Multi-track laser cladding is the primary technology used in industrial applications for surface reinforcement and remanufacturing of broken parts. In this study, the influence of processing parameters on multi-track laser cladding was investigated using a Taguchi orthogonal experimental design. A multi-response grey relational analysis (GRA) was employed to identify laser cladding processing parameters that simultaneously optimize the flatness ratio of the coating and the cladding efficiency. The optimal parameters setting found by GRA were validated experimentally. Results showed that the flatness ratio and cladding efficiency were closely correlated to the overlap rate and laser power, where the overlap rate shows the most significant impact on the flatness ratio and the laser power shows the most significant impact on cladding efficiency. Results from the validation experiment were within one percent (0.97% error) of the predicted value. This demonstrates the benefits of utilizing GRA in laser cladding process optimization. The methods presented in this paper can be used to identify ideal processing parameters for multi-response multi-track laser cladding processes or other industrial applications.

The influence of processing parameters on the micro-hardness and wear resistance of a Ni-based alloy and titanium carbide (TiC) composite cladding layer was studied. Mathematical models were developed to predict the micro-hardness and wear resistance of the cladding layer by controlling the laser cladding processing parameters. Key processing parameters were the laser power, scanning speed, gas flow, and TiC powder ratio. The models were validated by analysis of variance and parameter optimization. Results show that the micro-hardness is positively correlated with laser power and TiC powder ratio, where the TiC powder ratio shows the most significant impact. The wear volume decreased with an increasing TiC powder ratio. The targets for the processing parameter optimization were set to 62 HRC for micro-hardness and a minimal volume wear. The difference between the model prediction value and experimental validation result for micro-hardness and wear volume were 1.87% and 6.33%, respectively. These models provide guidance to optimize the processing parameters to achieve a desired micro-hardness and maximize wear resistance in a composite cladding layer.

No abstract

No abstract

The densification of ferrous powder in high velocity compaction (HVC) is numerically captured by using discrete element method. Macro property (porosity), micro properties (coordination number (CN), radial distribution function (RDF) and unbalanced force), and meso properties (force chains and their orientations) are characterized and analyzed. The effect of force chains on the densification mechanism is studied. The densification in HVC is reciprocating in accordance with the evolution of local porosity and CN. This phenomenon can be promoted by the peak of unbalanced force. The number of peaks in RDF changes from three to four during densification. In addition, force chains evolve from top to bottom and then move in reverse. The distribution of force chains is related to the CN evolution, and the degree of densification is affected by the force chain strength. Force chains can promote densification by pushing particles and squeezing adjacent particles.