484 research outputs found

    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

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

    Get PDF
    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

    Non-Ionized, High-Resolution Measurement of Internal and Marginal Discrepancies of Dental Prosthesis Using Optical Coherence Tomography

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    The Retina in Health and Disease

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    Vision is the most important sense in higher mammals. The retina is the first step in visual processing and the window to the brain. It is not surprising that problems arising in the retina lead to moderate to severe visual impairments. We offer here a collection of reviews as well as original papers dealing with various aspects of retinal function as well as dysfunction. New approaches in retinal research are described, such as the expression and localization of the endocannabinoid system in the normal retina and the role of cannabinoid receptors that could offer new avenues of research in the development of potential treatments for retinal diseases. Moreover, new insights are offered in advancing knowledge towards the prevention and cure of visual pathologies, mainly AMD, RP, and diabetic retinopathy
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