Showing papers on "Tool wear published in 2003"

Surface integrity in finish hard turning of case-hardened steels

Abstract: Highly stressed steel components, e.g., gears and bearing parts, are appropriate applications for hard turning. Therefore, the process effects on significant engineering properties of work materials have to be carefully analyzed. Roughness, residual stresses, and white layers as parts of surface integrity, are functions of the machining parameters and of the cuttability of the cutting edge, i.e. of the tool wear. The aim of this work was to study the influence of feed rate, cutting speed, and tool wear on the effects induced by hard turning on case-hardened 27MnCr5 gear conebrakes and to point out the technical limitations in mass production.

Drilling wear detection and classification using vibration signals and artificial neural network

Abstract: In automated flexible manufacturing systems the detection of tool wear during the cutting process is one of the most important considerations. This study presents a comparison between several architectures of the multi-layer feed-forward neural network with a back propagation training algorithm for tool condition monitoring (TCM) of twist drill wear. The algorithm utilizes vibration signature analysis as the main and only source of information from the machining process. The objective of the proposed study is to produce a TCM system that will lead to a more efficient and economical drilling tool usage. Five different drill wear conditions were artificially introduced to the neural network for prediction and classification. The experimental procedure for acquiring vibration data and extracting features in both the time and frequency domains to train and test the neural network models is detailed. It was found that the frequency domain features, such as the averaged harmonic wavelet coefficients and the maximum entropy spectrum peaks, are more efficient in training the neural network than the time domain statistical moments. The results demonstrate the effectiveness and robustness of using the vibration signals in a supervised neural network for drill wear detection and classification.

Machinability of hardened steel using alumina based ceramic cutting tools

Abstract: Alumina based ceramic cutting tool is an attractive alternative for carbide tools in the machining of steel in its hardened condition. These ceramic cutting tools can machine with high cutting speed and produce good surface finish. The wear mechanism of these ceramic cutting tools should be properly understood for greater utilization. Two types of ceramic cutting tools namely Ti[C,N] mixed alumina ceramic cutting tool and zirconia toughened alumina ceramic cutting tool are used for our investigation. The machinability of hardened steel was evaluated by measurements of tool wear, cutting forces and surface finish of the work piece. These alumina based ceramic cutting tool materials produce good surface finish in the machining of hardened steel. In this paper an attempt is made to analyse the important wear mechanisms like abrasive wear, adhesive wear and diffusion wear of these ceramic cutting tool materials and the performance of these ceramic cutting tools related to the surface finish is also discussed here.

Hybrid machining of Inconel 718

Abstract: A new approach for machining of Inconel 718 is presented in this paper. It combines traditional turning with cryogenically enhanced machining and plasma enhanced machining. Cryogenically enhanced machining is used to reduce the temperatures in the cutting tool, and thus reduces temperature-dependent tool wear to prolong tool life, whereas plasma enhanced machining is used to increase the temperatures in the workpiece to soften it. By joining these two non-traditional techniques with opposite effects on the cutting tool and the workpiece, it has been found that the surface roughness was reduced by 250%; the cutting forces was decreased by approximately 30–50%; and the tool life was extended up to 170% over conventional machining.

Development of a tool wear-monitoring system for hard turning

Abstract: This paper describes an in-depth study on the development of a system for monitoring tool wear in hard turning. Hard turning is used in the manufacturing industry as an economic alternative to grinding, but the reliability of hard turning processes is often unpredictable. One of the main factors affecting the reliability of hard turning is tool wear. Conventional wear-monitoring systems for turning operations cannot be used for monitoring tools used in hard turning because a conglomeration of phenomena, such as chip formation, tool wear and surface finish during hard turning, exhibits unique behavior not found in regular turning operations. In this study, various aspects associated with hard turning were investigated with the aim of designing an accurate tool wear-monitoring system for hard turning. The findings of the investigation showed that the best method to monitor tool wear during hard turning would be by means of force-based monitoring with an Artificial Intelligence (AI) model. The novel formulation of the proposed AI model enables it to provide an accurate solution for monitoring crater and flank wear during hard turning. The suggested wear-monitoring system is simple and flexible enough for online implementation, which will allow more reliable hard turning in industry.

Self-optimization in tool wear for friction-stir welding of Al 6061+20% Al2O3 MMC

Abstract: Tool wear and the rate of wear for hardened, steel, right-hand screws rotating at 1000 rpm in the friction-stir welding of Al 6061+20 vol.%Al2O3 particles were observed to decrease for increasing weld or traverse speeds. When sufficiently long traverse distances were reached, tool wear became small or negligible, and an optimized tool shape emerged. This shape was slightly different at 6 and 9 mm s−1 weld speeds but in each case a self-optimized tool shape emerged. This self-optimizing wear phenomena and tool shape result by counter motions of solid-state flow regimes which depend upon both tool rotation speed and actual weld traverse speed. Although sound, porosity-free welds are obtained with both the unworn, threaded pin tool and the worn, unthreaded pin tool, microstructures vary and the worn pin tool produced a narrower heat affected zone with less drop in hardness than the threaded pin tool.

Role of temperature and surface finish in predicting tool wear using neural network and design of experiments

Abstract: The present work focuses on the two of the techniques, namely design of experiments and the neural network for predicting tool wear. In the present work, flank wear, surface finish and cutting zone temperature were taken as response (output) variables measured during turning and cutting speed, feed and depth of cut were taken as input parameters. Predictions for all the three response variables were obtained with the help of empirical relation between different responses and input variables using design of experiments (DOE) and also through neural network (NN) program. Predicted values of the responses by both techniques, i.e. DOE and NN were compared with the experimental values and their closeness with the experimental values was determined. Relationship between the surface roughness and the flank wear and also between the temperature and the flank wear were found out for indirect measurement of the flank wear through surface roughness and cutting zone temperature.

Effect of chamfer angle on wear of PCBN cutting tool

Abstract: In precision hard turning, a remaining problem is to minimise tool wear to maintain the accuracy of geometry and surface finish. Tool wear not only directly reduces the part geometry accuracy but also increases cutting forces drastically. The change in the cutting forces also causes instability in the tool motion, which results in more inaccuracy. PCBN cutting tools are often used in hard turning. However, they are still relatively expensive compared to ordinary carbide cutting tools. In order to attain sufficiently high production rates at minimum cost, increase of knowledge on cutting tool geometry is necessary. This article presents a study of the effect of chamfer angle on tool wear of PCBN cutting tool in the super finishing hard turning. The correlation between cutting force, tool wear and tool life were investigated. The optimised chamfer angle for PCBN cutting tool is suggested. Finally, the distribution of stresses and maximum principal stress working on the tool edge were calculated with the use of finite element method.

Influence of refrigeration/lubrication condition on SAE 52100 hardened steel turning at several cutting speeds

Abstract: Nowadays, the use of cutting fluids on machining operations has been questioned, due to problems they may cause to the environment, due to damage to human health and also more due to the severe laws regarding industrial waste that have been passed. Therefore, industries are being forced to review the production processes aiming either, at elimination or, when it is not possible, a sharp reduction in the use of these fluids. The technique of minimum volume of oil (MVO) has been studied in machining processes as one alternative to the use of abundant cutting fluid. Research has shown that this technique, which is the pulverisation of a minimum volume of oil in a flow of compressed air, in several cases, reduces tool wear when compared to complete dry cutting, causing the improvement of the workpiece surface quality and an increase in tool life. In this work, the influence of MVO (oil flow of 10 ml/h) in the wear of a cubic boron nitride (CBN) tool, when turning 52100 hardened steel, was studied. Aiming at a comparison of the results, the experiments were also carried out under two other conditions: dry cutting and cutting with abundant soluble oil (wet cutting). During the experiments, the influence of cutting speed on CBN tool wear for the three refrigeration conditions was also checked. Besides this, tool wear and workpiece surface roughness was also measured as cutting time elapsed.

A Curvilinear Tool-Path Method for Pocket Machining

Abstract: A novel curvilinear tool-path generation method is described for planar milling of pockets. The method uses the solution of an elliptic partial differential equation boundary value problem defined on a pocket region. This mathematical function helps morph a smooth low-curvature spiral path in a pocket interior to one that conforms to the pocket boundary. This morphing leads to substantial reductions of tool wear in cutting hard metals and of machining time in cutting all metals, as experiments described here show. A variable feed-rate optimization procedure is also described. This procedure incorporates path, tool-engagement, and machine constraints and can be applied to maximize machine performance for any tool path.

A novel approach to quantifying tool wear and tool life measurements for optimal tool management

Abstract: It is a common practice in batch production to continually use the same tool to machine different parts, using disparate machining parameters. In such an environment, the optimal points at which tools have to be changed, while achieving minimum production cost and maximum production rate within the surface roughness specifications, have not been adequately studied. The tool wear index (TWI) and the tool life model developed in this study use a novel approach, analyzing wear surface areas and material loss from the tool using micro-optics and image processing/analysis algorithms. With relation to surface roughness, the TWI measures the wear conditions more accurately and comprehensively, and the tool life model enables maximum use of a worn tool and minimum risk for in-process tool failure. The TWI and a surface roughness control model are integrated into an optimal control strategy that shows potential for productivity improvement and reduction of manufacturing cost.

Tool wear and chip formation during hard turning with self-propelled rotary tools

Abstract: This paper presents a performance assessment of rotary tool during machining hardened steel. The investigation includes an analysis of chip morphology and modes of tool wear. The effect of tool geometry and type of cutting tool material on the tool self-propelled motion are also investigated. Several tool materials were tested for wear resistance including carbide, coated carbide, and ceramics. The self-propelled coated carbide tools showed superior wear resistance. This was demonstrated by evenly distributed flank wear with no evidence of crater wear. The characteristics of temperature generated during machining with the rotary tool are studied. It was shown that reduced tool temperature eliminates the diffusion wear and dominates the abrasion wear. Also, increasing the tool rotational speed shifted the maximum temperature at the chip–tool interface towards the cutting edge.

Application of statistical filtering for optical detection of tool wear

Abstract: The application of automated tool condition monitoring systems is very important for unmanned machining systems. Tool wear monitoring is a key factor for optimization of the cutting processes. Basically, tool wear monitoring systems can be subdivided into two classes: direct and indirect. Currently direct tool wear monitoring systems are most frequently based on machine vision by camera. Several approaches have been studied for tool wear detection by means of tool images, and an innovative statistical filter proved to be very efficient for worn area detection. A new approach has been implemented and tested in order to develop an automatic system for tool wear measurement. This new approach is described in this paper and the main topics related to tool wear monitoring using wear images have been discussed.

Modelling of the cutting temperature distribution under the tool flank wear effect

Abstract: The understanding of cutting temperature distribution at the presence of tool wear can aid in addressing important metal cutting issues such as part surface integrity, tool life and dimensional tolerance under practical operating conditions. The effect of tool wear on the cutting temperature distribution was first modelled by Chao and Trigger and there have been very few followers since. In Chao's model, the primary heat source was assumed to have no effect on the workpiece temperature rise and the chip temperature rise was treated as a bulk quantity. This paper analytically quantifies the tool wear effect by taking into account the contributions of the primary heat source and considering the distribution of chip temperature rise. On the chip side, the primary shear zone is modelled as a uniform moving oblique band heat source and the secondary shear zone as a non-uniform moving band heat source within a semi-infinite medium. On the tool side, the effects of both the secondary and the rubbing heat...

A theoretical wear model for diamond tools in stone cutting

Abstract: Metal-bonded diamond tools have been introduced to the processing of stone several decades ago. Today this type of process is carried out following tool-makers prescriptions, however tools often declared similar by manufacturers actually exhibit different behaviour and performance. Therefore, the study of a wear model is very important in order to define methods of selection for both tools and machining conditions. Since the tool wear in cutting process is a multidimensional problem of great complexity, the inductive method, based on empirical testing and results interpolation, is the most common in the literature. In this study, in order to attain a key of interpretation of the tool wear process in stone cutting, as well as to attain some criteria to plan sawing tests, a theoretical model of the tool wear is presented, which has been tested using experimental results drawn from the current literature.

Vibration-Assisted Precision Machining of Steel with PCD Tools

Abstract: This article presents experimental results of precision machining of steel alloys with polycrystalline diamond tools. Ultrasonic vibration-assisted cutting was tried out for expanding the application of diamond tools for high-precision and high-quality machining of ferrous materials. The experimental results show that compared with conventional turning, the cutting performance, in terms of cutting force, surface finish, and tool life, was improved by applying ultrasonic vibration to the cutting tool. The cutting forces and tool wear measured in vibration cutting are much lower than those in conventional cutting. The tool wear mechanism was discussed on the basis of the observation of wear zone.

Microstructure and tool electrode erosion in EDMed of TiN/Si3N4 composites

Abstract: Conductive TiN/Si3N4 ceramic composites were processed by electrical discharge machining (EDM) and their microstructure and conductivity were investigated. The whole process of tool electrode wear is evaluated by sinker-EDM. The machined surfaces of TiN/Si3N4 ceramic composites were examined by scanning electron microscopy (SEM) and profilometry to determine the surface finish. The electrode wear rate of brass is higher than copper electrode for all EDMed tests. The surface texture was found to have greater dependence on pulse energy. It was observed that the sinker-EDM at higher pulse energy caused severe microdamage in the surface. The surface roughness (Ra) values also increase with increasing pulse energy.