TY  - CONF
TI  - Value-Adding Index - Share of Direct Work Included in Uninterrupted Presence Time
C1  - Edmonton, Canada
C3  - Proc. 30th Annual Conference of the International Group for Lean Construction (IGLC)
SP  - 130
EP  - 141
PY  - 2022
DO  - 10.24928/2022/0115
AU  - Görsch, Christopher 
AU  - Jianyu, Zhao
AU  - Seppänen, Olli
AD  - Doctoral Candidate, Department of Civil Engineering, Aalto University, Espoo, Finland,  christopher.0.gorsch@aalto.fi, https://orcid.org/0000-0001-9632-4031
AD  -  Doctoral Candidate, Department of Civil Engineering, Aalto University, Espoo, Finland,  jianyu.zhao@aalto.fi, https://orcid.org/0000-0001-8519-6177
AD  - Associate Professor, Department of Civil Engineering, Aalto University, Espoo, Finland, olli.seppanen@aalto.fi, http://orcid.org/0000-0002-2008-5924 
AB  - Continuous improvement depends on appropriate productivity measures. Productivity can be measured through time-motion studies but relies heavily on manual efforts and therefore contributes insufficiently to real-time awareness in dynamic environments such as construction. Indoor positioning shows potential determining shares of construction workers VA (Value-adding), based on Bluetooth Low Energy technology in real-time. Different studies show positive correlations between VA and productivity. However, it is unknown from location data how much workers engage in VA work while being present. Applying both methods simultaneously to one worker, this paper shows how to numerically quantify direct work (DW) and VA. Such combined data can show how much VA and DW occur when uninterrupted presence is detected while applying thresholds, indicating minimum durations spent inside work locations. Utilizing a small data sample enabled proof-of-concept testing and resulted in numerical quantifications of DW and VA. Preliminary findings show larger proportions of DW and VA when uninterrupted presence time is higher. Future research needs to enlarge the included data. If findings hold true, uninterrupted presence with higher thresholds could predict more accurate workers´ VA levels in real-time. The study also contributes to knowledge positively impacting construction by bridging workers’ behaviors on-site with monitoring technologies detecting movement
KW  - Time-motion study
KW  - indoor-positioning
KW  - continuous improvement/kaizen
KW  - flow
KW  - lean  construction
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/1951/pdf
L2  - http://iglc.net/Papers/Details/1951
N1  - Export Date: 28 April 2024
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -