Artificial intelligence is currently on everyone's lips. Is its significance for industry really as great as the hype suggests?

Artificial intelligence is a significant lever in the industry. However, you have to differentiate depending on the application: In the automation of business processes, AI systems are already making significant contributions to increasing efficiency, e.g. in data analysis and processing, personalized marketing, supply chain optimization, with intelligent assistants, voice and image recognition and much more.

AI also has enormous potential to improve production processes. However, this requires a number of prerequisites: Machines must be networked, data must not only be collected but also processed in a meaningful way. And the AI must be trained.

If these requirements are met, AI can contribute to major cost savings. The current focus is primarily on error detection and quality assurance. The comprehensive automation of complex, specific processes within a production machine using AI is still too challenging according to the current state of the art. However, sub-processes, such as image recognition and processing, can already be optimized very well using AI systems.

Many companies say they use AI. How do you assess this statement?

There are definitely very different degrees of use - depending on the industry and use case. Many companies use AI to improve their business processes. These range from the automation of repetitive processes to advanced applications such as sophisticated machine learning models. Unfortunately, AI is also often used as a buzzword, as has been the case with the term Industry 4.0 in recent years. In-depth know-how on AI is not yet available across the board. The implementation of AI can be complex and associated with various challenges such as data procurement, skills shortages and ethical issues. Companies therefore often rely on third-party solutions.

How do automation providers use artificial intelligence? What role do LLMs like ChatGPT play in this?

Large Language Models such as ChatGPT play an important role in the implementation of AI in areas where natural language processing is required. They can be used in text generation, communication with users, automated text analysis and much more. Companies can use LLMs to develop chatbots and virtual assistants that are able to simulate human interactions and perform tasks in natural language. Communication between humans and machines in the direct production environment via voice control is still difficult because safety aspects or background noise also need to be taken into account. Otherwise, automation providers have the same range of applications as described above, especially for general business processes.

What specific AI solutions do companies offer?

Specific AI solutions on the market or fields of application in which AI already plays an important functional role include translation, data analysis, biometrics and image processing, energy control and distribution, cyber security and personalization.

One specific use case in the automation and production environment at Bosch is the AI platform - an internal analysis solution for greater transparency and insights into manufacturing processes in Bosch plants. The solution enables specialists to monitor key performance indicators, carry out independent analyses and find the causes of errors in complex production problems. It uses AI to detect anomalies in real time and inform production staff about the errors. In addition, the AI platform provides Bosch associates with data provision functions.

What trends and solutions relating to this AI & Co. do you think will be on show at SPS in November?

At SPS, the main focus will be on AI applications that are particularly relevant in the field of industrial automation. These include solutions for process optimization, quality control and predictive maintenance. In the field of industrial automation, it is first and foremost about enabling the use of AI in the first place. Bosch Rexroth is pursuing this enabler strategy with the ctrlX Automation modular automation system, which ensures consistent data availability. It also enables scalable computing power from the field device to the edge and into the cloud, as well as unrestricted usability of all common tools in the AI environment.