Surface defect evolution in hot rolling of high-Si electrical steels

Lü

Materials Science and Technology

et al. 2019

Homogenisation has been used to eliminate solute segregation of CrMnFeCoNi high-entropy alloys (HEAs) before thermomechanical processing. To overcome the deficiencies caused by high-temperature homogenisation, we cancelled the homogenisation and studied the solute segregation feature and its effect on the grain growth and the mechanical property. The HEA forms equiaxed grains with the solute segregation in the range of tens of micrometres after cold rolling and recrystallisation. The grain growth in recrystallisation still abides by the classical grain growth kinetics, but with a higher power index of 3.33 and activation energy of 392.4 kJ mol−1 than those of the homogenised HEA, indicating a solute-drag effect. The relationship between the yield stress and grain size follows the Hall–Petch dependence with a higher intrinsic strength.

Section: Introductionmentioning

confidence: 99%

Solute segregation effect on grain boundary migration and Hall–Petch relationship in CrMnFeCoNi high-entropy alloy

Lü

Materials Science and Technology

et al. 2019

New Trends in Production Engineering

“…Such defects may be removed by subjecting a pipes to heat treatment or reclassification of the material to another strength group (Przybyłowicz, 1999). Surface defects are usually the result of defects in the mill equipment or other plant equipment and failure to follow the technological instructions (Nioi et al, 2017). The most common defects in shape are:  incorrect outer or inner diameter,  ovality,  incorrect wall thickness,  differentiating wall thickness,  incorrect straightness,  incorrect length,  incorrect length after removing the defect,  scratches, burrs and other mechanical damage,  defects in the shape and dimensions of pipes with mechanically machined ends.…”

Section: Defects and Incompatibilities Created During The Rolling Promentioning

confidence: 99%

Defects and Incompatibilities of Pipes Manufactured by Pilgrim Method

Biś

Koczurkiewicz

Mazur

2019

The increase in the quality requirements for the pipes and the increasing needs to reduce production costs, while increasing the efficiency of the process in market of hot rolled pipes are observed. One of the cost reduction factors is the reduction of the number of defects by early detection and, if possible, the removal of non-conformities. Incompatibility is an error that can be removed in accordance with the performance standard that does not cause defects (Norma API). The defect is imperfection that is so important that it is the basis for the removal of the product or its part based on the criteria set out in the performance standards. In pipe manufacturing processes, defects and batch incompatibilities can be distinguished, which arise in the steelworks during metal solidification and roll forming in the course of metal processing. The defect may also arise as a result of removing steel material or result from rolling processes defects. The paper presents the analysis of the process of quality control of pipes manufactured using the pilgrim method on the basis of real process data. The analysis were involved 1070 pieces of ingots from 11 different melts for rolling pipes. At various stages of production, discrepancies and defects were revealed, which were caused by metallurgical or technological defects associated with rolling pipes. The total amount of discrepancies and defects eliminated 168 pieces of finished pipes. The aim of the work is to show that by means of appropriately selected methods of eliminating imperfections, it is possible to increase the efficiency of the manufacturing process.

“…And some are associated with the shortcomings of the rolling equipment, its adjustment, calibration, wear, etc. When combined, violations of the casting and rolling technology contribute to the impairment of the rolled metal [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Recognition of Scratches and Abrasions on Metal Surfaces Using a Classifier Based on a Convolutional Neural Network

Konovalenko

Maruschak

Brevus³

et al. 2021

Metals

Classification of steel surface defects in steel industry is essential for their detection and also fundamental for the analysis of causes that lead to damages. Timely detection of defects allows to reduce the frequency of their appearance in the final product. This paper considers the classifiers for the recognition of scratches, scrapes and abrasions on metal surfaces. Classifiers are based on the ResNet50 and ResNet152 deep residual neural network architecture. The proposed technique supports the recognition of defects in images and does this with high accuracy. The binary accuracy of the classification based on the test data is 97.14%. The influence of a number of training conditions on the accuracy metrics of the model have been studied. The augmentation conditions have been figured out to make the greatest contribution to improving the accuracy during training. The peculiarities of damages that cause difficulties in their recognition have been studied. The fields of neuron activation have been investigated in the convolutional layers of the model. Feature maps which developed in this case have been found to correspond to the location of the objects of interest. Erroneous cases of the classifier application have been considered. The peculiarities of damages that cause difficulties in their recognition have been studied.