AI Success Stories
POCs, projects, prototypes, MVPs and industrial integrations of AI technology
Projects
01/07
Proposal for trouble shooting by entering a semantic problem description (VW)
Category
Automotive
Duration
6 months
Scope of work
- Implementation of a Retrieval Augmented Generation system to solve problems based on historical trouble-shooting-data
- Using LLM to identify over 7000 engineering specific wordings.
- Training LLM and Embedding model to search for similar entries in a large database
- Show similar trouble shootings in the past, synthesize possible solutions based on loose problem descriptions
02/07
Inline inspection of cracks in cartridges in the medical technology sector (B.Braun)
Category
Medicine
Duration
4 month
Scope of work
- Finding micro cracks in cartridges for dialysis machines
- Design of a computer vision inspection system
- Installing 4 micro cameras in the production line with the help of 3d printers
- Fine-tuning of a neural network for crack detection
- The project was part of the B.Braun Accelerator program for new technologies
03/07
Online Scoring System of Startups (Exponential Innovation Institute)
Category
Consulting
Duration
2 weeks
Scope of work
- The project aimed to develop a bot capable of scraping real time online data to score startups based on varied parameters.
- A sophisticated scoring algorithm was developed, utilizing GPT4 and its reasoning capabilities as well as advanced prompting techniques.
- Rigorous integration and testing were conducted to assure seamless functionality and reliability of the bot in real-world conditions.
- Post-implementation, continuous analysis and optimizations were performed to enhance the bot’s scoring precision and performance.
04/07
Identification of system behaviour for wear reduction in electric motors (Hucon)
Category
Automotive Development
Duration
2 weeks
Scope of work
- A diverse and reliable dataset of an automotive electro motor and controls was rigorously preprocessed to eliminate discrepancies and noise.
- Sophisticated machine learning algorithms and statistical methods were utilized to isolate significant factors and interactions, revealing intricate dependencies and correlations within the motor controls.
- A detailed analysis of failure modes provided unprecedented insights into the root causes of malfunctions, highlighting previously unidentified triggers and system vulnerabilities.
- The discovered patterns and anomalies were rigorously validated through statistical tests and real-world correlation, ensuring the reliability and relevance of the findings.
05/07
Counting, tracking and checking donuts along a production line (Schwarz Produktion / Lidl)
Category
Food Production
Duration
12 month
Scope of work
- A monitoring system was developed to count, track, and measure donuts along the production line in real-time.
- State-of-the-art sensors and cameras were implemented for precise detection and surveillance of the donuts throughout the entire production process.
- The system integrated seamlessly into the existing MES by OPC-UA.
- A dashboard shows statistics in real time
- An object detection model is implemented base on augmented virtual training data of a digital twin.
- A gradient flow based model is trained to fit the shapes on sub-pixel level to ellipses.
06/07
Automation of IT structures for part changes for Just-In-Time production (EDS/VW)
Category
Industrial Manufacturing
Duration
4 month
Scope of work
- The project focused on leveraging AI to automate IT structures, enabling efficient integration of parts for just-in-time production processes.
- Advanced AI technologies were utilized to ensure precise and sensitive handling of components, reducing errors and damages in the production line.
- The implemented AI system considerably reduced the time traditionally required for parts integration, enhancing overall operational efficiency.
- The system intelligently adapts to various components, ensuring seamless integration and maintaining the integrity of just-in-time production models.
- The project successfully enhanced the reliability and consistency of production processes, ensuring product quality and timely delivery.
07/07
Detection of web breaks and incorrect machine settings (Technoform)
Category
Automotive
Duration
12 month
Scope of work
- The AI project successfully implemented advanced detection algorithms to identify rail breaks and incorrect machine settings in a plastic continuous extrusion machine utilized for window facade profiles.
- State-of-the-art sensors and data acquisition systems were integrated, ensuring precise and real-time data collection critical for accurate anomaly detection.
- A robust machine learning model was developed and trained using historical data, enabling the efficient identification of abnormalities and potential failures in the extrusion process.
- The AI system provided actionable insights and real-time alerts, allowing for immediate corrective actions, reducing downtime, and ensuring continuity in production.
- Through this integration, the overall efficiency and reliability of the extrusion machine were significantly improved, resulting in enhanced product quality and reduced operational costs.
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