Manual operation simulation using motion-time analysis toward labor productivity estimation: A case study of concrete pouring operations

Ji Wook Kim, Alireza Golabchi, Sang Uk Han, Dong Eun Lee

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Based on the labor-intensive nature of construction tasks and high costs associated with labor operations, reliable estimation of construction labor productivity is crucial. However, owing to the dynamic nature and variety of tasks involved in a construction activity, obtaining accurate and reliable productivity data has proven to be difficult. Herein, a motion data-based modeling approach for estimating the labor productivity is proposed. The method consists of the following: estimating the standard motion time of the tasks, measuring the unit workload of an operation cycle using 3D models, and quantifying the production rates based on the cycle times and unit workloads. Motion-data analysis is also integrated into simulation modeling to incorporate the impact of jobsite conditions. To validate the proposed approach, a case study is applied for estimating the production rate of concrete placement operations. The results demonstrate that the proposed approach can reliably estimate the productivity of the operations.

Original languageEnglish
Article number103669
JournalAutomation in Construction
Volume126
DOIs
StatePublished - Jun 2021

Keywords

  • Building information modeling (BIM)
  • Cycle time estimation
  • Labor productivity
  • MTM-1
  • Predetermined motion time system (PMTS)
  • Simulation modeling

Fingerprint

Dive into the research topics of 'Manual operation simulation using motion-time analysis toward labor productivity estimation: A case study of concrete pouring operations'. Together they form a unique fingerprint.

Cite this