Learn Curve for Precast Component Productivity in Construction

Hsing Wei Tai, Jieh Haur Chen, Jiun Yao Cheng, Shu Chien Hsu, Hsi Hsien Wei

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

The study objective is to establish the learning curve model for precast component productivity in construction, verified using cross-validation empirical data for over 90% of these facilities’ precast component production activities over the past 5 years, with a total of 373,077 datasets across 14 production activities, sorted among a total of 4352 workers. By applying the learning curve theory to the analysis, the results show that relative to the straight-line model, the learning curve was established using exponential models. The exponential model can effectively mitigate the unreasonable fluctuations present in the cubic model’s representations of learning curves during initial training periods. This study therefore suggests the adoption of the Exponential model to model the learning curves for production workers learning to make precast components. The model has a satisfactory degree of fit (R2 > 0.88), and the post-cross-validation results also show that the model has a highly accurate prediction capability (MAPE value < 10%). The finding can serve as an important reference for the creation of production personnel allocation plans, personnel reserve plans, and training plans at precast factories in the construction industry.

Original languageEnglish
Pages (from-to)1179-1194
Number of pages16
JournalInternational Journal of Civil Engineering
Volume19
Issue number10
DOIs
Publication statusPublished - Oct 2021

Keywords

  • Construction industry
  • Exponential model
  • Learning curve
  • Precast components production

ASJC Scopus subject areas

  • Civil and Structural Engineering

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