Coarse grain refinement resulting from deformation heterogeneity induced for the mixed-grain structure of 316LN steel through limited deformation condition
Material and Manufacturing Technologies:

Coarse grain refinement resulting from deformation heterogeneity induced for the mixed-grain structure of 316LN steel through limited deformation condition

recently the deformation heterogeneity of 316LN steel with mixed-grain structures were examined experimentally, which showed that the MCGs were more affected to deform than fine grains even if MCGs are with hard orientations. Therefore, a two-stage technique was investigated to refine MCGs, which causes the advantage of this deformation heterogeneity.

Evaluation of Life cycle on tire derived fuel as another fuel in cement industry
Material and Manufacturing Technologies:

Evaluation of Life cycle on tire derived fuel as another fuel in cement industry

End-of-life tires are a challenging type of waste since they are difficult to shred and are expensive to treat and get rid of. However, tire-derived fuel is an extremely good alternative to the traditional fuels used in cement kilns, like oil, coal, and petroleum coke.

Additive manufacturing of metals: Evaluation Microstructure evolution and multistage control
Laser and Manufacturing Technologies:

Additive manufacturing of metals: Evaluation Microstructure evolution and multistage control

Based on recent studies, formation mechanisms of multistage microstructures are examined and then the techniques of microstructure control are presented. Additively manufactured microstructures are developed during and after solidification of melt pool. A comprehensive processing map is presented for metals additive manufacturing.

Analysis of predictors for modification of alumina inclusions in medium carbon steel
Material and Manufacturing Technologies:

Analysis of predictors for modification of alumina inclusions in medium carbon steel

Recently, “inclusions engineering” has engaged a linked area in terms of improvements in processes and products in steelmaking. Because these compounds, depending on the chemical nature, morphology, physical state, size and distribution, damage both the processes and the mechanical properties of the final product.

The applications of Machine learning and process intelligence for cement industries
Material and Manufacturing Technologies:

The applications of Machine learning and process intelligence for cement industries

Estimating energy consumption in cement mills is critical for the cement industry. Following data science practices and adopting machine learning (ML) technologies, a recent research study developed energy consumption prediction models for a cement mill of TITAN SA plant in Kamari Viotia.

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