top of page

Industries

AUTOMOTIVE

carassemble-white.png

Automotive

Global major players in the automotive industry are changing their manufacturing environment into innovative and intelligent factories in response to the demands of cutting-edge products and ever-changing market requirements.

Shifting to custom production trends in the global automotive market, the automotive makers adopt AI technology to diversify the product line-up in the existing assembly line and to manage the quality of the products at the same time. The efforts can yield a company a competitive edge in the market. Innovation in the production line is at the heart of the efforts.

With BISTelligence, acquire a competitive advantage in the market by increasing your production efficiency and overall product quality.

Process anomaly detection/monitoring & data analysis: Data collected from automation equipment and robots via IoT can be analyzed in real-time to monitor manufacturing process faults and find the root cause of them and other factors that impact product quality. 

Enhance problem-solving capability with AI: The custom production environment is changing continuously, which causes many manufacturing problems. Our AI automation models can diagnose the problems and suggest solutions to them. The models can solve recurring problems autonomously. 

Use Case 1

Intelligent Automotive Assembly and Production System by AI 

One of the global automotive companies introduced BISTelligence AI technology to its assembly line to complete an intelligent automation system. Our AI technology monitored the vibration and electric current data of robotic arms, lift equipment, engines, and load tester in real-time. AI detected and classified process faults and predicted the remaining useful life of equipment. The engineer team could find and respond to the problems in a timely manner and prevent the production line downtime.  

Use Case 2

AI-based automotive engine test cell management

In an automotive R&D center, where they run various test cells with various test modes and test environments, alarm management is considered one of the most important activities. One of our customers minimized the false alarm events per engine test cell and focused on analyzing true alarms using machine learning models.

Using our AI technology, the R&D team monitored RPM, temperature, vibration RMS, vibration spectrum, and other parameters in the automotive engine test cell to detect mechanical alarms and classify them to understand the diagnosis and solutions of faults.

Ask an Expert!

수채화 새 2
bottom of page