2017Procedia EngineeringOpen access

An Estimation of the Learning Effect on Project Cost Scheduling

Levente Mályusz, Anita Varga

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Abstract

The effect of the learning phenomenon (learning curve) on project cost and scheduling is discussed in this paper. Although learning is an essential part of life, traditional scheduling techniques cannot efficiently handle the learning curve effect. It is assumed that the durations of impending repetitive activities, performed by the same workers, are shorter due to the learning curve effect, therefore no additional acceleration cost is necessary and the deployment cost before the second activity can also be neglected if the gap between consecutive activities is small enough. Taking into consideration the effects of the learning curve (or experience curve), it is possible to reduce project duration and cost. According to this study 0.4%-1% reduction in project cost and a 9-40% reduction in acceleration cost on a given project duration is available. Although the effect is a “simple” calculation, it leads to an exponential time algorithm if the learning effect is applied to traditional project scheduling techniques like Critical Path Method (CPM), or Precedence Diagramming Method (PDM). In this paper, an integer programming model is developed, and an efficient algorithm is used to estimate the project cost curve. The results are validated through an artificial example project.

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What this paper is about

The effect of the learning phenomenon (learning curve) on project cost and scheduling is discussed in this paper. Although learning is an essential part of life, traditional scheduling techniques cannot efficiently handle the learning curve effect. It is assumed that the durations of impending repetitive activities, performed by the same workers, are shorter due to the learning curve effect, therefore no additional acceleration cost is necessary and the deployment cost before the second activity can also be neglected if the gap between consecutive activities is small enough. Taking into consideration the effects of the learning curve (or experience curve), it is possible to reduce project duration and cost. According to this study 0.4%-1% reduction in project cost and a 9-40% reduction in acceleration cost on a given project duration is available. Although the effect is a “simple” calculation, it leads to an exponential time algorithm if the learning effect is applied to traditional project scheduling techniques like Critical Path Method (CPM), or Precedence Diagramming Method (PDM). In this paper, an integer programming model is developed, and an efficient algorithm is used to estimate the project cost curve. The results are validated through an artificial example project.

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Available abstract

The effect of the learning phenomenon (learning curve) on project cost and scheduling is discussed in this paper. Although learning is an essential part of life, traditional scheduling techniques cannot efficiently handle the learning curve effect. It is assumed that the durations of impending repetitive activities, performed by the same workers, are shorter due to the learning curve effect, therefore no additional acceleration cost is necessary and the deployment cost before the second activity can also be neglected if the gap between consecutive activities is small enough. Taking into consideration the effects of the learning curve (or experience curve), it is possible to reduce project duration and cost. According to this study 0.4%-1% reduction in project cost and a 9-40% reduction in acceleration cost on a given project duration is available. Although the effect is a “simple” calculation, it leads to an exponential time algorithm if the learning effect is applied to traditional project scheduling techniques like Critical Path Method (CPM), or Precedence Diagramming Method (PDM). In this paper, an integer programming model is developed, and an efficient algorithm is used to estimate the project cost curve. The results are validated through an artificial example project.

Key concepts: Learning curve, Critical path method, Scheduling (production processes), Learning effect, Computer science, Mathematical optimization, Integer programming, Software deployment

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