Risk Management in CPM Networks

Riggs, Leland S.

doi:10.1111/j.1467-8667.1989.tb00022.x

Cited by 16 publications

(5 citation statements)

References 6 publications

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“…Merge event bias occurs when several paths converge on a single node (Riggs, ). When an overlap is applied to the predecessors and the successors that are located before and after a node in which a merge event occurs, multiple rework durations are generated because there are many predecessors having a direct relation with the successor.…”

Section: Concurrent Construction Scheduling Simulation Methodsmentioning

confidence: 99%

Concurrent Construction Scheduling Simulation Algorithm

Lim

Lee

et al. 2014

Computer aided Civil Eng

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A scheduler can accelerate a construction project by setting up overlapping activities. Activities are said to be overlapping if two activities that are normally executed in sequence are performed in parallel, the successor starting before the end of the predecessor. This article presents a novel method that identifies an optimal overlap rate between critical activities to provide a time‐cost trade‐off analysis, hence reducing completion time and cost without allocating additional resources. This method is then coded into Concurrent Construction Scheduling Simulation System (C2S2) that makes use of schedule data exported from Primavera Project Planner (P6), integrates the activities’ concurrency attributes, calculates the rework probability/amount, and computes the variability in project completion time and cost by adjusting the overlap between activities. This study is of value to practitioners because C2S2 allows establishing a compressed schedule that satisfies a limited budget within a specified contract duration. The study is also of relevance to researchers because it identifies the optimal overlaps between activities expeditiously. Two test cases verify the usability and validity of the computational methods implemented in the system.

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Section: Concurrent Construction Scheduling Simulation Methodsmentioning

confidence: 99%

Concurrent Construction Scheduling Simulation Algorithm

Lim

Lee

et al. 2014

Computer aided Civil Eng

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“…CPM uses a single number to estimate each activity duration [1][2][3]. Hence it does not provide enough information on the uncertainty and risk associated with the activity durations [4].…”

Section: Introductionmentioning

confidence: 99%

Estimating Project Completion Time with Monte Carlo Simulation

Fadjar

Nirmalawati

Hidayat

2022

RTCEJRD

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Risk and uncertainty are factors that construction project managers have been increasingly had to deal with. Project completion time is one of the areas where the expected time is often underestimated or shorter than the actual completion time. Monte Carlo simulation is a widely used simulation technique in modeling a process that is difficult to predict due to its random variables. This study provides a practical way to use Monte Carlo simulation to simulate a project using functions available in a spreadsheet application. A project with five activities was simulated 2000 times using minimum, maximum, and expected duration. The mean, mode, and median simulation results were then plugged into their respective precedence diagram networks to compare them. The precedence diagram computations found that mean, mode, and median project completion times were longer than the initially expected completion time. The mean, mode, and median were 50, 53, and 48 days, respectively, which were 8, 11, and 6 days longer, respectively, than the 42 days initially expected. The study showed that the Monte Carlo simulation could assist the project manager in planning a project schedule that deals with risk and uncertainty more realistically.

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“…Few attempts have been made to simulate project schedules (Carr, 1979;Woolery and Crandall, 1983;Ahuja and Nanclakumar, 1985). Riggs (1989) summarized past attempts in the area of simulation modelling for planning of construction processes. Early efforts can be traced back to Halpin (1977) who popularized it with his development of a system called cyclic operation network (Cyclone).…”

Section: Introductionmentioning

confidence: 99%

Estimating productivity using simulation

Rustom

Yahia

2007

Construction Innovation

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Purpose -Recently, there has been increased interest in the use of simulation for real-time planning, scheduling, control of construction projects and obtaining optimum productivity. The purpose of this case study is to demonstrate the use of simulation as an effective tool for estimating production rates in an attempt to prepare optimal time schedules. Design/methodology/approach -Gaza Beach-Camp Shore Protection Project was taken as a case study. The case study is used to demonstrate how to estimate effectively the production rates of labour and equipment during the implementation of the project activities and to estimate the duration of the project using process simulation. The model simulates the construction of 1,600 m of gabions divided into 32 identical stations. Probabilistic distribution functions were used to fit the time functions for each process and sub-process based on 100 replications. Findings -The simulation output generated three probabilistic values for completing each activity upon which the overall project completion time is determined. The resources utilizations for all processes were also generated and used in the determination of the average production rates. Originality/value -The computation of productivity based on effective resources utilization has been demonstrated to give better results than estimating productivity based on aggregate resources assignments.

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Risk Management in CPM Networks

Cited by 16 publications

References 6 publications

Concurrent Construction Scheduling Simulation Algorithm

Concurrent Construction Scheduling Simulation Algorithm

Estimating Project Completion Time with Monte Carlo Simulation

Estimating productivity using simulation

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