Sensor monitoring of chip form in turning of C45 carbon steel was performed through sensor fusion based signal feature extraction and pattern recognition aimed at single chip form classification and ...favourable/unfavourable chip type identification. Features from signals provided by a cutting force based sensor monitoring system were extracted through the Principal Component Analysis algorithm. Pattern recognition of chip form typology was performed by inputting the extracted features into feed-forward back-propagation neural networks.
This paper draws on the activities of the CIRP Collaborative Work on “Round Robin on Chip Form Monitoring” carried out within the Scientific-Technical Committee Cutting (STC-C). This collaborative ...work involved the following main round robin activities: (a) generation, detection, storage and exchange of cutting force sensor signals obtained at different Laboratories during sensor-based monitoring of machining processes with variable cutting conditions yielding diverse chip forms, and (b) cutting force signal (CFS) characterization and feature extraction through advanced processing methodologies, both aimed at comparing chip form monitoring results achieved on the basis of innovative analysis paradigms.
This paper aims to investigate cutting conditions influence on main cutting force and surface roughness based on considered chip form types in cast nylon turning operation with single-point high ...speed steel cutting tool. The 75 experiments were performed by average of three levels of cutting speed, five levels of cutting depth and five levels of feed rate. The results reveal that main cutting forces were increased by an increasing of cutting speed and cutting depth for all obtained chip form types for all chip form types. The surface roughness is affected by increasing of feed rate and reduction of cutting speed for 2.3 Snarled and 4.3 Snarled chip form types. The statistical path-coefficient analysis results are shown that the main cutting force affected by cutting speed, depth of cut and feed rate with total causal effect value of 0.5537, 0.4785 and 0.1718, respectively. The surface roughness is influenced by feed rate, cutting speed and depth of cut with 0.8400, -0.2419 and-0.0711 of total causal effect value, respectively. These results are useful to perform varying cutting conditions for high quality of workpiece in cast nylon turning by control the chip form type.
Chip-form/chip-breakability and tool-wear/tool-life are two important aspects commonly considered in evaluating the performance of a machining process. The advent of new grooved tools with complex ...chip-groove geometry has required a better understanding of the curling behavior of the chip for effective curling and breaking of the chip. This paper presents a methodology for modeling chip-curl in machining with progressively worn grooved tools from measured cutting forces by using the equivalent toolface (ET) model. The ET is an imaginary flat toolface formed by effective inclination and rake angles to represent a grooved tool. This is achieved by iteratively changing the effective angles to match the flat-faced forces, calculated from a predictive cutting force model, with the measured grooved tool forces. The variation of the ET orientations resulting from the combinations of the effective angles shows a good correlation with the chip-curl ratio (ratio of up-curl to side-curl calculated from the twist angle), defined to indicate the curling pattern of chip. In this paper, this methodology is extended to correlate chip curling when machining with progressive tool-wear mechanisms in grooved tools. Experiments have been performed to measure the cutting forces at varying stages of progressive tool-wear, and chips are collected for a range of cutting conditions. The anticipated chip-curl/chip-forms and the associated dominant tool-wear patterns from the use of the predictive ET model are correlated well with the experimental observations.
The reliability of machining operation is an essential requirement in a modern production system. Chip control is one major aspect with regard to turning operation and becomes significant in ...industrial automation. At present, toolpath simulation is available in most computer aided manufacturing (CAM) systems. However, only the rendering scene of the stock material shape changing during cutting and the resultant part are shown. The chips formed in the machining process are not modelled or displayed in the simulation. To assess the chip control properly, many models and simulation methods were developed for predicting the chip forms produced in the cutting operation. If the chip forms can be predicted using some of the mathematical models, the design and planning of the machining operation can be greatly assisted, especially in the shop-floor level. Apart from chip form prediction, modelling of the machining process and chip formation are also issues that must be considered. To do this, a chip modelling and simulation system is proposed. Based on the machining parameters settings, the corresponding chip model can be calculated and simulated for more realistic analysis.
The present paper first outlines the chip form mathematical model being used. The criteria to ensure that the theoretical model can be used to calculate the practical chip models effectively are described. Then the modelling of the chips and the simulation of the chip forming with computer graphic animation are explained. Several sets of turning parameters are used as examples to demonstrate how the corresponding chip models are calculated from the proposed system.
The Japan Society for Analytical Chemistry has developed new plastic certified reference materials (CRMs) for the analysis of four hazardous elements (Pb, Cd Cr and Hg) in plastics to ensure the ...quality control of analyses. These CRMs (named as JSAC 0601-1 and 0602-1) were prepared by leading a raw material liquid of polyester resin mixed with hardener and organometallic compounds into a flat mold. The obtained plastics plates were crushed in a chip form by a mill, and sieved to obtain 0.5∼1 mm size pieces. An interlaboratory comparison study was performed with the participation of 20 laboratories. z-scores of the robust method were applied for a statistical analysis. The certified uncertainties were determined at the confidence levels of 95%. These presented CRMs are the first reference materials for plastics in Japan for the analysis of hazardous metals contained in plastics, and are expected to be useful for the quality assurance and quality control of trace metals in plastics.
In this paper classification of chip form and main cutting force prediction of cast nylon in turning operation by using artificial neural network (ANN) are described. The multi-layer perceptron of ...back-propagation neural network (BPNN) was employed as a tool to classify a chip form following ISO 3685-1977(E) and predicted the tangential cutting force. The turning operation was performed by a conventional form of high speed steel cutting tool with various cutting speeds, feed rates and depths of cutting. The BPNN structure had two models consisting of classification and prediction model. Each model composes of an input layer, two hidden layers and one output layer. Input layer composes of three input parameters, including cutting speed, feed rate and cutting depth. Hidden layer contains twenty nodes on each layer. A node of output layer was determined for obtaining the results. The sixty data from the experiments were used for neural network training with optimum parameters equal 0.6 of training rate and 0.6 of momentum. A set of data from the fifteen turning operation experiments were employed for prediction. The results revealed that the classification accuracy for classification chip form was 86.67%; and the main cutting force prediction was 91.130% of accuracy. Therefore, the chip form and main cutting force in cast nylon turning operation can be classified and predicted with reasonable accuracy for a given set of machining conditions using ANN model.
This drill generates three particular type chips. It has narrow face of 0-degree rake angle. It has clearance between chip and drill flute (2nd rake face) near the narrow face. When the chip top ...comes in contact with the wall of drilled hole, the contact reaction twists chip due to the clearance. The twist causes “chip-lever effect” at outside of chip and decreases the frictional force at inside of chip. These effects make the shear angle large at both inside and outside of chip, and generate twist ribbon type chip. The twist ribbon type chip is gradually restrained by the flute. Then, the cross section of chip becomes U-shape (U-type chip). At deep hole stage, the chip is restrained by the flute and the drilled hole. The chip is compressed when its top reaches to drill chuck. U-shape cross section makes the compressive force strong. The strong compressive force progresses the bending of chip near the narrow face, and generates the wavy type chip. When the chip curl is restrained, the chip receives the forces at chip top and narrow rake face end. The chip acts as a lever. Then, strong force acts at the shear zone near the cutting edge. And the shear deformation zone is narrow. The narrow shear deformation zone is that the shear angle is large. The chip curl restraint makes the frictional force large. The large frictional force makes the shear angle small. Therefore, the chip becomes thin, when the chip lever effect is larger than the frictional effect.
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