Prediction of machining accuracy based on geometric error estimation of tool rotation profile in five-axis multi-layer flank milling process

In five-axis multi-layer flank milling process, the geometric error of tool rotation profile caused by radial dimension error and setup error has great influence on the machining accuracy. In this work, a new comprehensive error prediction model considering the inter-layer interference caused by tool rotation profile error is established, which incorporates a pre-existing prediction model dealing with a variety of errors such as geometric errors of machine tool, workpiece locating errors, and spindle thermal deflection errors. First, a series of tool contact points on the tool swept surface in each single layer without overlapping with others are calculated. Second, the position of the tool contact points on the overlapped layers is updated based on the detection and calculation of inter-layer interferences. Third, all evaluated tool contact points on the final machined surface are available for completing the accuracy prediction of the machined surface. A machining experiment has been carried out to validate this prediction model and the results show the model is effective

Integration of tool error identification and machining accuracy prediction into machining compensation in flank milling

In a flank milling process, the tool rotation profile error induced by its radial dimension error, setup error, tool deflection, and wear has a great influence on the dimensional accuracy of the machined components. In this paper, we present an integrated identification of tool error, prediction of machining accuracy, and compensation methodology for tool profile error to improve the machining accuracy. Firstly, the tool errors are divided into static and dynamic errors based on the error characteristics and the corresponding error identification methods are established to recognize the tool error parameters. Secondly, the machining accuracy is predicted by a prediction model, and the tool error parameters are input into this model. Thirdly, a new tool error compensation method is developed and incorporated in the corresponding NC codes. Finally, some machining experiments have been carried out to validate the proposed identification-prediction-compensation methodology, and the results show that this methodology is effective

FNDC5/Irisin Inhibits the Inflammatory Response and Mediates the Aerobic Exercise-Induced Improvement of Liver Injury after Myocardial Infarction

Myocardial infarction (MI) causes peripheral organ injury, in addition to cardiac dysfunction, including in the liver, which is known as cardiac hepatopathy. Aerobic exercise (AE) can effectively improve liver injury, although the mechanism and targets are currently not well established. Irisin, mainly produced by cleavage of the fibronectin type III domain-containing protein 5 (FNDC5), is a responsible for the beneficial effects of exercise training. In this study, we detected the effect of AE on MI-induced liver injury and explored the role of irisin alongside the benefits of AE. Wildtype and Fndc5 knockout mice were used to establish an MI model and subjected to AE intervention. Primary mouse hepatocytes were treated with lipopolysaccharide (LPS), rhirisin, and a phosphoinositide 3-kinase (PI3K) inhibitor. The results showed that AE significantly promoted M2 polarization of macrophages and improved MI-induced inflammation, upregulated endogenous irisin protein expression and activated the PI3K/ protein kinase B (Akt) signaling pathway in the liver of MI mice, while knockout of Fndc5 attenuated the beneficial effects of AE. Exogenous rhirisin significantly inhibited the LPS-induced inflammatory response, which was attenuated by the PI3K inhibitor. These results suggest that AE could effectively activate the FNDC5/irisin-PI3K/Akt signaling pathway, promote the polarization of M2 macrophages, and inhibit the inflammatory response of the liver after MI