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06/06/2024|Digitization

Artificial intelligence (AI) in manufacturing

The increasing digitization of industry on the way to Industry 4.0 puts artificial intelligence (AI) and its applications in manufacturing in the spotlight. AI algorithms and machine learning are revolutionizing production and engineering. Robots and intelligently controlled machines not only optimize production processes, but also offer innovative applications for factory maintenance. However, along with the immense potential of AI, there are new challenges when it comes to integrating intelligence into machines and effectively using large amounts of data. Integrating AI in manufacturing requires a deep understanding of the technologies.

The rapid pace of digitization has also ushered in the era of artificial intelligence in industry. The buzzword AI encompasses many concepts, technologies, and applications that are revolutionizing manufacturing. But the birth of artificial intelligence goes back many years. In 1955, a team of scientists submitted a groundbreaking proposal to a seminar at Dartmouth College. Their goal was to create a machine capable of simulating capabilities such as language processing, abstraction, and self-optimization. At the time, this was science fiction, but today artificial intelligence is an essential part of modern manufacturing.

How AI applications are revolutionizing industrial manufacturing

What does the term "artificial intelligence" mean? AI in manufacturing opens up a universe of possibilities. AI-enabled machines and robots can not only optimize processes, but also analyze large amounts of data and perform predictive maintenance. Sensors monitor the health of machines, while intelligent technologies predict potential failures and schedule maintenance.

Since the Dartmouth Conference in 1956 and the basic assumptions about artificial intelligence that were made there, the fundamental concepts and algorithms have continued to evolve. The diversity of artificial intelligence manifests itself in several subfields, each of which encompasses different applications and technologies, depending on its focus.

The key areas of AI include:

  • Machine learning
  • Neural networks
  • Natural language processing
  • Genetic algorithms
  • Computational creativity
Machine learning processes input data and finds patterns and dependencies
Machine learning processes input data and finds patterns and dependencies

Machine learning in particular is emerging as an important area of artificial intelligence, especially in production and manufacturing. Machine learning involves the analysis of data by computer-aided systems that can independently recognize correlations and trigger appropriate actions. The discipline of machine learning is closely related to the field of big data, as the digital age is generating more and more data that can hardly be managed using conventional methods.

The convergence of information and production technology has led to industrial automation and the emergence of the industrial Internet of Things, in which cnc machines, systems, and processes are increasingly networked. The data they generate is a valuable resource. The challenge now is to use this data efficiently and create value for customers.

AI turns data into knowledge

There is a lot of interest in artificial intelligence, and for good reason. It is no secret that valuable knowledge can be generated from the data obtained, providing real economic value. This potential extends to production itself, as well as to all upstream and downstream processes. In the area of machine learning in particular, AI offers a wealth of potential applications that affect all areas of the value chain.

Data is the fuel for new machine learning applications. It is becoming a valuable raw material that continuously provides new application scenarios for machine learning. In particular, there are immense opportunities in process optimization and automation. Data enables the generation of additional information that leads to new product and process knowledge. This in turn initiates a continuous improvement process that can be continued in an endless loop and constantly optimized.

AI applications in manufacturing & production

Coolant nozzles are adjusted so that chip removal produces an ideal result
Coolant nozzles are adjusted so that chip removal produces an ideal result

DMG MORI's AI-assisted chip disposal is setting new standards in the manufacturing industry. Chips are a common cause of machine downtime and malfunctions. The „AI Chip Removal“ uses artificial intelligence to analyze chip production and automatically dispose of the chips.

CNC Machine's work area
Two high-resolution cameras in the machine's work area monitor the chip fall

The technology is based on two high-resolution cameras inside the machine that continuously provide clear images of the work area. Based on these images, the "AI Chip Removal" system analyzes the chip accumulation and learns more and more about the working conditions. In this way, the artificial intelligence determines the optimal cleaning method. It automatically adjusts the orientation of the coolant nozzles to the position of the chips and, if necessary, ensures optimal chip removal.

AI chip removal

Artificial intelligence for a manufacturing efficiency advantage

The use of artificial intelligence for data analysis is becoming increasingly important for the efficiency of manufacturing processes and is therefore also gaining in importance at DMG MORI. The aim is to significantly improve the performance, precision and cost-effectiveness of machine tools, automation solutions and machining processes by combining AI and "mirroring" the results in digital twins. By creating digital images of machines and processes, simulations can be run to predict potential problems and identify opportunities for optimization. AI plays an important role in the analysis and interpretation of the simulation results.

DMG MORI uses artificial intelligence in a variety of ways to improve the performance of its CNC machines and make manufacturing processes more economical. This makes the company a pioneer in the integration of AI technologies and has a significant impact on the future of the manufacturing industry.