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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15841
Title: An Architecture for Computational Control of an Industrial Machine for Classifying Chestnuts
Authors: Álvarez Valera, Hernán
Bolivar Vilca, Edwin
Cervantes Jilaja, Claudia
Cuadros Zegarra, Emil
Barrios Aranibar, Dennis
Patiño Escarcina, Raquel Esperanza
Keywords: Automation;Computer vision;Efficiency;Fruits;Information systems;Robotics;Automation process;chestnuts;Electrical components;Industrial automation;Industrial machines;Mechanical components;Mechanical modules;Selection algorithm;Information management
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.dc.relation.uri: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964354822&doi=10.1109%2fLARS-SBR.2015.52&partnerID=40&md5=eddfd63ac5f056af136c66ca5af789e5
Abstract: Nowadays, the automation of industrial machines increase the productivity and efficiency of the mass production business. These machines are mainly composed of expensive electrical and mechanical modules to achieve companies production goals. However, many of these do not have information systems capable of providing the user relevant production data. In this work, the authors present an architecture for industrial automation machines of the chestnuts selection process, obtaining some features such as efficiency, effectiveness, high free configurability and low cost of maintenance and construction. This architecture is composed by three different modules: Mechanical components module, responsible of the physical parts management which interact directly with the products. Electrical components module, responsible for transferring data between the computational and mechanical layer through sensors and programs made. Finally, computational layer, responsible for two main tasks: process the necessary selection algorithms, sending the results to the electronic layer and run an information system, used to manage basic machine control operations, and generate the production data through the time. © 2015 IEEE.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15841
ISBN: 9781467371292
Appears in Collections:Artículos de investigación

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