E3S Web Conf.
Volume 91, 2019Topical Problems of Architecture, Civil Engineering and Environmental Economics (TPACEE 2018)
|Number of page(s)||7|
|Section||Environmental Management and Environmental Economics|
|Published online||02 April 2019|
Indicators of reliability and efficiency of construction production processes
Moscow State University of Civil Engineering, 129337, 26, Yaroslavskoe Shosse, Moscow, Russia
* Corresponding author: LossevKY@mgsu.ru
The study contributes to interrelation of innovative and traditional indicators of reliability and efficiency of construction production processes. The object of the article is organizational and technological potential of the processes of construction production and two of its research directions: 1) an infographic modeling of the parameters for the creation and functioning of systems of organizational design and management in construction; 2) a concept of organizational and technological potential (of the efficiency of the construction process). An important aspect of the sufficiency of the potential of the reliability of construction production is the use of a balanced system of interrelated indicators. The subjects of research in the article are innovative and traditional indicators of reliability and efficiency of construction production processes. The task of the study was to analyze interrelation of innovative and traditional indicators and determine groups of interrelated indicators and determine the average values of the readiness indicator value ranges. An infographic modeling method and a predominantly deterministic inverse multi-stage dynamic perspective factor analysis have been used in the study. The four groups of interrelated indicators have been determined for a construction company performance evaluation: financial, client, internal business processes, training and development. The average values of the readiness indicator value ranges have been obtained by the average statistical values of mean time between failures: 0.86-0.92 for technical equipment and SMIT; 0.80-0.85 for material resources and components; 0.78-0.83 for labor resources.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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