Delay Risk Assessment of Repetitive Construction Projects Using Line-of-Balance Scheduling and Monte Carlo Simulation

Tokdemir, Onur Behzat; Erol, Huseyin; Dikmen, İrem

doi:10.1061/(asce)co.1943-7862.0001595

Cited by 50 publications

(38 citation statements)

References 30 publications

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“…Luu et al [3] identified 16 factors of schedule risks and obtained 18 cause-and-effect relationships between these factors through 2 Complexity expert interviews to develop a belief network model. Tokdemir et al [13] assumed that risks originated from vagueness/uncertainty, task complexity, and vulnerability and defined the labor hour coefficients and the learning rate, both of which determined the activity duration, based on these factors. Cho et al [35] built a schedule delay estimation model with three fully connected layers: a project attributes layer, a risk factors layer, and a work variation layer.…”

Section: Literature Reviewmentioning

confidence: 99%

“…is can cause issues such as disorganized planned resources [11], increased communication costs, and misunderstandings [12], which initiates change risk propagation throughout an AON network [8,13]. erefore, it is essential to explore the mechanism of risk propagation of schedule changes.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, several studies have examined the modeling of construction schedule risks. Previous studies mainly focused on identification and evaluation of schedule risks [2-4, 9, 14], simulation of schedule risks in construction projects [10,13,15], and analysis of schedule risks with activity sensitivity information [16][17][18], but less attention has been paid to the topologies of AON networks and predicting the behavior of risk propagation from an overall perspective [8]. Managing risk propagation is a challenging task across numerous fields, ranging from finance [19], infrastructure management [20], and project management [8,[21][22][23].…”

Section: Introductionmentioning

confidence: 99%

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Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach

et al. 2020

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Construction schedules play an important role in construction project management. However, during construction activities, risks may arise due to unexpected schedule changes, resulting in the ineffective delivery of projects. This study aims to reveal the law of schedule change risk propagation and to analyze the effects on the risk propagation through numerical simulations. First, construction projects are represented by activity-on-node (AON) networks. A model of risk propagation is then built based on a susceptible-infected (SI) model considering the effects of the nodal characteristics on the propagation process. Next, the model is tested on a real-world project to examine cascading failures with varying parameters. The experimental results demonstrate that the model is effective in identifying the activities most capable of affecting a project schedule and evaluating the impact of schedule change risk propagation. This study will provide a basis for enhancing the robustness of AON networks and controlling the propagation of schedule change risks.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach

et al. 2020

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“…According to previous studies and project management body of knowledge (PMBOK), which is recognized as a fundamental rule of project management around the world, if historical data exists sufficiently, high accuracy duration estimation is possible [5]. However, most of the researches [6,[8][9][10] apply probability distribution to activity by expert judgment like three-point distribution due to lack of data availability. Therefore, for reliable results of analysis, it is an important issue how to develop data structure which is able to enhance data availability.…”

Section: Required Data Structure For Uncertainty Informationmentioning

confidence: 99%

“…For scheduling of EPC project schedule, a planned schedule is prepared, which consists of hundreds, or even thousands, of activities. In this case, the uncertainty of the individual activity duration is treated as probabilistic variables, and this probability should be estimated based on previous project experience and data [5,6].…”

Section: Introductionmentioning

confidence: 99%

Schedule Uncertainty Analysis System Framework to Manage and Allocate Historical Data for Industrial Construction Project

Yoon¹,

Lee²,

Park³

et al. 2019

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Many project managers and researchers have emphasized the importance of considering uncertainty in the scheduling of EPC projects, and perform stochastic analysis when preparing a schedule to reflect uncertainties of duration for project activities. In this case, the uncertainty of the individual activity duration is treated as probabilistic variables, and this probability should be estimated based on previous project experience and data. To use past project data for probabilistic schedule analysis of planned schedules, the schedule information of past project should be stored and managed systematically, and the analysis should be based on the relevant past project data. Existing schedule analysis tools are focused on the analysis process, and there is a lack of consideration on how to manage and apply the past project data needed for the schedule analysis. Therefore, this paper proposes a system framework that enables probabilistic schedule analysis, which automatically supports the process of identifying and allocating corresponding past project activities for estimating activity durations of a planned schedule. We propose a data model and system framework that reflects defined issues and the requirements. The framework is composed of 4 modules: As-built schedule data storage module, a planned schedule input module, a historical data allocation module, and uncertainty analysis module. It is expected that the proposed system framework will contribute to overcoming the difficulties of data management for collection and planned schedule analysis in practice.

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Holonic Construction Scheduling System for Construction Projects Using Python Programming Language

Gopinath,

Rukhsar

2023

Lecture Notes in Civil Engineering

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Delay Risk Assessment of Repetitive Construction Projects Using Line-of-Balance Scheduling and Monte Carlo Simulation

Cited by 50 publications

References 30 publications

Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach

Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach

Schedule Uncertainty Analysis System Framework to Manage and Allocate Historical Data for Industrial Construction Project

Holonic Construction Scheduling System for Construction Projects Using Python Programming Language

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