An Estimation of the Learning Curve Effect on Project Duration with Monte Carlo Simulation

Abstract

The aim of this paper is to estimate learning curve effect on project duration with the mean of project scheduling techniques. To measure this effect only one assumption is taken: the activity time individuals / groups take to perform an activity decreases at a given rate as experience is gained with the activity. Unfortunately this effect directly is not taken into account by project management software. In some software after scheduling, supervisor manually can switch on the "as soon as possible" or "as late as possible" buttons on an activity.
Monte Carlo simulation was used to model the risks in the total project durations. It is assumed that the (normal) durations of the activities can vary according to the beta distribution. The minimum estimate is 95 % of the original (normal) duration, and the maximum estimate is 140 % of the original (normal) duration. We assumed that most likely value is the (normal) duration of each activity. The learning effect on project duration with the help of test problems and real problems was investigated. In test problems learning effect can occur between two consecutive activities. These pairs are chosen randomly. After calculating project duration, these pairs are allocated to be closer to each other using the predecessor's total float time. It is assumed that the duration of impending repetitive activities is shorter due to the learning curve effect if the gap between consecutive activities is small enough. This iteration is carried out until it is not possible to shorten the successor's activity time in a pair. It is shown that this effect brings a 2-3 % shorter project duration meanwhile variance is also left in a 1-2 % range. Numerical tests were implemented by XPRESS-Mosel Optimization Software.