Artificial intelligence and Mechanical engineering - Digital quality control rethought
State-of-the-art AI algorithms optimize Processes, make well-founded and precise Decisions for more efficiency and ensure the highest Quality - efficient, automated and future-proof.
AI transformation in mechanical engineering through digital processes
In the Mechanical and plant engineering precision determines success or failure. Artificial intelligence gives Industry 4.0 systems the decisive edge:
36ZERO Vision uses AI and deep learningto perform visual inspection tasks in the Mechanical engineering completely, automatically and efficiently. The AI application analyzed Upload from Industrial cameras in real timerecognizes even the finest Surface defects and evaluated Components objective. This will Processes not only faster, but also much more reliable. The Cloud platform serves the development of AI models individually for each application. It is initially trained with known defect types and can be continuously improved through interaction with employees. In this way, it adapts flexibly to new product groups, variants and production conditions and standardizes quality decisions worldwide. Images from industrial cameras with the trained models self-sufficient, on-premise and in real time analyzed, relevant Error pattern and components can be objectively evaluated. Complex surfaces, material structures and production processes can thus be inspected without delay - faster and more precise than by the human eye or classical systems such as anomaly detection, which declare any deviation as an error.
The Result:
Less Pseudo committee.
Less Complaints and significantly more Efficiency in every Production application.
36ZERO Vision continuously adapts to the Challenges of the Mechanical engineering by using the valuable Know-how of the companies intelligently with artificial intelligence combined.
This means that standardized, traceable and fast Quality decisions at any time to all Employees available.
Challenges in mechanical engineering and Industry 4.0
Pseudo committee drives up costs
Faultless parts are sorted out unnecessarily and Machines work inefficiently.
Customer complaints are a drain on resources
Defective products require additional, manual Examinations and cost time and trust.
Traditional camera systems are inflexible
With a wide range of variants Applications and complex Machines conventional Technologies like machine learning quickly reach their limits.
number_of_connectors_9
The target number of 9 connectors was identified.
number_of_screws_6
The cover was fixed in place with the 6 screws provided.
scratch_surface
There is a small scratch on the surface which does not affect the function.
Added value for higher Competitiveness
Automation in Manufacturing
Lenses Classification from Errors
Seamless implementation - Turnkey solutions and retrofitting of existing sensors in systems and production lines.
Train faster - with considerably less Data
Continuous improvement of controls and Processes through iterative further development of the models
Increased efficiency promotes the added value of Applications and reduces costs
