Working Group

Quantitative microstructural analysis

Committee members: 79

In the age of rapidly increasing digital networking at all levels of social life, a restructuring of industrial production in this respect is also under discussion. If one considers the currently valid standards and implementation regulations in material analysis, subjectively afflicted evaluation methods are often still the common practice. In order to enable a largely self-organized production process, the integration of digital image analysis methods is a necessary prerequisite. The Working Group Quantitative Microstructure Analysis deals with issues relating to the determination of microstructure parameters that can be determined from digital images. Of particular interest are those parameters that are closely related to the manufacturing conditions or material properties.

Chair

  • Dr. rer. nat. Marco Witte
    Salzgitter Mannesmann Forschung GmbH
Structure

Expert Committee

Materialography

Events
No upcoming events
  • Addressing industrial and scientific issues concerning the characterization and description of microstructures by means of quantitative methods.
  • Initiation of research and development projects: joint projects of universities, research institutes, and industrial companies.
  • Exchange of experience between users and developers working in the field of quantitative microstructure analysis, and networking.
  • Exchange of experience on the application of various image analysis programs.
  • Publication of development results produced within the framework of the Working Group.

The topics that have been dealt with for about 8 years are very broad and are held together, so to speak, by the bracket "digital image processing". The topicality also plays a role, so that successively further interesting tasks are added.
The first focus of general interest is the topic of reproducible measurement, where questions such as the suitability of test equipment, the adaptation of preparation methods, and the statistical treatment of measurement inaccuracies play a role.
Furthermore, the characterization of various materials plays an important role, with methods of artificial intelligence, in particular machine learning, being increasingly considered.
The support of ongoing research projects must also be mentioned. Among other things, this involves participation in project-accompanying committees and in interlaboratory tests. The focus here is mainly on cast materials.
Last but not least, the plant tours and visits to research laboratories held at the respective organizer's location represent a gain in knowledge that should not be underestimated.

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