Visual data and predictive analytics for proactive project controls on construction sites

Jacob J. Lin, Mani Golparvar-Fard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents the theoretical foundation for a project controls system that improves understanding of how construction performance can be captured, communicated, and analyzed in form of a visual production system; predicts and effectively communicates the reliability of the weekly work plan and look-ahead schedules, supports root-cause assessment on plan failure at both project and task-levels; facilitates information flows; and decentralizes decision-making. Our model-driven system builds upon novel visual data analytics to map the current state of production in 4D (3D+time), compare to 4D BIM, and expose waste at both project and task-levels. Using predictive analytics and based on actual progress and productivity data, reliability in the future state of production is forecasted to highlight potential issues in a location-driven scheme and support collaborative decision making that eliminates root causes of waste. To evaluate the performance of our system, several case studies are conducted on real-world commercial building projects. It is shown that the developed system provides visual interfaces between people and information on and offsite, enables effective pull flows, decentralizes work tracking, facilitates in-process quality control and hand-overs among contractors, and most importantly transforms retroactive and task-driven workflows in contractor coordination meetings to proactive location-driven practices.

Original languageEnglish (US)
Title of host publicationAdvanced Computing Strategies for Engineering - 25th EG-ICE International Workshop 2018, Proceedings
EditorsBernd Domer, Ian F. Smith
PublisherSpringer-Verlag Berlin Heidelberg
Pages412-430
Number of pages19
ISBN (Print)9783319916347
DOIs
StatePublished - 2018
Event25th Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2018 - Lausanne, Switzerland
Duration: Jun 10 2018Jun 13 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10863 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other25th Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2018
CountrySwitzerland
CityLausanne
Period6/10/186/13/18

Keywords

  • Lean construction
  • Predictive data analytics
  • Visual production management

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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