Schedule Risk Analysis using a Proposed Modified Variance and Mean of the Original Program Evaluation and Review Technique Model (original) (raw)
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This document shows a possible way how to deal with insecurities in the time schedule of a project plan. It shows that Program Evaluation and Review Technique (PERT), the most popular approach to handle this, bears some severe disadvantages. Furthermore it offers an alternative to overcome them by using Monte Carlo simulation. Finally it can be claimed that a complete change of paradigm is necessary: If you have any insecurities as inputs, everything becomes insecure. This might on the first sight convey the impression that the whole situation converts more complex, but we should rather accept this as the opportunity to apply all the well-known instruments from statistics.
On the Project risk baseline R3
Computers & Industrial Engineering, 2021
Obtaining a viable schedule baseline that meets all project constraints is one of the main issues for project managers. The literature on this topic focuses mainly on methods to obtain schedules that meet resource restrictions and, more recently, financial limitations. The methods provide different viable schedules for the same project, and the solutions with the shortest duration are considered the best-known schedule for that project. However, no tools currently select which schedule best performs in project risk terms. To bridge this gap, this paper aims to propose a method for selecting the project schedule with the highest probability of meeting the deadline of several alternative schedules with the same duration. To do so, we propose integrating aleatory uncertainty into project scheduling by quantifying the risk of several execution alternatives for the same project. The proposed method, tested with a wellknown repository for schedule benchmarking, can be applied to any project type to help managers to select the project schedules from several alternatives with the same duration, but the lowest risk.
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Construction projects are risky in both physical implementation and management. The characteristics of the risk reinforce the necessity of efficient management to increase the chances of success without commitment to its goals. This study explores the correlation of delay and the schedule performance index (SPI) to evaluate the risk of a construction project completed with time overruns. The hypothesis that the SPI of projects with a delay is distinct from those projects without a delay is assumed. A database with 19 elements was used to test this hypothesis and to calculate limit values to the SPI. Therefore, the risk of delay will be small when the observed SPI is greater than the superior limit and large when the SPI is below the inferior limit. The simplicity involved in the calculation of these values showed an advantage in comparison with other methods of risk evaluation. Another strong point observed is that any company can determine the value of risk by considering its own history and support decisions like doing corrective actions.
International Journal of Integrated Engineering, 2020
One of the problems faced by the contractors is an inappropriate scheduling method. For project scheduling, the contractor using Bar chart. Although this method still can be used, but in its application is limited to scheduling large-scale projects, because this method cannot describe the interdependence of activity. The problem can be solved using Program Evaluation and Review Technique (PERT) and Critical Path Method (CPM). PERT is a method that can be used to estimate the duration of activity and can calculate the probability of project time completion, while CPM is a scheduling method used to find the path of critical path and can describe the relationship between activities. Scheduling results using CPM found that the minimum duration to complete the project was 135 days with 20 activities on the critical path with 50% project probability. Further analysis using PERT found that for a greater probability of the project completion was 68% for 139.78 days duration, 95% for 144.56 days, and 99.7% for 149.34 days.
On the project risk baseline: Integrating aleatory uncertainty into project scheduling
Computers & Industrial Engineering, 2021
Obtaining a viable schedule baseline that meets all project constraints is one of the main issues for project managers. The literature on this topic focuses mainly on methods to obtain schedules that meet resource restrictions and, more recently, financial limitations. The methods provide different viable schedules for the same project, and the solutions with the shortest duration are considered the best-known schedule for that project. However, no tools currently select which schedule best performs in project risk terms. To bridge this gap, this paper aims to propose a method for selecting the project schedule with the highest probability of meeting the deadline of several alternative schedules with the same duration. To do so, we propose integrating aleatory uncertainty into project scheduling by quantifying the risk of several execution alternatives for the same project. The proposed method, tested with a well-known repository for schedule benchmarking, can be applied to any project type to help managers to select the project schedules from several alternatives with the same duration, but the lowest risk.
Schedule Risk Analysis Using Monte Carlo Simulation for Residential Projects
2019
Scheduling is an essential part of construction project management. Planning and scheduling of construction tasks help engineers to complete the project on time and within the budget. Most of the construction project failed to finish within planned duration; one of the reasons is regarded to estimated project duration without considering uncertainties that may cause a delay in performing specific activities. Hence it is vital to develop a risk management process which deals with the risks of execution that affects the project duration. This study focused on Schedule Risk Analysis Using Monte Carlo Simulation for Residential Projects, by taking the construction of a residential house as a case study. The primary objective of this study analyzes the output of a project schedule risk simulation when Monte Carlo use to simulate the duration of individual activities of the project and compare the total project duration outputs graphically and through statistical analysis. Consequently, using the Critical Path Method (CPM) to determine the project duration, which is equal to 96 days. For deciding the activity duration, the researcher has made a form. The form consists of all house tasks and estimated quantity with three columns for estimating Optimistic Duration, Most Likely Duration, and Pessimistic Duration in accordance with the respondent's perception for establishing the project duration by using the Program Evaluation and Review Techniques (PERT) method, which is equal 103 days. Project duration with low risk equal to 103 days, with base risks equal to 107 days and with high-risk project duration equal to 111 days. The outcomes clearly show that it is extremely unlikely to complete the project within 98 days and there is 100% chance that the project will be completed in 115 days. The sensitivity analysis for residential construction house indicates that the project schedule is most sensitive to the activity of "Wall Ceramic Tiles", which can influence the completion date because of the correlation coefficient of this activity reached to 0.39 and top-ranked of all other activities.
Probabilistic Completion Time in Project Scheduling
— There are two common used methods to find the minimum completion time for a project scheduling. These methods are Critical Path Method (CPM) and Program Evaluation Review Technique (PERT). In CPM, a network diagram, which is Activity on Node (AON), is drawn and the slack time for every activity is calculated such that the project's critical path could be found. It is important that the critical path can suggest the shortest possible completion time. On the other hand, PERT concerns on uncertainty and risk in a project. It has three time estimates, which are optimistic, pessimistic and most likely, and all the time estimates mentioned follows the beta distribution. Besides, the probability in completing the project within certain duration is calculated by using the standard normal distribution. As the risk cannot be avoided in a project, it is important to keep track on any changes and to minimize the completion time for a project. Both of the methods are used to calculate the shortest possible completion time, slack and critical path. The difference between these methods is CPM has only one determined time estimate, while PERT has three time estimates, which shows the uncertainty in the duration of an activity in a project. For illustration, the data used for the construction of a three-room house was studied. The results show that the minimum completion time for the project is 44 days with a success probability 0.91. In conclusion, CPM and PERT are practical tool in the project scheduling.
A Framework to Predict Time and Cost Risks based on Project Factors
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The occurrence and severity of risks are directly associated with the project factors, and in the case of determining a logical and significant correlation between project factors and risks, the final conditions of the project based on the initial and definite project factors can be predicted. In this research, a final list of 112 risks was prepared using the views of experts. Then, the risks’ weight was determined based on their impact on time and cost and according to the repetition of each risk in the earlier studies, as well as the use of 630industry experts using online web-based forms. Afterwards, 21 project factors that could affect the probability of occurrence and severity of risks related to time and cost were identified, and these factors were prioritized for each risk using the views of 25 experts. Then, applying the Pareto Principle, 14 project factors were identified. In all 4cases, including calculating the weight of risks in the technical literature as well as the ex...
Applied Sciences, 2020
Most construction managers use deterministic scheduling techniques to plan construction projects and estimate their duration. However, deterministic techniques are known to underestimate the project duration. Alternative methods, such as Stochastic Network Analysis, have rarely been adopted in practical contexts as they are commonly computer-intensive, require extensive historical information, have limited contextual/local validity and/or require skills most practitioners have not been trained for. In this paper, we propose some mathematical expressions to approximate the average and the standard deviation of a project duration from basic deterministic schedule information. The expressions' performance is successfully tested in a 4100-network dataset with varied activity durations and activity durations variability. Calculations are quite straightforward and can be implemented manually. Furthermore, unlike the Project Evaluation and Review Technique (PERT), they allow drawing inferences about the probability of project duration in the presence of several critical and subcritical paths with minimal additional calculation.
Comparison of Project Scheduling techniques: PERT versus Monte Carlo simulation
Industrial Engineering Journal, 2018
With an increase in the focus on achieving customer satisfaction, manufacturing industries are aiming to optimise their processes to a great extent. In any project the constraints of schedule, budget, scope and quality which form the basis of the project management triangle can be fulfilled by implementing project management planning tools & techniques appropriately. In this research study PERT (Program Evaluation and Review Technique) is applied on a project to evaluate the probability of project completion. Another scheduling tool which has gained popularity in recent times is the Monte Carlo simulation. This technique is applied on the same project to perform schedule risk analysis by evaluating the criticality index. The results of both the techniques are compared using hypothesis test to evaluate the more suitable one which can be used practically as a scheduling tool.