How Bosch uses AI in manufacturing - A foray through our very own manufacturing plants

There are sound economic reasons for Bosch using applied AI: depending on the size of the plant and type of production, artificial intelligence can be used to achieve productivity gains and six- to seven-figure cost savings – per year and plant

AI status: widely used in Bosch plants

Many Bosch plants have one thing in common: not only are they AI pioneers, but they also focus consistently on Industry 4.0. For example, Bosch research has developed an AI-based system that identifies anomalies and malfunctions in the manufacturing process and improves product quality. This software is now in use in around 50 Bosch plants, with over 2,000 production lines connected. Many Bosch plants also use artificial intelligence in the optical inspection of components. For example, over 20 plants use Machine Vision AI, a solution designed by Bosch’s special-purpose machinery unit that helps detect hard-to-identify features, such as scratches and chipping on surfaces and defects in weld seams.

"Nearly half of all Bosch plants are already using AI in their manufacturing operations. With the help of generative AI, we’re not only improving existing AI solutions, but we’re also laying the foundations for the optimum take-up of this future technology in our global manufacturing network"

says Stefan Hartung , chairman of the board of management of Robert Bosch GmbH

AI boost: generative AI pushes the boundaries of feasibility

For years, the Feuerbach plant inspected fuel-injection components manually. The nature and complexity of the products, as well as differences in the structure of the production lines, meant that neither rule-based nor AI-assisted optical inspection was possible. The new approach is a scalable generative AI that recognizes variants of a product and error patterns and takes into account different arrangements and sequences in the production process. This is based on a foundation model developed by Bosch research and fed by large data sets from the Bosch manufacturing network. Synthetically generated data is used to refine the model and customize it for on-site applications. This is expected to make the AI capable of inspecting components independently, only submitting cases to visual inspectors where it is unsure. At the Hildesheim plant, synthetically generated images have already been successfully used for training purposes in the first standard systems in electric motor production. The human eye cannot distinguish the artificially generated images from real ones. The plant expects that project duration will be six months shorter with the new approach than with conventional methods, leading to annual productivity increases in the six figure euro range. Bosch plans to expand the AI approach to other locations

AI pioneers: World Economic Forum commends Bosch plants

The Bosch plant in Bursa, Turkey, illustrates what AI can achieve in manufacturing. Starting from an already high level of technical expertise, the plant has used AI to further improve manufacturing quality: it has reduced water consumption by 30 percent, energy consumption by 6 percent, and scrap by 9 percent, while also increasing plant efficiency by almost 10 percent. This year, these achievements prompted the World Economic Forum (WEF) to single out the plant in Bursa as an Industry 4.0 lighthouse. This is the fourth time a Bosch plant has received such recognition from the World Economic Forum, and the second time specifically for developments in the field of artificial intelligence

Bosch plant in Ansbach

This plant manufactures printed circuit boards for use in control units for ABS and ESP as well as for electronic steering systems. In the assembly of these boards, particular attention has to be paid to the solder joints: there are between 5,000 and 8,000 of them on each board. The Ansbach plant uses an AI-based measuring process to check whether all circuit-board elements are soldered correctly. If this is not the case, an image of the faulty solder joint is presented to experienced visual inspectors for evaluation. All in all, the inspectors now receive only a fraction of the images they previously had to review. The AI significantly reduces the visual inspectors’ workload, improves the quality of the results, and increases productivity.

Bosch plant in Blaichach

The plant in Bavaria also uses AI for quality control. At the Immenstadt site, the screen at the test bench for ABS systems lights up red to show the assembly workers if the component being tested is defective. This information is provided by a self-learning system that uses the data it has collected to recognize error patterns and, in this way, to distinguish relevant error messages from non-relevant ones. Weekly retraining of the algorithms continuously improves the high success rate.

Bosch plant in Changsha

At this plant in China, Bosch has introduced an AI-based energy management system that it developed in-house. The system relies on AI algorithms to predict energy consumption on production lines, enable continuous production scheduling, and incorporate business and environmental factors. These factors include forecasts of customer demand, production plans, weather, temperature, and humidity. This saves energy and reduces emissions. With the help of the AI solution, the Changsha plant was able to cut its annual electricity consumption by 18 percent and carbon dioxide emissions by 14 percent. For its achievements, the plant was singled out as an Industry 4.0 lighthouse by the World Economic Forum in 2022.

Bosch plant in Charleston

At this U.S. location, Bosch manufactures mobility solutions such as ESP, electric motors, and fuel-injection valves. The plant uses a root-cause analysis to investigate causal relationships that can lead to rejects at the end of the production process. AI software lends support to this analysis by sifting through the billions of data points that a manufacturing execution system (MES) collects and records during production. From this data, the AI derives possible correlations between the measured values and quality deviations in the production line and sets them out clearly on a dashboard, where associates see a ranked list of possible causes sorted by descending probability.

Bosch plant in Dresden

In this wafer fab, which went into operation in 2021, the company employs an AI system developed by its own researchers to detect anomalies and faults in the manufacturing process at an early stage. Predictive maintenance means that work on machines and systems is carried out as necessary. Artificial intelligence guarantees high process stability in the wafer fab and increases quality continuously. This saves customers time-consuming tests and curtails month-long trials. As a result, Bosch not only manufactures faster, but can also be relied on to deliver on time.

Bosch plant in Mexicali

At this plant in Mexico, AI uses noise analysis to check the quality and functionality of the multifunctional tools manufactured on-site. Once production is complete, a microphone “listens” to the tools for three seconds before the AI software delivers its verdict: OK or not OK – and the results are much more reliable than is possible for human inspectors. Around 300,000 tools were tested during development of the AI solution. The plant aims to use this process to inspect over one million products per year.

Bosch in Reutlingen

Artificial intelligence is also used in production scheduling at highly automated wafer fabs such as the Bosch plant in Reutlingen, Germany, where it saves time and costs as it guides the wafers through up to 1,000 processing steps. The AI has an overview of all the materials available for a manufacturing step and sorts them on the assembly line so as to achieve optimum throughput. In many instances, production sequencing is determined completely by AI, thus ensuring optimum utilization of capacity.