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Quantifying change order impact on productivity by using ANN approach

Quantifying change order impact on productivity by using ANN approach. ECE 539 Project Presentation (Order: 316). Min-Jae Lee Construction Management Program Civil & Environmental Engineering Department University of Wisconsin - Madison . Change. Delta . Base.

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Quantifying change order impact on productivity by using ANN approach

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  1. Quantifying change order impact on productivity by using ANN approach ECE 539 Project Presentation (Order: 316) Min-Jae Lee Construction Management Program Civil & Environmental Engineering Department University of Wisconsin - Madison

  2. Change Delta  Base Direct Field Labor Hours Estimate Total Actual Labor Hours (Base + Change) (Hanna et al. 1999a, 1999b) 0 100 Construction Phase (% Complete) Research Background • Productivity loss (Delta:  ) happen • “Owner” & “Contractor” conflict ---Claims • We need “Models” developed by historical data Model 1: Was the project impacted by change orders or not Model 2: How much impacted by change orders

  3. Data Characteristics • 140 case study from U.S. area [impacted(50) / unimpacted(50)] • Ask 70 Indicator factors related with change orders • Find “significant factors” by using Statistical method (20 factors, correlation test, significant test)

  4. Model1: Logistic Regression • Model2: Regression Model • % delta = • + 0.36866 • + 0.11957 Percent Change • - 0.08065 PM%TimeOnProject • 0.16723 %OwnerInitiatedCO • 0.09147 Productivity • 0.05213 Overmanning • + 0.022345 ProcessingTime lXactual – Xestimatedl Xestimated Average = =72.2% %Error 75% Accuracy Previous Research & ANN approach Training data size: 100 cases, Testing sample size: 30 cases Model1(Impact): bp Model2(%Delta): RBN Output Output 20 feature factors 20 feature factors Impacted or Not % Delta

  5. Results & Discussion Model1(Impact): bp Logistic Regression C_rate = 71% Training C_rate = 87% Testing C_rate = 82% Model2(%Delta): RBN Regression Model: 73% RBN Model: 14% lXactual – Xestimatedl Xestimated Average %Error =

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