Revolutionising Metal & Steel Characterisation

Precise characterisation of metals and steels is crucial in research and development as well as manufacturing quality control. This webinar explores how ZEISS revolutionises the field through modern microscopy and the integration of machine learning and deep learning algorithms to deliver deeper, faster and more predictive insights into metallurgical structures and performance.

ZEISS’s cutting-edge microscopy technologies enable detained analysis of microcstructures, revealing insights into material properties that are essential for optimising applications and manufacturing processes. High-resolution imaging facilitates a deeper understanding of grain structures, phase distributions and defect features that play a key role in material properties.

By coupling advanced microscopy techniques with machine learning and deep learning workflows, metallurgical studies gain sophisticated data interpretation and predictive capabilities. Machine learning models identify patterns and correlations within large datasets, while deep learning enhances feature extraction and classification to support more robust materials insights.

Through illustrative case studies, this webinar will demonstrate the transformative impact of combining modern microscopy with intelligent algorithms. Attendees will discover how this approach improves the accuracy, efficiency and depth of metallurgical analysis, paving the way for innovative applications and shaping the future of metals and steels characterisation.

Who Should Attend

This webinar is of interest to:
• Anybody in the metals and steels industry with a laboratory focus
• Quality assurance and quality control teams in metals manufacturing
• Microscopists working in metals analysis
• Professionals interested in advances in materials microscopy and data-driven interpretation