TY  - CONF
TI  - Workflow Issue Identification by Applying Location-based Work Sampling
C1  - Osaka and Kyoto, Japan
C3  - Proceedings of the 33rd Annual Conference of the International Group for Lean Construction (IGLC 33)
SP  - 587
EP  - 597
PY  - 2025
DO  - 10.24928/2025/0126
AU  - Madushanka, Malik
AU  - Fiirgaard, Tobias
AU  - Pérez, Cristina T.
AD  - Master student, Department of Civil & Architectural Engineering (CAE), Aarhus University (AU), malikmadushanka52@gmail.com, https://orcid.org/0009-0006-2562-5121,
AD  - Master student, CAE Department, AU, Denmark, tobias.fiirgaard@gmail.com, https://orcid.org/0009-0002-4078-3372
AD  - Tenure Track Assistant Professor, CAE Department, AU, Denmark, cristina.toca.perez@cae.au.dk, https://orcid.org/0000-0002-4182-1492
ED  - Seppänen, Olli 
ED  - Koskela, Lauri 
ED  - Murata , Koichi 
AB  - This study examines Location-Based Work Sampling (LBWS) to improve construction site management by identifying workflow issues. For that, a Case Study was conducted on a Danish new building project, and the workflows of three trades were observed. The LBWS application presented a structured four-step methodology: (1) activity and workspace identification; (2) data collection; (3) data visualization; and (4) data analysis. For the LBWS application, the “Ajour system” app was selected as the optimal software based on the technique “Choosing by Advantages”. At the data collection step, the authors registered 994 random observations of worker activities classified into six work activity categories (production, preparation, transportation, walking, talking, and waiting) and into four workspace categories (production, preparation, storage, and transportation workspace). Previous LBWS studies used a single workspace categorization. This study introduces a grid-based system to capture production dynamics. This study highlights LBWS as a powerful tool for optimizing workflows by identifying inefficiencies. It provides insights into (1) work activity analysis,  differentiating value-added vs. non-value-added tasks, reducing excessive walking and waiting times; (2) workspace and resource utilization, using heat maps to assess labor and material distribution; and (3) interferences and congestion, identifying workflow bottlenecks caused by overcrowding or mismanagement.
KW  - Location-based Work Sampling
KW  - workflow
KW  - heat map
KW  - job site.
PB  - 
T2  - Proceedings of the 33rd Annual Conference of the International Group for Lean Construction (IGLC 33)
DA  - 2025/06/02
CY  - Osaka and Kyoto, Japan
L1  - http://iglc.net/Papers/Details/2322/pdf
L2  - http://iglc.net/Papers/Details/2322
N1  - Export Date: 02 June 2025
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -