Oil Processes VR Training View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-11-10

AUTHORS

Víctor H. Andaluz , José L. Amaquiña , Washington X. Quevedo , Jorge Mora-Aguilar , Daniel Castillo-Carrión , Roberto J. Miranda , María G. Pérez

ABSTRACT

In this paper a virtual reality solution is developed to emulate the environment and the operations of the pitching and receiving traps of pipe scrapers (PIG), with the aim of reinforcing the training of operators in oil camps. To develop this, the information was collected on various pitching and receiving traps of the real pipeline operating companies in the country, thus defining the basic and specific parameters for the virtual recreation of a typical trap model. The 3d models obtains from P&ID’s diagrams to interact with user. The environment, interaction and behavior of pipes was developed in a graphic engine, to make training tasks with real state procedures on the oil industry. The goal is save time, money, resources in the training and learning specific oil industry; and make available a base to simulate another complex process. More... »

PAGES

712-724

References to SciGraph publications

  • 2014-02. Recent Advances in Wavelength Selection Techniques for Hyperspectral Image Processing in the Food Industry in FOOD AND BIOPROCESS TECHNOLOGY
  • 2015. Industry 4.0 - Potentials for Creating Smart Products: Empirical Research Results in BUSINESS INFORMATION SYSTEMS
  • 2017. Virtual Reality System for Training in Automotive Mechanics in AUGMENTED REALITY, VIRTUAL REALITY, AND COMPUTER GRAPHICS
  • 2016. Unity3D-MatLab Simulator in Real Time for Robotics Applications in AUGMENTED REALITY, VIRTUAL REALITY, AND COMPUTER GRAPHICS
  • 2016. Immersive Industrial Process Environment from a P&ID Diagram in ADVANCES IN VISUAL COMPUTING
  • 2015-09. Firm Characteristics, Industry Context, and Investor Reactions to Environmental CSR: A Stakeholder Theory Approach in JOURNAL OF BUSINESS ETHICS
  • 2018. Virtual Reality Production Training System in the Scope of Intelligent Factory in INTELLIGENT SYSTEMS IN PRODUCTION ENGINEERING AND MAINTENANCE – ISPEM 2017
  • 2000. Structure of Advanced Planning Systems in SUPPLY CHAIN MANAGEMENT AND ADVANCED PLANNING
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  • 2018-07. Training genomic selection models across several breeding cycles increases genetic gain in oil palm in silico study in MOLECULAR BREEDING
  • Book

    TITLE

    Advances in Visual Computing

    ISBN

    978-3-030-03800-7
    978-3-030-03801-4

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-030-03801-4_62

    DOI

    http://dx.doi.org/10.1007/978-3-030-03801-4_62

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1109840813


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