Institute for Systems Research

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Author: search.filters.author.Zhang, G.M.Subject: search.filters.subject.measurements

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    Control of Machining Induces Edge Chipping on Glass Ceramics
    (1996) Ng, S.J.; Le, Dung T.; Tucker, S.R.; Zhang, G.M.; ISR
    Edge chipping is a phenomenon commonly observed during the machining of ceramic material. Characterization of edge chipping, both in macro and in micro scale, and correlating its formation to machining parameters form a basis for developing new and innovative technologies for controlling in machining induced damage. An experimental-based study using glass ceramic material is performed. Three types of edge chipping are identified. The SEM-sterephotography method and the finite element method are used to evaluate the edge chipping effect under a set of machining conditions. Significant findings are obtained and guidelines for controlling edge chipping during machining are suggested.
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    Characterization of the Surface Texture Formed During the Machining of Ceramics
    (1995) Zhang, G.M.; Ng, S.J.; Le, Dung T.; Job, Lenox S.; ISR
    This paper presents the development of a computer-based system to perform characterization of the surface texture formed during the machining of ceramic material. Techniques of image processing and computer graphics are employed to display vivid pictures of micro-scale details of the machined surfaces. Special attention is given to establishing the interrelations between the surface texture formation and the grain facet fracture induced by machining. Results obtained from microscopic analysis of the formed surface texture reveal that grain pullouts and cleavage, as a result of the progressive development of grain boundary micro-cracking, are two mechanisms responsible for the material removal process. The surface texture is an aggregation of macro and micro-scale fractured facets. A new performance index  cavity density is introduced to quantify the combinational effect of material microstructure and the dynamic loading during machining on the micro-mechanisms of the material removal process.
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    Study of the Formation of Macro-and-Micro-Cracks during Machining of Ceramics
    (1993) Zhang, G.M.; Anand, Davinder K.; Ghosh, Subrata; Ko, Wing F.; ISR
    This paper presents an experimental study on the formation of macro- and micro- cracks formed during the machining of ceramic materials. Aluminum oxide (Al2O3) was used as the testing material and polycrystalline diamond tipped carbide inserts were used for material removal. The cutting force was recorded during machining and surface finish was measured after machining. an environmental SEM was used to obtain high-magnification images of macro- and microcracks induced by machining. With the assistance of a computer-based vision system, qualification of fracture surfaces with respect to crack nucleation, growth, and cleavage was attempted. Results from this research provide an insight into the prevailing mechanisms of material removal during the machining of ceramics, and suggest the development of crack- controlled machining technologies.
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    A Stochastic Modeling for the Characterization of Random Tool Motion during Machining
    (1992) Hwang, Tsu-Wei; Zhang, G.M.; ISR
    This paper presents the development of a new stochastic approach to characterize random tool motion during machining. The complexity of cutting mechanism is represented by a random excitation system related to physical properties of the material being machined. A Markov-chain based stochastic approach is developed to model the random tool motion as the response of a machining system under the random excitation. In considering a turning operation, a concept of group distributions is introduced to characterize the global effect on the cutting force due to the variation of a certain material property. A model of segment excitation is used to describe its micro function within an individual revolution. A distribution pattern observed in the material property is represented by a transition model. The simulation of random tool motion during machining resembles the generation of Markov chains. Microstructure analysis and image process are used to collect data, calculate relevant statistics, and estimate the system parameters specified in the developed stochastic model. As illustrated in this paper, the developed stochastic model can be effectively used to simulate the random tool motion and to learn rich information on the performance measures of interest such as machining accuracy and finish quality. The new approach represents a major advance to create a fundamental scientific basis for the realization of a reliable and effective prediction system for information processing in sensor-based manufacturing.
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    Dynamic Visualization of the Surface Texture Formed During Machining
    (1991) Zhang, G.M.; Hwang, Tsu-Wei; Song, J.F.; ISR
    This paper presents a new methodology to study the properties of machined surfaces. A conceptual framework designed for dynamically visualizing the surface texture formed during machining is proposed. By integrating material science, machining science, and metrology science, the framework provides a systematic approach to investigate the mechanism of surface irregularity formation during machining. Studying the variability of basic material properties in micro-scale and relating this information to the surface texture formation during machining, this research provides a computer-based and comprehensive metrological system for industrial control and diagnostics of the surface quality during machining.