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inSpect Fuel Cell Visual Inspection of Fuel Cells

Automated in-line visual inspection technology monitors high-volume roll-to-roll fuel cell production. Leveraging advanced image processing, it detects and analyzes defects like scratches, cracks, particles, and pattern irregularities in real-time.

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Modular design

Inspection system designed with modularity as its core principle, each operation resides in its independent module or production cell, providing the flexibility to be added, removed, or relocated along the production line. This modular design enables adjustment of production sequences by incorporating additional production cells as needed. Future-proof design allows integration of new production cells, ensuring adaptability and scalability.

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Tailored approach

Fuel cell quality control utilizes a range of advanced techniques, from optical, spectral, and 3D scanning to IR thermal, Terahertz, and Low-energy X-ray imaging. These methods, enhanced by classical computer vision and deep learning, create a robust quality control system. The choice and number of methods employed depend on the various defects that need attention.

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Timing precision

The roll-to-roll visual inspection attains speeds of up to 1 m/s, which is crucial in fuel cell production lines. With each operation being highly significant and the web moving rapidly, specialized equipment is employed to strictly maintain timing precision. This prevents any deviation that could cause an offset on the web, ensuring synchronized operations, and production efficiency.

Process monitoring and
defect detection

Visual inspection is crucial for ensuring the quality and reliability of fuel cells in high-volume roll-to-roll (R2R) production processes. Leveraging advanced image processing techniques, defects such as scratches, cracks, particles, and pattern irregularities are detected and analysed in real-time within a clean room environment (ISO class 3).

inSpect Fuel Cells technology not only identifies defects but also monitors essential process parameters like material thickness, colour, conductivity, temperature, humidity, tension, and pressure. Its sensors continuously regulate these conditions, proactively addressing potential issues to maintain optimal quality standards.

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Advanced techniques for fuel
cell quality control

In the continuous R2R process, fuel cell layers, approximately 10 microns thick, are applied on a carrier foil moving at speeds up to 1 m/s. To ensure proper application and detect imperfections like thickness variations and holes in the membrane and catalyst layers, multiple approaches are used, including thickness measurement, material composition analysis, hyperspectral imaging, and traditional computer vision.

Configurable with various inspection equipment, R2R inspection machines facilitate real-time quality assessments, enhancing the overall reliability of fuel cells in functional materials manufacturing.

Precision timing in high-speed
R2R production

Full cell production operates as a fully automated roll-to-roll (R2R) process, with visual inspection seamlessly integrated for real-time quality control. Timing precision is crucial due to the high web speed, which can reach up to 50 m/min. Even the slightest delay can cause significant offset on the web, emphasizing the need for precise time synchronization in critical operations. Specialized fast equipment is employed to process signals efficiently in these scenarios.

Precision and accuracy are essential for detecting defects in fuel cells, with specifications dependent on production line speed, including sample width, layer thickness, x/y resolution, scan frequency, and provisional defect size limits based on human eye limitations. In the roll-to-roll process, this information guides the removal of defective products, as peeling off individual products from the foil is not feasible until the entire roll is completed.

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Real-time supervision with visual inspection and HMI and SCADA

inSpect Fuel Cells integrates modern HMI and SCADA systems, enabling operators to visualize and supervise the manufacturing process, aid in diagnostics, perform QA, and monitor real-time performance. Data storage facilitates analysis and tracking, making the inspection approach essential for producing high-quality, high-performance fuel cells in advanced manufacturing processes.

Incorporating inspection systems in R2R production significantly reduces waste and scrap by identifying defects early, ensuring fewer defective materials reach the final product, enhancing efficiency and customer satisfaction. Data generated is used for process optimization through machine learning and AI, customizing inspections for various materials and quality criteria.

Key Technologies

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Confocal thickness measurement

Confocal thickness measurement ensures reliable detection using light refraction. Each production lane features a C-frame with two confocal sensors to scan the web's thickness, offering customizable patterns based on equipment and web speed.
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Hyperspectral imaging offers precise material differentiation by measuring reflections across the invisible spectrum, combining spectroscopy and digital photography. It captures light intensity for numerous spectral bands per pixel, enabling detailed object characterization.
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XFR control measures element concentrations within layers by moving transversely to predefined or random web positions. It measures mgPt/cm² and reports Fe trace amounts, averaging results longitudinally. A contrast sensor detects CCM leading edges to initiate and end analyses.
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AI surface

AI surface inspection employs high-resolution line scan cameras on a static frame to examine surface quality. An encoder ensures uniform intervals as the cameras capture lines of the moving web. Classical computer vision and AI algorithms analyse the data to detect defects and assess quality.

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Frequently Asked Questions

The inSpect Fuel Cells system utilizes a variety of measuring techniques, including confocal thickness measurement, hyperspectral imaging, XRF analysation, and classical computer vision. These technologies enable real-time defect detection and monitoring of critical process parameters such as thickness, colour, conductivity, temperature, humidity, tension, and pressure to ensure optimal quality.
Roll-to-roll visual inspection can achieve speeds of up to 1 meter per second (1m/s) for the foil. In an R2R production line, timing precision is paramount due to the significance of each operation and the high web speed, which can reach up to 50 meters per minute. Even a minor delay can cause a significant offset on the web, underscoring the importance of time synchronization in critical operations. Specialized fast equipment is utilized to process signals efficiently in such scenarios, ensuring seamless operation and maintaining production efficiency.
The visual inspection approach is versatile, adaptable to diverse roll-to-roll processes. Both equipment and inspection methods can be fully customized to meet specific requirements. The roll-to-roll process itself is highly flexible and can be upgraded as necessary, with individual stations seamlessly added or modified according to specific needs. This adaptability ensures seamless integration into various roll-to-roll manufacturing setups, providing efficient and tailored quality assurance across different processes.
inSpect Fuel Cells can detect defects such as scratches, cracks, and irregularities, as well as monitoring critical parameters like thickness, colour, and conductivity, inSpect Fuel Cells ensures that fuel cells meet stringent quality standards. This not only enhances the overall efficiency and reliability of fuel cell systems but also ensures customer satisfaction and safety. Moreover, timely detection and resolution of defects help minimize waste, reduce production costs, and optimize manufacturing processes for greater efficiency and competitiveness.
The specifications for defect detection in fuel cell production are influenced by several factors: production line speed, sample width, layer thickness, x/y resolution, scan frequency, and defect size limitations based on human eye limitations. Faster production lines require higher scan frequencies to keep up with product movement, while wider samples need advanced imaging for complete coverage. Layer thickness necessitates sensitivity adjustments to detect hidden defects. High x/y resolution is crucial for identifying small imperfections. The scan frequency must match production speed for real-time inspection, and defect size limits ensure the system focuses on significant defects, ensuring high-quality fuel cells.
The inSpect Fuel Cells system leverages real-time data for process optimization using machine learning and AI, tailored to diverse materials and quality criteria. Advanced human-machine interface (HMI) and supervisory control and data acquisition (SCADA) systems facilitate real-time monitoring and analysis, enabling operators to diagnose issues promptly. In roll-to-roll production, where removing defective products before completing the entire roll is impractical, this information guides the selective peeling from individual products from the foil for disposal.

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