The chemical, process, and energy generation industries are essential production industries worldwide. However, these traditionally powerful industrial sectors have been under ever-increasing cost pressure in recent years, so the companies are continuously trying to improve wage- and energy-intensive products as well as services through the use of digitalization of production processes, e.g., to use operational data to optimize processes by tailoring them to customer needs and, at the same time, cutting operation and production costs. The machines and equipment in these industries are typically operated for several decades and cannot be directly integrated into the newly developed digitized processes. One of the possibilities to perform a so-called smartification of the machines and equipment is to retrofit them with sensors and data processing hardware. The present paper presents a methodology for the systematic selection of sensors for retrofitting existing and operating plants. For this purpose, the requirements for the selection process have been established. The advantages and disadvantages of existing methods for sensor selection are presented and analyzed. Subsequently, a new methodology for sensor selection is presented and successfully validated in the retrofit process of an existing and still operating for 20 years 900 kW wind turbine.


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    Titel :

    Sensor Selection for Smart Retrofitting of Existing Plants


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Ivanov, Vitalii (Herausgeber:in) / Trojanowska, Justyna (Herausgeber:in) / Pavlenko, Ivan (Herausgeber:in) / Rauch, Erwin (Herausgeber:in) / Piteľ, Ján (Herausgeber:in) / Adamenko, Dmytro (Autor:in)

    Kongress:

    Design, Simulation, Manufacturing: The Innovation Exchange ; 2023 ; High Tatras, Slovakia June 06, 2023 - June 09, 2023



    Erscheinungsdatum :

    2023-05-23


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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