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Energy Management of Municipal Transportation Facilities and Transport

EMMFT-2018 2018: International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018 pp 166–173Cite as

Evaluation of the QMS Efficiency of Management Companies as a Criterion for the Effectiveness of Operation of “Intelligent Buildings”

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 983))

Abstract

The article describes an algorithm developed by the author for assessing a quality management systems (QMS) effectiveness of management companies, which involved in the operation of “intelligent buildings”. Unlike other approaches described in the scientific literature, this algorithm is based on the joint application of collective and individual expert assessments to form a set of criteria for evaluating the effectiveness of QMS and for determining each criteria’s level of significance. Formulas for rank calculation of the criteria and for determining a level of a relative increase/decrease in the effectiveness of the QMS are given. A graphic interpretation of the results of evaluating the effectiveness of the QMS and its trend is proposed. The algorithm takes into account the requirements of regulatory documents to assess the performance of the QMS.

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Author information

Authors and Affiliations

  1. Moscow State University of Civil Engineering, Yaroslavskoye shosse, 26, 129337, Moscow, Russia

    Nikolay Ivanov

Authors
  1. Nikolay Ivanov
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Correspondence to Nikolay Ivanov .

Editor information

Editors and Affiliations

  1. Moscow State University of Civil Engineering, Moscow, Russia

    Vera Murgul

  2. Department of Information Engineering, Università degli Studi di Brescia, Brescia, Italy

    Marco Pasetti

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Ivanov, N. (2019). Evaluation of the QMS Efficiency of Management Companies as a Criterion for the Effectiveness of Operation of “Intelligent Buildings”. In: Murgul, V., Pasetti, M. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. Advances in Intelligent Systems and Computing, vol 983. Springer, Cham. https://doi.org/10.1007/978-3-030-19868-8_16

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