Trends 2024

Increased efficiency and cost savings

In modern industry, increasing efficiency and reducing operating costs is crucial. Embedded AI enables the optimization of production processes in real time. Machines and systems can be continuously monitored for conditions and anomalies using sensors and algorithms in order to identify bottlenecks, optimize processes and use resources more efficiently. This leads to considerable cost savings and an increase in competitiveness.

Predictive maintenance (preventive maintenance)

An outstanding use case of embedded AI in industry is the often mentioned but still little used preventive maintenance. By integrating sensors and data analysis within production facilities, companies can monitor the condition of machines in real time without data leaks to the outside world. When anomalies or signs of wear and tear occur, maintenance can be planned in advance to minimize unplanned downtime. This increases the lifespan of equipment and significantly reduces maintenance costs through predictability and new business model opportunities.

Quality control and waste minimization

Embedded AI enables precise quality control during the manufacturing process. Cameras and sensors such as lidars, radars or those for spectrography and ultrasound can monitor products in real time and detect defects or deviations from standards. Defective products can be identified at an early stage and ejected from the production process, which increases quality and minimizes waste. In addition, direct feedback for minimizing waste in real time is a significant advantage, as incorrect settings and incorrect operation or supplier defects become more transparent and consequently cause less damage.

Autonomous robots and automation

Autonomous robots are playing an increasingly important role in industrial production. Embedded AI enables these robots to perform tasks such as material handling, inspection and assembly autonomously. They can adapt to changing conditions in real time, as local AI can deal robustly with variance and handle complex tasks without human intervention. This significantly increases productivity and precision.

Energy efficiency and sustainability

Monitoring and controlling energy consumption is another area where embedded AI has a major impact. Industrial plants can use AI algorithms to optimize energy consumption by dynamically adjusting the demand for heating, cooling and lighting depending on the situation. The metering sector in particular is directly affected, while machine and plant manufacturers can use this indirectly in their processes. This not only helps to reduce operating costs, but also to reduce the industry’s ecological footprint.

Safety in the workplace

Embedded AI can also help to improve safety in the workplace. By continuously monitoring hazards and undesirable events, early warnings can be triggered and preventive measures taken to avoid accidents and protect the health of employees. In addition, intelligent user interaction through gesture, person and voice recognition is a feature that makes interaction more efficient and addresses the shortage of skilled workers.

Adaptability and scalability

Another advantage of embedded AI is its adaptability and scalability. Companies can gradually drive forward the integration of AI in their production processes and expand the technology as required in a decentralized manner and without leading cloud systems and follow-up costs. Despite the hardware required, this enables flexible implementation that meets the individual requirements of each company.

Competitive advantage and innovation:

Companies that adopt embedded AI early on can gain a significant competitive advantage. The ability to process data in real time and make informed decisions enables innovation in products and services without dependencies on networks, suppliers and infrastructure providers. This opens up new business opportunities, increases resilience and innovatively strengthens the market position.

Conclusion

Embedded AI has the potential to transform industry in many ways. From increasing efficiency and quality assurance to energy efficiency and innovation, this technology offers numerous benefits. Companies that do not engage with embedded AI could run the risk of being left behind in an increasingly digitalized world. This is because pure cloud strategies lead to dependencies, chaos and cost explosions. Even worse: some use cases with real-time requirements are ruled out from the outset by the cloud and the maximum amount of data that can be transferred. This is why embedded AI is becoming increasingly important in industry, as it will play a key role in shaping the future of manufacturing and production.