Elevate Your Process Stability & Product Quality with AMCA
Achieve consistent performance, customer satisfaction, and cost savings with MetIQ’s
Automated Metal Cleanliness Analyzer (AMCA).
The AMCA Method
Transforming Aluminum Metal Cleanliness Assessments
The Automated Metal Cleanliness Analyzer (AMCA) method revolutionizes aluminum metal cleanliness assessments by offering a digital, automated alternative to manual methods, including traditional PoDFA metallographic analyses.
Utilizing advanced image analysis and AI, AMCA provides rapid, accurate, and reproducible quantifications from any suitably polished surface of aluminum alloys, including filtration cakes obtained from common PoDFA, Prefil®, or LAIS.
AMCA classifies each pixel, covering common inclusion groups such as Carbides, Spinells, Oxides, Refractories, Grain Refiner Particles, and provides a Total Inclusion Count and complementary statistics.
Key Advantages Using AMCA
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REPRODUCIBILITY & ACCURACY
AMCA's fully digital approach eliminates the subjectivity of traditional methods, enabling accurate detection of smaller inclusions, down to ~1μm ESD, with consistent and fully reproducible results.
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CONSIDERABLY FASTER ANALYSIS
Receive results typically within 1-2 days, with a maximum turnaround time of 1 week. Upon special request and agreement, the analyses can be carried out within the hour.
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TRANSPERANCY & RAW DATA ACCESS
Full access to color-coded micrographs and raw data in an Excel file (or csv export) with descriptive statistics to highlight large inclusions (per class and image) and particle size distributions. Includes manual correction features.
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LOWER COST PER SAMPLE
AMCA is set up once per sample type to then rapidly analyze large sets of images for superior cost-scaling and statistical robustness.
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TAILORED IMPLEMENTATION
We tailor AMCA for each sample type with the possibility of adding custom features by the customer's needs. E.g. special inclusion detections, automated statistics, or visual guidance for analysing inclusion properties.
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USAGE OF STANDARD EQUIPMENTS
AMCA is designed to process micrographs from standard moving stage light microscopes, avoiding investments into specialized equipment.
Topological Shadow Isolation
AMCA excels by its unique shadow detection module that robustly isolates topological shadows at the filter grain edges to minimize false-positive artifacts. This revolutionizes detection precision over traditional thresholding methods.
Watch the three steps of analysis shown in the slider below.
Services
Metallography and Cleanliness Solutions
Qualitative Inclusion Assessment
We categorize inclusions into common groups (e.g., carbides, oxides, refractories, spinells, and grain refiner particles) and provide an estimate of the relative distribution.
Quantitative Inclusion Assessment
AMCA provides a detailed, pixel-precise systematic quantification of all inclusions in your samples. The provided metrics include:
- Total Inclusion Count (TIC)
- Inclusion area per sample for each class
- Relative inclusion distribution (% per class)
- Size distributions per sample
- Number of large inclusions (>20μm) per image per class
- ESD of largest detected inclusion per image per class
- Raw data (% of each class per image)
Expert Metallographer Assessment
If process details such as alloy type, sampling position, and general trial background are disclosed, the report will contain general comments of the results with regard to common benchmark levels and process conclusions based on the obtained results.
Metallurgical Inclusion Assessment Services
Optional and Complementary Services
Sample Preparation and Polishing
We provide professional metallurgical preparation, including polishing, to ensure optimal image quality for digital analysis and reproducible results using the AMCA method.
External PoDFA Benchmarking
We offer PoDFA analysis through a certified laboratory, providing industry-standard benchmarks for comparison with AMCA data. Note: typical lead times apply.
Other Image Analysis Tasks
Our automated image analysis can handle various tasks beyond standard PoDFA, such as evaluating porosities or structural features. Contact us for tailored solutions.
Collaboration Opportunities and Products
Software Solutions
We are developing software to enhance metal cleanliness assessments, enabling PoDFA operators to use AMCA for faster, more robust analyses. Designed for both standalone use and as a module in microscopy suites, this software makes automated digital cleanliness assessment widely accessible.
Joint Industry Projects (JIP)
We invite industry partners to collaborate on benchmarking and method development projects. By participating in PoDFA campaigns, partners can help refine AMCA for various industrial applications and gain tailored process data and analyses.
Joint Venture Opportunities
We seek partners for developing dedicated hardware solutions for automated sampling, preparation, and image acquisition, aiming to fully automate metal cleanliness assessments and boost efficiency across industries.
Publications
Research and Publications
Extensive Research and Development
The AMCA method is based on extensive research and development, supported by numerous publications over the years. Our work has consistently advanced metal cleanliness assessment technologies, ensuring that AMCA delivers precise, reliable results across various applications.
Aluminum Cleanliness Benchmarking
We’ve rigorously validated the AMCA method against industrial PoDFA and LiMCA data to ensure it meets top industry standards for metal cleanliness. Our studies confirm AMCA’s precision and robustness across various sample types using both deterministic and deep learning models.
Flexible Approach
The AMCA method has been successfully applied to other image analysis tasks, such as polymer porosity quantification for medical devices, aluminum dross analysis via EPMA/EDS, and Hard Grey Scale analysis in aluminum off-gas production.
Contact us in the form below to learn more about our research.
Contact
MetIQ and AMCA Origins
MetIQ AS was founded in 2022 for the commercialization of the AMCA method.
AMCA originates from NTNU research at the Department of Materials Science and Engineering starting in 2011.
We are always welcoming new possibilities to take AMCA further.
Get in touch today to discuss your specific case.
Hannes Zedel, CEO & Co-founder
Contact Us Today!
Let us provide you with competitive quotes for your technical service needs.
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