The Relationship between Cyclic Multi-Scale Self-Organized Processes and Wear-Induced Surface Phenomena under Severe Tribological Conditions Associated with Buildup Edge Formation

This paper presents experimental investigations of various interrelated multi-scale cyclic and temporal processes that occur on the frictional surface under severe tribological conditions during cutting with buildup edge formation. The results of the finite element modeling of the stress/temperature profiles on the friction surface are laid out. This study was performed on a multilayer coating with the top alumina ceramic layer deposited by CVD (chemical vapor deposition) on a WC/Co carbide substrate. A detailed analysis of the wear process was conducted by 3D wear evaluation, scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM/EDS) and electron backscattered diffraction (EBSD), as well as X-ray photoelectron spectroscopy (XPS) methods. The following cyclic phenomena were observed on the surface of the tribo-system during the experiments: a repetitive formation and breakage of buildups (a self-organized critical process) and a periodical increase and decrease in the amount of thermal barrier tribo-films with a sapphire structure (which is a self-organization process). These two processes are interrelated with the accompanying progression of cratering, eventually resulting in the catastrophic failure of the entire tribo-system.

Wear evaluation and microstructure analysis of cryogenically treated AISI 440C Bearing steel

In this research work, two types of cryogenic treatment such as deep cryogenic treatment (-196oC) and shallow cryogenic treatment (-80oC) have been adopted for wear resistance to increase in AISI 440C bearing steel. This paper has been focused to increase Wear Resistance (WR) through deep micro structural analyses, and also attention has been made to correlate the microstructure with the wear character of Deep Cryogenic treated (DCT) specimens, Conventional Heat Treated (CHT) specimens and Shallow Cryogenic Treated (SCT) specimens. Micro structural examinations have been carried out in the specimens through Scanning Electron Microscopy (SEM), Energy Dispersive Analysis of X-ray (EDAX) and X-Ray Diffraction (XRD). Wear characteristics of AISI 440C bearing steel has been studied. The outcome of the research disclosed that the DCT specimens have higher wear resistance than SCT and CHT specimens. The effective wear mechanisms recognized were the constitution of white layers and delamination of white layers. The microstructures of the materials have been varied through heat treatment process. The modification of Secondary Carbides (SCs) precipitation characteristics and its reduction of retained austenite in the microstructure have been correlated with wear character and these are the liable mechanism to raise the wear resistance of bearing steels through DCT.

Reliability of qualitative occlusal tooth wear evaluation using an intraoral scanner: A pilot study

Dental wear analysis through the use of an intraoral scanner is a reality of modern dentistry. This study aimed to investigate the reliability of qualitative tooth wear evaluation through three-dimensional images captured with an intraoral scanner and compared to clinical and photographic examinations. Eighteen adult volunteers of both genders (18 to 55 years old) were submitted to clinical exams, intraoral photographs and intraoral scanning protocol using an optical scanner (TRIOS® Pod, 3Shape, Copenhagen, Denmark). Occlusal tooth wear, from second to second premolars, was measured by two evaluators and reevaluated after 30 days, according to a slight modification of the method described by Mockers et al. Weighted Kappa was used to measure intra and inter-examiner agreement. The Friedman test was used to verify the differences among methods. Random and systematic errors were assessed using Bland-Altman plots. All statistical analysis was performed with p<0.05. There was a substantive agreement for clinical (K = 0.75) and photographic exams (K = 0.79) and a moderate agreement for intraoral scanner analysis (K = 0.60) for inter-examiner evaluation. A substantial intra-examiner agreement was obtained for both evaluators. No significant difference between the methods was observed (p = 0.7343 for examiner 1 and 0.8007 for examiner 2). The Bland-Altman plot confirmed no systematic errors between the methods and a random error of 0.25 with the scanner method when compared to clinical assessment. All three methods showed reliability in qualitative occlusal tooth wear evaluation. Intraoral scanning seems to be a sound and reliable tool to evaluate tooth wear when compared to traditional methods, considering the lower inter-examiner agreement and the inherent limitations of this pilot study. Further research will be necessary in order to achieve more robust evidence.

Research on online detection System of lathe tool wear based on Machine Vision

Machine tools are important factor to determine the surface quality of the workpiece, and the online detection of tool wear is of great significance to the production and processing. In this paper, turning tools are taken as the research object, the tool wear evaluation index is defined, and the online detection system of lathe tool wear based on machine vision is designed. The workpiece processing, tool wear image acquisition, transmission, storage, and processing are completed in this system. Aiming at the problem of tool wear state detection, an adaptive hybrid filtering method is proposed in order to remove noise in the image acquisition process, nonlinear transformation and unsharp masking methods are used to enhance tool wear image quality. The GrabCut improved algorithm is used to segment the tool wear image. The Canny edge detection operator with adaptive double thresholds is used to detect the edge of the tool wear area. Finally, the upper and lower boundaries of the tool wear area are detected by using the Hough transform method, and the wear value of the tool flank is calculated, which is compared with the blunt standard VB=06mm to determine whether the tool needs to be replaced. The accuracy of the detection method is verified by experimental measurement of the surface roughness of the workpiece after machining.

Tool Wear Evaluation Based on Design Space Exploration Coupled with Explicit Cutting Simulations and Cutting Forces Excitation Signature

Cutting operations are still one of the main methods used in the industry for surface generation in mass production. The dynamics of these processes are complex and having a good insight into the interdependencies of the nonlinear physical phenomena can be translated into better cutting performance. One of the main cutting tool geometrical parameter, usually associated with wear, is the cutting edge radius. Continuous direct evaluation of this parameter exhibits some important limitations offline, if this evaluation needs to be online the whole process becomes very complicated due to the measurement limitations that might appear. For online cases, the best approach is to determine the amplitude of this parameter indirectly using various side effects that can be correlated. One possible option is to monitor the vibrations generated by the resulting cutting forces. In the latest years, the usage of explicit finite element methods (FEM) to simulate the cutting processes has grown exponentially with the continuous increase of computation efficiency. With the help of Computer-Aided Engineering (CAE in short) solutions and using the latest advances in design space exploration (DSE) solutions, it is possible to create models able to parametrically explore a design space (DS), having precise targets, and also get the important correlations for all the important, quantifiable, cutting parameters. This paper presents an innovative method to create tool wear evaluation models focused mainly on the cutting edge radius indirect evaluation. The proposed method uses guided simulation loops able to generate a variety of dynamic signatures which are further post-processed to get a complex correlative model. The model can be applied in real cutting cases using the reciprocity property and can determine online the state of the cutting edge radius for further tool wear evaluation. The paper concludes with an analysis of the obtained model and the applicability of the data for the intended purpose.