Big Data as a Tool for Building a Predictive Model of Mill Roll Wear

Big data analysis is becoming a daily task for companies all over the world as well as for Russian companies. With advances in technology and reduced storage costs, companies today can collect and store large amounts of heterogeneous data. The important step of extracting knowledge and value from such data is a challenge that will ultimately be faced by all companies seeking to maintain their competitiveness and place in the market. An approach to the study of metallurgical processes using the analysis of a large array of operational control data is considered. Using the example of steel rolling production, the development of a predictive model based on processing a large array of operational control data is considered. The aim of the work is to develop a predictive model of rolling mill roll wear based on a large array of operational control data containing information about the time of filling and unloading of rolls, rolled assortment, roll material, and time during which the roll is in operation. Preliminary preparation of data for modeling was carried out, which includes the removal of outliers, uncharacteristic and random measurement results (misses), as well as data gaps. Correlation analysis of the data showed that the dimensions and grades of rolled steel sheets, as well as the material from which the rolls are made, have the greatest influence on the wear of rolling mill rolls. Based on the processing of a large array of operational control data, various predictive models of the technological process were designed. The adequacy of the models was assessed by the value of the mean square error (MSE), the coefficient of determination (R2), and the value of the Pearson correlation coefficient (R) between the calculated and experimental values of the mill roll wear. In addition, the adequacy of the models was assessed by the symmetry of the values predicted by the model relative to the straight line Ypredicted = Yactual. Linear models constructed using the least squares method and cross-validation turned out to be inadequate (the coefficient of determination R2 does not exceed 0.3) to the research object. The following regressions were built on the basis of the same operational control database: Linear Regression multivariate, Lasso multivariate, Ridge multivariate, and ElasticNet multivariate. However, these models also turned out to be inadequate to the object of the research. Testing these models for symmetry showed that, in all cases, there is an underestimation of the predicted values. Models using algorithm composition have also been built. The methods of random forest and gradient boosting are considered. Both methods were found to be adequate for the object of the research (for the random forest model, the coefficient of determination is R2 = 0.798; for the gradient boosting model, the coefficient of determination is R2 = 0.847). However, the gradient boosting algorithm is recognized as preferable thanks to its high accuracy compared with the random forest algorithm. Control data for symmetry in reference to the straight line Ypredicted = Yactual showed that, in the case of developing the random forest model, there is a tendency to underestimate the predicted values (the calculated values are located below the straight line). In the case of developing a gradient boosting model, the predicted values are located symmetrically regarding the straight line Ypredicted = Yactual. Therefore, the gradient boosting model is preferred. The predictive model of mill roll wear will allow rational use of rolls in terms of minimizing overall roll wear. Thus, the proposed model will make it possible to redistribute the existing work rolls between the stands in order to reduce the total wear of the rolls.

Analysis of Roll Wear Costs During Multi-Strand Rolling of Ribbed Bars Using New Slitting Pass System

The paper presents a modification of the slitting pass system, which ensured a reduction in roll wear during three-strand rolling of ribbed bars with a diameter of 16 mm, and thus reduced the associated costs. The theoretical and experimental research on the rolling process of ribbed bars with a diameter of 16 mm rolled in three-strand technology was carried out on a D350 18-stand continuous bar rolling mill conditions. To determine the cost of slitting pass wear, the results of numerical calculations of the frictional force unit of work obtained using the Forge2011® computer program was used, as well as empirical calculations.

Influence of Heat Treatment on the Wear Behavior of a Haynes 282® Nickel-Based Superalloy

Superalloys are metallic systems commonly used in components for aerospace and energy generation applications. In this paper, results of an investigation developed to analyze the effect of heat treatment on the wear behavior of a Haynes 282® superalloy under sliding, nonlubricated conditions are presented. Room temperature pin-on-roll wear tests were undertaken at a constant load and for a fixed sliding distance of 7.5 km. It was found that the wear rate of the alloys was greater for the heat treated specimens compared to the specimens that were tested in a cast and forged condition. Inspection of the alloys in both metallurgical conditions suggests that the wear phenomenon was characterized mostly by severe plastic deformation of the alloy matrix at both surface and subsurface regions by the well-known mechanism of plowing. The test specimens also experienced the formation of a tribofilm whose characteristics were different for each test condition. The formation of tribofilms also had a considerable influence on the wear behavior of the systems studied because they were also present on the surface of the counter rolls with this phenomenon being an additional wear mechanism experienced by the tribosystems studied.

Review on Parameters Influencing the Rice Breakage and Rubber Roll Wear in Sheller

The present review deals with parameters influencing the rice breakage during rice milling operations and the effect of rubber roll Sheller in rice husk removal process. The main objective of rice milling system is to remove the husk and bran layer to produce the white rice. In this process, rubber roll sheller is used to remove husk from the grains by friction process. If the rubber material is too soft, there may not be sufficient shear force to husk the paddy. Wear will be minimum for rubber material with high hardness but indeed it pronounce the breakage of rice. Hence, for efficient husking the rubber roll material should possess the balance of physico-mechanical properties. Rice breakage depends on several other parameters like the type of harvest, drying temperature, drying methods, physical characteristics of paddy, husking characteristics, paddy moisture content, rubber roller speed, rubber roll pressure, paddy feed rate and fissures. Rubber roll wear depends on the type of rubber material attached to the roller, feed rate, roller speed, pressure etc.