be seen as a template for a specific Industry 4.0 solution, but rather as a versatile building block that can be adapted to specific objectives. From productivity increases to product-oriented variant diversity, an individual current state can be identified for each company, which can be improved by Industry 4.0. It is our task at the Chair of Processes and Systems to identify problems from practice, to generalize them, to develop solutions and methodologies, and finally to apply our findings to the concrete problem.

A hybrid simulation environment as a research basis: Virtuality - Augmented Reality - Reality

A model is the basic building block for gaining knowledge. The integration of automation technology, logistics, robotics, CMS and operational application systems into a single simulation environment is offered by our Learning Factory of the Research and Application Center Industry 4.0. Here we can combine components of software and hardware and achieve a particularly high degree of immersion for the user due to the combination of the three components Virtuality Augmented Reality - Reality. The fast and low-cost linking of physically or virtually provided production objects allows us to examine production processes individually for potential and to demonstrate the benefits of Industry 4.0 technologies in a vivid and realistic way on the concrete process. Since we work with real data and real technology, this unique presentation helps to argue investment decisions of different target groups.

Integration of brownfield situations into the digitization process

With the future-oriented design of Industry 4.0 in the company, decisions are no longer made centrally at one point, but directly in production. A suitable form of intelligence and communication capability within and between the individual devices is essential for such decentralization. In the starting position of a so-called brownfield scenario, existing machines and equipment must first be digitized before they can be integrated into new cyber-physical production systems (CPPS). The challenge of redesigning a central and complex control process to break it down into independent, segmented subsystems was solved by developing an Industry 4.0 Box. It enables machines and systems that were previously not CPS-capable to act as CPS from now on and thus become part of a networked production system. The Industry 4.0 Box is being tested in its application in practical companies.

Industrial internet of things and manufacturing analytics: The eyes and ears of manufacturing

The Internet of Things in the industrial environment plays a fundamental role in the digitalization of classic manufacturing and production facilities. In contrast to IoT, the concepts do not focus on consumers and users, but on the data-driven optimization of industrial processes and the automation of their operations. The intelligent networking of machines and their environment provides a decisive information advantage, enabling decisions to be accelerated or business processes to be adapted flexibly. A central role is played by sensors and sensor data, which provide the data basis for self-learning machines and contribute to an expansion of knowledge within the production process through analysis. The aim is to create a constant and real flow of information that evaluates the usage data obtained from production and feeds it back directly into the process. The machines used are independently able to recognize what they need for the ongoing production process or when the next maintenance is due. Our research investigates the potential of the industrial Internet of Things for the future and competitiveness of a company, looks for optimization potential in the analysis area and identifies newly emerging business areas.

Artificial intelligence in production with big and small data

Due to the digitalization of manufacturing and production processes, more and more data is being collected. Cyber-physical systems and the Internet of Things are creating individual knowledge bases that are available for higher-level intelligence. This opens up methods of machine learning and automated modelling with great potential for optimisation, such as rapid identification of the causes of faults. The basic idea of machine learning is to gain knowledge from experience after a general solution specification has been given. The more data available, the easier it is to implement the Case-Best-Reasoning approach as a form of Artificial Intelligence. It is therefore all the more crucial that we also focus our research on small data - a situation that mainly affects SMEs, where a basis for artificial intelligence is to be created despite the lack of data.

IT security in critical infrastructures

The reliable supply of drinking water and the equally reliable disposal of wastewater from households, industry and agriculture are indispensable in everyday life. In the supply sector, many companies work with computer, guidance and control systems, but as networking increases, they are increasingly becoming the target of standardised cyber attacks. In the course of a joint project, a simulation case has been developed at our chair, which technically resembles a section of a real waterworks to be tested. By applying various penetration tests, this allows a critical analysis of the respective systems without actually endangering the security of supply. Adapted measures to improve the technical, organisational and personnel aspects of risk management can be derived.

IT security in the manufacturing industry

While digitization enables many competitive and optimization advantages for the manufacturing industry, it also creates new potential for attack. In the wake of the DSGVO and the increasing data processing within production processes, there is therefore an increased need for IT security. Due to the increased feedback of acquired data to production, there is a particular need for an information security process that includes the systematic safeguarding of the entire factory IT. In our research we therefore test the applicability of common IT security procedures and search for solutions to ensure data protection and data security. The Industry 4.0 Box developed at the chair could be used as a means of an information gateway and, in addition to the cyber-physical networking of production units, also serves as a means of data security.