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Remote diagnosis design for a PLC-based automated system: 1-implementation of three levels of architectures

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Abstract

To troubleshoot the equipment installed in geographically distant locations, equipment manufacturers and system integrators are increasingly resorting to remote diagnosis, thereby achieving savings in cost and time for both customers and manufacturers. Remote diagnosis involves the use of communication technologies to perform fault diagnosis of a system located at a site distant to a troubleshooter. Several frameworks for remote diagnosis have been proposed, incorporating advancements such as automated fault diagnosis, collaborative diagnosis, and mobile communication techniques. Furthermore, standards for different levels of remote diagnosis exist. However, there has been relatively little research on the application of these levels of remote diagnosis architectures to diagnose failures in a discrete automated system. This paper is the first of two parts of a design for remote diagnosis for a programmable logic controller (PLC)-based discrete automated system. It investigates experimental variables, infrastructure, and hardware and software used for diagnosis in order to empirically validate the use of hierarchical levels of remote diagnosis architectures by experts to remotely diagnose failures in a PLC-based automated assembly line. Common failures in automated assembly systems were identified and duplicated. The suitability of each level of architecture for diagnosing different types of failures was evaluated based on ratings from experts in the field of automation. The experts opined that the architecture with the most advanced capabilities was most suitable for diagnosing failures related to measured or monitored system variables. For failures purely related to system hardware that could not be monitored, an architecture with basic capabilities was preferred.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Dwight Look College of Engineering, Texas A&M University, College Station, TX, 77843, USA

    Ramnath Sekar, Sheng-Jen Hsieh & Zhenhua Wu

  2. Department of Engineering Technology and Industrial Distribution and Department of Mechanical Engineering, Dwight Look College of Engineering, Texas A&M University, College Station, TX, 77843, USA

    Sheng-Jen Hsieh

Authors
  1. Ramnath Sekar
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  2. Sheng-Jen Hsieh
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  3. Zhenhua Wu
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Correspondence to Sheng-Jen Hsieh.

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Sekar, R., Hsieh, SJ. & Wu, Z. Remote diagnosis design for a PLC-based automated system: 1-implementation of three levels of architectures. Int J Adv Manuf Technol 57, 683–700 (2011). https://doi.org/10.1007/s00170-011-3314-6

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  • DOI: https://doi.org/10.1007/s00170-011-3314-6

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