40 research outputs found

    Modeling and Contour Control of Multi-Axis Linear Driven Machine Tools

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    In modern manufacturing industries, many applications require precision motion control of multi-agent systems, like multi-joint robot arms and multi-axis machine tools. Cutter (end effector) should stay as close as possible to the reference trajectory to ensure the quality of the final products. In conventional computer numerical control (CNC), the control unit of each axis is independently designed to achieve the best individual tracking performance. However, this becomes less effective when dealing with multi-axis contour following tasks because of the lack of coordination among axes. This dissertation studies the control of multi-axis machine tools with focus on reducing the contour error. The proposed research explicitly addresses the minimization of contour error and treats the multi-axis machine tool as a multi-input-multi-output (MIMO) system instead of several decoupled single-input-single-output (SISO) systems. New control schemes are developed to achieve superior contour following performance even in the presence of disturbances. This study also extends the applications of the proposed control system from plane contours to regular contours in R3. The effectiveness of the developed control systems is experimentally verified on a micro milling machine

    Self-Calibration of Two-Dimensional Precision Metrology Systems

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    In modern industry, there usually exist high-precision stages, such as reticle stages and wafer stages in VLSI lithography tools, metrology stages in coordinate measurement machines, motion stages in CNC machine tools, etc. These stages need high-precision measurement/metrology systems for monitoring its XY movement. As the metrology systems are quite accurate, we often cannot find a standard tool with better accuracy to implement a traditional calibration process for systematic measurement error (i.e., stage error) determination and measurement accuracy compensation. Subsequently, self-calibration technology is developed to meet this challenge and to solve the calibration problem. In this chapter, we study the self-calibration of two-dimensional precision metrology systems and present a holistic self-calibration strategy. This strategy utilizes three measurement views of an artifact plate with mark positions not precisely known on the un-calibrated two-dimensional metrology stage and constructs relevant symmetry, transitivity, and redundancy of the stage error of the metrology stage. The misalignment errors of all measurement views, especially including those of the translation view, are totally determined by detailed mathematical manipulations. Then, a redundant equation group is synthesized, and a least-square–based robust estimation law is employed to calculate out the stage error even under the existence of random measurement noise. Furthermore, as the determination of the misalignment error components of the measurement views is rather complicated but important in previous and the proposed methods, this chapter also significantly analyzes the necessity of this costly computation. The proposed approach is investigated by simulation computation, and the simulation results prove that the proposed determination scheme can calculate out the stage error rather exactly without random measurement noise. Furthermore, when there exist various random measurement noises, the calibration accuracy of the proposed strategy is also investigated, and the results illustrate that the standard deviations of the calibration error are consistently with the same level of those of the random measurement noises. All these results verify that the proposed scheme can realize the stage error rather accurately even under the existence of random measurement noise. The practical procedure for performing a standard self-calibration is also introduced for engineers to facilitate actual implementation

    Hierarchical control of complex manufacturing processes

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    The need for changing the control objective during the process has been reported in many systems in manufacturing, robotics, etc. However, not many works have been devoted to systematically investigating the proper strategies for these types of problems. In this dissertation, two approaches to such problems have been suggested for fast varying systems. The first approach, addresses problems where some of the objectives are statically related to the states of the systems. Hierarchical Optimal Control was proposed to simplify the nonlinearity caused by adding the statically related objectives into control problem. The proposed method was implemented for contour-position control of motion systems as well as force-position control of end milling processes. It was shown for a motion control system, when contour tracking is important, the controller can reduce the contour error even when the axial control signals are saturating. Also, for end milling processes it was shown that during machining sharp edges where, excessive cutting forces can cause tool breakage, by using the proposed controller, force can be bounded without sacrificing the position tracking performance. The second approach that was proposed (Hierarchical Model Predictive Control), addressed the problems where all the objectives are dynamically related. In this method neural network approximation methods were used to convert a nonlinear optimization problem into an explicit form which is feasible for real time implementation. This method was implemented for force-velocity control of ram based freeform extrusion fabrication of ceramics. Excellent extrusion results were achieved with the proposed method showing excellent performance for different changes in control objective during the process --Abstract, page iv

    Proceedings of ICMMB2014

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    Aeronautical Engineering: A continuing bibliography with indexes (supplement 166)

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    This bibliography lists 558 reports, articles and other documents introduced into the NASA scientific and technical information system in September 1983

    Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

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    Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems

    Friction Force Microscopy of Deep Drawing Made Surfaces

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    Aim of this paper is to contribute to micro-tribology understanding and friction in micro-scale interpretation in case of metal beverage production, particularly the deep drawing process of cans. In order to bridging the gap between engineering and trial-and-error principles, an experimental AFM-based micro-tribological approach is adopted. For that purpose, the can’s surfaces are imaged with atomic force microscopy (AFM) and the frictional force signal is measured with frictional force microscopy (FFM). In both techniques, the sample surface is scanned with a stylus attached to a cantilever. Vertical motion of the cantilever is recorded in AFM and horizontal motion is recorded in FFM. The presented work evaluates friction over a micro-scale on various samples gathered from cylindrical, bottom and round parts of cans, made of same the material but with different deep drawing process parameters. The main idea is to link the experimental observation with the manufacturing process. Results presented here can advance the knowledge in order to comprehend the tribological phenomena at the contact scales, too small for conventional tribology
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