project planning & control - nptel.ac.in 3. uncertai… · project planning & control...
TRANSCRIPT
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Koshy Varghese, Ph.D.Professor
Building Technology & Construction Management
Department of Civil Engineering
I.I.T. Madras
Project Planning & Control
Lesson 3
Uncertainty in Project Schedules
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Lecture Outline
• Uncertainty in Project Schedules
• PERT Background & Assumptions
• PERT – Stepwise Procedure
• PERT Examples
• Summary
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Prerequisite Knowledge
• You should be familiar with reading standard normal distribution (given m & s ) to:
• (i) Find probability (area under the curve) for a given value (x).
• (ii) Find value given a probability.
https://www.youtube.com/watch?v=_86q-hn_3DQhttp://nptel.ac.in/courses/105103027/1https://www.youtube.com/watch?v=mai23vW8uFM
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Uncertainty in Projects
• CPM does not directly model uncertainty- No probability based query can be modeled in CPM.
• Uncertainty is an inherent characteristic of all projects.– Duration uncertainty, Cost uncertainty, Quality
uncertainty, Resource uncertainty, etc……
• Construction projects have a relatively lower level of uncertainty compared to research/defense/space projects.
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Uncertainty in Projects
• Uncertainty in construction can be addressed through risk analysis and management
• Modeling & managing duration uncertainty & risk is an important part of project planning and control
• PERT was developed to address the needs of projects which are being done for the first time – challenge to estimate activity duration.
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Activity Duration Estimating
6.4.2 Tools & Techniques
–Expert Judgment (Heuristic)
–Analogous Estimating (Data + Heuristic)
–Parametric estimating
–Three Point Estimate (Uncertainty)
–Reserve analysis (Buffer)
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Probabilistic Duration• Probabilistic duration distribution is used to account
for the uncertainty in activity duration estimation.
• The duration of a particular activity is assumed to be a stochastic variable that follows a certain distribution as shown in the figure below
Expert OpinionHistorical Data
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Probabilistic Duration(Historical Data)
• Consider duration data which was collected for a activity.
Duration(days) 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Occurances 1 1 5 10 8 7 5 4 3 3 2 2 2 1 1 1 1 1
Mean = 8.17 daysMode = 5 daysMedian = 7 days
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Frequency Distribution
Probabilistic Duration(Historical Data)
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Probabilistic Duration(Historical Data)
Probability Distribution
Cumulative Probability
Probability Distribution
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Probabilistic Duration(Historical Data)
Beta Type DistributionIs found to be best for
Const. Duration
Distribution Fitting
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Probabilistic Duration(Expert Estimate)
Beta Type Distribution
Expert – 3 time estimates
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B
4d5 9
7 11
D
3d11 14
11 14
C
6d5 11
5 11
A
5d0 5
0 5
Deterministic Duration(Historical data or Computations)
B
? ?
? ?
D
? ?
? ?
C
? ?
? ?
A
0 ?
0
Probabilistic Duration(Historical or Expert Data)
SIMULATION OR
PERTCPM
?
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SIMULATION
Run-1
Run-2
Run-3
Run-4
Run-5
Run-6
Run-7
Run-8
Run-9
Run-10
Run-11
Run-12
Run-N-3
Run-N-2
Run-N-1
Run-N
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Historical Data & Simulation - Issues
• Not easily available
• Even when available – is it data appropriate for current activity/project ?
• Simulation approach is computing intensive –1950’s mainframe had limitations
• Simulation is popular approach today!