Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103155
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Title: Determining worker training time for precast component production in construction : empirical study in Taiwan
Authors: Tai, HW
Chen, JH
Cheng, JY
Wei, HH 
Hsu, SC 
Liu, HC
Issue Date: Jan-2021
Source: Journal of construction engineering and management, Jan. 2021, v. 147, no. 1, 05020023
Abstract: This study is aimed at determining the worker training time and proficiency threshold for each activity in precast component production based on the learning curve theory. Training data for precast component production for the past 5 years were collected in Taiwan, including 317,832 datasets for 14 production activities involving a total of 4,352 worker participations and 492 completion times. A learning curve model for workers to master the manufacture of precast component was developed, yielding the major finding that training time for workers to learn precast component production has a learning curve slope=-0.75. The training time required to reach proficiency varies from 3.87 to 26.15 days for noncomplex activities. The findings also show that four out of 14 activities can be identified as complex with a learning curve slope of-0.75. Practitioners should mainly focus on worker training for those complex activities as the critical path to improving precast component productivity. The findings also provide thresholds (in days) for all activities, which helps to quantify how much time is needed to efficiently train workers for precast component production.
Keywords: Construction management
Learning curve
Precast component
Productivity
Training time
Publisher: American Society of Civil Engineers
Journal: Journal of construction engineering and management 
ISSN: 0733-9364
EISSN: 1943-7862
DOI: 10.1061/(ASCE)CO.1943-7862.0001964
Rights: © 2020 American Society of Civil Engineers.
This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://doi.org/10.1061/(ASCE)CO.1943-7862.0001964.
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