Impact of Activity Sequencing on Reducing Variability

Søren Munch Lindhard, Farook Hamzeh, Vicente A. Gonzalez, Søren Wandahl, Lene Faber Ussing

Research output: Contribution to journalJournal articleResearchpeer-review

7 Citations (Scopus)
14 Downloads (Pure)

Abstract

Variation in production is a major cause of producing waste in onsite construction operations, resulting in a workflow that is full of delays and interruptions. To reduce the negative impact of waste in construction, production managers need to address the causes of the variation that results in such waste. This paper explains the way to reduce the effects of variation in construction by changing the task sequence arrangement. The study analyzed the effect of some different task sequence arrangements on the production gap, crew waiting time, and production delay by simulating a group of work tasks and changing the task sequence arrangement from linear to parallel. Accordingly, 100 work activities were simulated in 98 different sequence designs, using a stochastic discrete-event simulation model, during which the number of parallel activities was systematically increased. The main finding from the studied configuration is that arranging tasks in parallel increases waste, whereas it reduces project duration. Moreover, waste resulting from variation was found to be an additional cause of waste when accelerating the production. Finally, it was revealed that the impact of variation on the task sequence highly depends on how often the schedule is updated. This study helps production managers to better understand of how the task sequence arrangement affects production performance in onsite construction operations.

Original languageEnglish
Article number04019001
JournalJournal of Construction Engineering and Management
Volume145
Issue number3
Number of pages9
ISSN0733-9364
DOIs
Publication statusPublished - 2019

Keywords

  • Waste management
  • Stochastic processes
  • Managers
  • Construction wastes
  • Industrial wastes
  • Construction management
  • Linear analysis
  • Simulation models

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