Industrial quality inspection solutions

The data pipeline is crucial for industrial inspection solutions as it facilitates the seamless flow of data through various stages. From acquisition to storage, management, visualization, logging, and archiving, CSEM’s data pipeline ensures efficient and effective handling of inspection data. By collecting and storing data efficiently, it becomes easily accessible for visualization and analysis. Furthermore, logging data enables traceability and future reference, while proper data management enhances decision-making during the development and production phases. Whether the data is processed on the edge, on a local server, or in a public cloud, the pipeline always adapts to your business needs. By leveraging data assets, businesses can extract valuable insights to drive improvements in their processes.

Algorithms play a pivotal role in industrial quality inspection, covering various stages of the inspection process. Pre-processing techniques are employed to enhance data quality by reducing noise and extracting relevant features for subsequent analysis. Classical algorithms, such as metrology, enable precise measurements, dimensional analysis, and defect detection. To address the complexities posed by diverse product ranges, complex defects, and high production speeds, we fine-tune our deep learning algorithms to recognize and classify complex patterns, defects, or anomalies.

Additionally, our algorithms are designed to be adaptable over time, supporting life-long learning for continuous improvement and adaptation to evolving inspection requirements. Our experts are already working on the next generation of quality inspection techniques, which combine multimodal vision data with time-series signals from various sensors. This enables a holistic view of the machine or process to monitor perfect quality.

In our pursuit of excellence in industrial quality control, we continuously strive to enhance existing data sets. We achieve this by creating photorealistic images using advanced rendering software like Unity and Blender and further adapting them with Generative Adversarial Networks (GANs) to resemble real-world conditions. By leveraging synthetic data generated in combination with existing data sets, we can create more robust and generic solutions while minimizing the effort and cost associated with collecting real data. CSEM quickly adapts the most promising algorithmic approaches from academia, optimizes them for our customers, and takes care of deployment for industrial needs. This approach enables us to deliver even more reliable and efficient quality inspection solutions to our clients.