Institute for Systems Research Technical Reports
Permanent URI for this collectionhttp://hdl.handle.net/1903/4376
This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.
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Item Control of Machining Induces Edge Chipping on Glass Ceramics(1996) Ng, S.J.; Le, Dung T.; Tucker, S.R.; Zhang, G.M.; ISREdge 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.Item Characterization of the Surface Cracking Formed during the Machining of Ceramic Material(1995) Zhang, G.M.; Ng, S.; Le, Dung T.; ISRThis paper presents a method to characterize the surface cracking formed during the machining of ceramics material. Ceramic specimens are prepared under two different machining environments, dry and submersion. An environmental scanning electron microscope is used to obtain high-magnification images of machined surfaces. Reconstruction of the surface texture in a three-dimensional space is made by scanning the images and using graphics software to obtain detailed and informative spatial views of the machined surface. The visualized surface cracks provide quantitative information on their size and shape. Two performance indices are proposed to characterize the distribution of surface cracks induced by machining in terms of the density and crack depth with reference to the machined surface. As a case study, the developed nondestructive evaluation method is used to assess the effectiveness of using the submerged machining to process ceramic material. The obtained results present a clear picture illustrating the capability of controlling the crack formation during the submerged machining.Item The Mechanics of Material Removal Mechanisms in the Machining of Ceramics(1994) Zhang, G.M.; Satish, K.G.; Ko, Wing F.; ISRThis paper presents a study on the mechanics of material removal for ceramic materials by observing single-point turning process of aluminum oxide (Al2O3). On-line cutting force measurement is performed and the surface integrity is characterized off-line by examining the surface texture. A theoretical analysis of fracture mechanics provides a comprehensive understanding of the chip formation process, and a model describing the material removal mechanisms is discussed. Based on the model, a systematic investigation of the chip fragments formed during machining is performed.Item Optical Area-Based Surface Quality Assessment for In-Process Measurement(1993) DeVoe, Don L.; Zhang, G.M.; ISRThe measurement of surface finish has been recognized as an important element of Computer Integrated Manufacturing (CIM) systems which perform on-line machining systems control. Optical methods for the in-process measurement of surface roughness have been developed for this purpose, but these systems have in many cases introduced excessive complexity in the CIM system. This work presents an area-based surface characterization technique which applies the basic light scattering principles used in other optical measurement systems. These principles are applied in a novel fashion which is especially suitable for in-process measurement and control. A prototype of the optical system to implement these principles is developed in this work. The experimental results are presented to demonstrate the capabilities and future potential for integrating the measurement system into a machining process to achieve significant improvement of quality and productivity.Item Estimation of Achievable Tolerances(1993) Gupta, Satyandra K.; Nau, D.S.; Zhang, G.M.; ISRThis report presents a new and systematic approach to assist decision-making in selecting machining operation plans. We present a methodology to estimate achievable tolerances of operations plan. Given an operation plan, we use variety of empirical and mathematical models to evaluate process capabilities of various machining operations and compute achievable tolerances using tolerance charting techniques.Item 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.; ISRThis 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.Item Mathematical Modeling of the Uncertainty for Improving Quality in Machining Operations(1993) Zhang, G.M.; Hwang, Tsu-Wei; Ratnakar, R.; ISRThe difficulty in quality improvement of machining performance comes from the uncertainty about the cutting force generated during the material removal process. This paper presents the results from the research aimed at developing a new approach to capture the uncertainty through mathematically modeling the physical machining system. a case study is used to demonstrate the procedure to interpret the cutting force variation through a three stage process. By integrating deterministic and stochastic approaches, an observed cutting force variation, which was recorded from an experiment, can be explained satisfactorily. The reduction of uncertainty allows an accurate prediction of the cutting force variation and forms a basis for developing a control strategy for improving the machining performance.Item Analysis of Elastoplastic Deformation Observed on Machined Surfaces(1993) Hwang, Tsu-Wei; Zhang, G.M.; ISRIn this paper, the study of material removal mechanism is focused on a non-linear quasi-static analysis of the elastoplastic interaction between a single-point cutting tool and the material being cut. An updated Lagrange procedure is applied to solve the large strain elastoplastic deformation problem which generates part of the irregularities observed on machined surfaces. A unique three-dimensional finite element model is developed to simulate the single-point metal cutting process. The effects of cutting parameter settings and workpiece material on the elastoplastic deformation of machined surfaces are investigated. The validity of this analysis is verified by experiments. The results of this analysis can be applied as a surface texture modification model to enhance the accuracy of a computer-aided surface texture simulator, an important part of a computer integrated manufacturing system.Item Implementation of an Integrated CAD and CAM System(1992) Chen, A.T.; Zhang, G.M.; ISRThis is a progress report on a joint research project between the University and the M.S. Willett, Inc. The research focus is on the integration of a CAD system and a CAM system currently being used at the Willett.The development of CAD systems has revolutionized the process of preparing engineering designs and drawings. Likewise, CAM systems have significantly impacted the stop floor production process. Numerically controlled machines have improved accuracy and productivity in many applications. Integration of these two systems would tie the design phase of a project to the production process, and if done efficiently, could result in significant cost reduction and quality improvement.
In this project, two computer programs have been developed to automate NC code generation directly from a CAD file, either in DXF format or in IGES format. These two programs have been successful in identifying the important elements of an integrated CAD and CAM system. The initial results also indicated how the Willett could shorten the time of product development cycle, low the production cost, and improve the quality of end products.
This project has been supported by the Center for Manufacturing on the College Park campus.
Item Neural Network Applications in On-line Monitoring of Turning Processes(1992) Zhang, G.M.; Khanchustambham, Raju G.; ISRThe need to improve quality and decrease scrap rate while increasing the production rate is motivating industry to consider untended machining as viable alternative. On-line monitoring of a machining process is the key component to success for an untended machining operation. In this chapter, a framework for sensorbased intelligent decision-making systems to perform on- line monitoring is proposed. Such a monitoring system interprets the detected signals from the sensors, extracts the relevant information, and decides on the appropriate control action. Emphasis is laid on applying neural networks to perform information processing, and to recognize the process abnormalities in a machining operation. A prototype monitoring system is implemented to demonstrate the working mechanism. For successful implementation of the developed intelligent monitor, an instrumented force transducer is designed for signal detection and is used in a real time turning operation. A neural network monitor based on feedforward back-propagation algorithm is developed and tested under the machining of advanced ceramic materials and steel. The monitor is trained by the detected cutting force signal, the measured surface finish, and the observed tool wear. The superior learning and noise suppression abilities of the developed monitor enable high success rates for monitoring in machining process.