TY  - CONF
TI  - Robustness of Work Sampling for Measuring Time Waste
C1  - Edmonton, Canada
C3  - Proc. 30th Annual Conference of the International Group for Lean Construction (IGLC)
SP  - 247
EP  - 258
PY  - 2022
DO  - 10.24928/2022/0127
AU  - Wandahl, Søren 
AU  - Pérez, Cristina Toca 
AU  - Salling, Stephanie 
AU  - Lerche, Jon 
AD  - Professor, Department of Civil & Architectural Engineering, Aarhus University, Denmark,  swa@cae.au.dk, https://orcid.org/0000-0001-8708-6035
AD  - Postdoc, Department of Civil & Architectural Engineering, Aarhus University, Denmark,  cristina.toca.perez@cae.au.dk, https://orcid.org/0000-0002-4182-1492
AD  - Research Assistant, Department of Civil & Architectural Engineering, Aarhus University, Denmark,  stsa@cae.au.dk, https://orcid.org/0000-0001-7088-6458 
AD  - Postdoc, Department of Business Development and Technology, Aarhus University, Denmark,  jon.lerche@btech.au.dk, https://orcid.org/0000-0001-7076-9630
AB  - Construction can be considered a socio-technical system, which is challenging to model due to the many agents interacting either in a managed way or autonomously. Therefore, cause and effect models are hard to validate, and a traditional correlation approach is insufficient. In this study, the method of robustness testing was applied to test the effect stability when assumptions of a model are changed. The research objective is to apply robustness testing on WS data to assess the robustness and validity of the WS method. An actual refurbishment project was the case for this study, where data was acquired through nine days of continuous WS application. Time-series data were grouped into Direct Work (DW), Indirect Work, and Waste Work. Several different robustness tests were applied. It can be concluded that the WS method is robust, i.e., the effect (DW) is stable even if the assumptions are changed severely. Deleting 90% of the sample does, for instance, almost not change the effect. Likewise, if errors are infused into the sample, the effect is stable. Also, if certain structural parts are excluded from the sample, e.g., observations during morning startup, etc., the effect is still stable. 
KW  - Value stream
KW  - Waste
KW  - Trust
KW  - Robustness
KW  - Work Sampling
PB  - 
T2  - Proc. 30th Annual Conference of the International Group for Lean Construction (IGLC)
DA  - 2022/07/27
CY  - Edmonton, Canada
L1  - http://iglc.net/Papers/Details/1961/pdf
L2  - http://iglc.net/Papers/Details/1961
N1  - Export Date: 29 April 2024
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -