Defects such as shrinkage and gas porosity, oxide inclusions or the notorious oxide bifilms observed in High Pressure Die Casting (HPDC) are a major cause of rejection of cast components. Occurrence and characteristics of such defects naturally differ depending on casting process, cast alloy and processing as well as other boundary conditions, as does their impact on part properties. Producing parts without any defect is basically impossible. However, rejection of parts is costly specifically if defects are detected only late in the manufacturing chain, and it adds to the environmental footprint of casting processes. Reducing defect related process scrap and improving defect tolerance are key challenges for increased process efficiency, improved structural reliability, and making metal casting process more sustainable.

Thus the main questions to be answered to increase yield, and the focal points of the present session, are the following:

• How and for what reason do casting defects form?
• How can they be detected using non-destructive methods?
• What are their effects on the performance of the cast part?

Understanding why and how defects form is a prerequisite for eliminating them - or at least limiting their amount.

Detection of defects goes beyond locating and identifying them. Finding the defects and pinpointing both their coordinates as well as their geometry can give access to new ways of describing defect populations, e.g. in terms of spatial arrangement and linking them to processing conditions and behavior of the final part under operating conditions.

Understanding the effects of defects in detail allows to define criteria that better distinguish between good parts and rejects than common approaches like maximum pore size or porosity level in critical areas.

The interplay of these three main aspects can pave the way towards new levels of quality and performance in cast parts. It may also facilitate a change in perspective from avoiding defects at ever higher cost to accepting their presence based on a deeper understanding of how they affect the relevant characteristics of the component in question.

The session encourages contributions that establish quantitative links between process parameters, defect population characteristics, and component performance under quasistatic, dynamic and cyclic load. Integrated approaches combining experiments, advanced characterization techniques (X-ray CT etc.), process simulation, and data-driven or machine learning methods for defect prediction and quality control are especially welcome. All casting processes and materials are addressed, however, a certain focus is placed on High and Low Pressure Die Casting (HPDC, LPDC) of light alloys (aluminium, magnesium). Similarly, effects of defects predominantly relates to structural performance, but may also include relevant functional properties such as electrical or thermal conductivity.