MITIGASI RISIKO KETERLAMBATAN PROYEK PERBAIKAN TANGKI MINYAK MENTAH DI DURI DENGAN SIMULASI MONTE CARLO

2019 ◽  
Vol 17 (2) ◽  
pp. 49
Author(s):  
Arvin Arvin ◽  
Ari Sandhyavitri ◽  
Muhammad Ikhsan
Keyword(s):  
Monte Carlo ◽  
Critical Path

Pekerjaan pada jalur kritis (critical path) berpotensi terjadinya keterlambatan penyelesaian proyek. Pekerjaan kritis mempunyai risiko dominan dan berpengaruh pada pekerjaan berikutnya jika terlambat memulai dan menyelesaikan pekerjaan tersebut. Proyek perbaikan tangki memiliki serangkaian pekerjaan critical path yang berisiko tinggi. Perlunya daftar risiko yang teridentifikasi pada perencanaan skedul sebuah proyek, membantu manajemen proyek dalam meminimalisir keterlambatan waktu pekerjaan sebuah proyek. Tujuan penelitian ini adalah untuk mengidentifikasi, menganalisis dan melakukan mitigasi terhadap faktor risiko keterlambatan pada proyek perbaikan tangki minyak yang berlokasi di Duri Kabupaten Bengkalis.  Dari hasil identifikasi terdapat 29 faktor risiko yang menyebabkan keterlambatan proyek. Setelah dilakukan pengelompokan level risiko, teridentifikasi 8 faktor risiko dengan kategori level tinggi dan dominan yang sangat mempengaruhi dan berdampak secara signifikan terhadap keterlambatan proyek diantaranya faktor keselamatan kerja pada saat konstruksi, kekurangan sumber daya manusia yang berpengalaman, banyaknya pekerjaan critical path, pengalaman kontraktor, ketersediaan peralatan konstruksi yang terbatas, proses memperoleh izin kerja harian yang terkendala, kurangnya pengawas yang berkualitas, dan kurangnya koordinasi antar tim yang terlibat. Berdasarkan faktor-faktor risiko diatas, proyek telah mengalami keterlambatan selama 257 hari kerja. Setelah dilakukan mitigasi risiko, dengan asumsi nilai besaran risiko berkurang hingga 25%, dengan simulasi monte carlo untuk mengestimasi total waktu penyelesaian proyek dengan program @Risk for Excel diperoleh hasil bahwa proyek mengalami percepatan waktu sebesar 17,34%. Simulasi monte carlo dengan program @Risk mampu mengestimasi total durasi pelaksanaan proyek untuk memperoleh hasil yang mendekati akurat.

Risk Management of Construction Schedule by PERT with Monte Carlo Simulation

2014 ◽  
Vol 548-549 ◽  
pp. 1646-1650 ◽  
Author(s):  
Yang Liu ◽  
Yan Li
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Critical Path ◽  
Total Duration ◽  
Control Points ◽  
Schedule Management ◽  
Simulation Results ◽  
Critical Paths ◽  
Construction Schedule

It has been proved that the construction schedule management was an uncertain problem. Traditional CPM method was a good way to define the total duration and critical paths but can not solve uncertainty. The paper use CPM to define the duration and critical path firstly, then defined the parameters with Delphi and make Monte Carlo simulation. Through simulation results, it is found that the probability to finish the work on time was only 35.3%. The following step is to make sensitivity analysis, through the calculation, the work which has large influence was found and treat as key control points. It is proved that Monte Carlo simulation is useful to solve the problem of construction schedule management.

scholarly journals Dynamic Cooperative Model for Ranking Construction Risks using Monte Carlo Simulation

2020 ◽  
Vol 9 (12) ◽  
pp. 211-216
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Construction Projects ◽  
Critical Path ◽  
Quantitative Model ◽  
Decision Makers ◽  
Path Model ◽  
Simulation Engine ◽  
Construction Risks ◽  
Risk Planning

Construction projects suffer from diverse uncertainties that hinder the key objectives’ achievement. These uncertainties represent risks that may appear through the project life cycle. This paper introduces a quantitative model to estimate and rank risks dynamically during the risk planning phase. Such ranking would help decision-makers appropriately respond to and/or control construction risks. The model provides proper risk contingency reserves for both project time and cost that meet decision-makers' selected confidence levels using Monte Carlo Simulation (MCS). In order to quantify the project uncertainty, severities of residual risks are determined and allocated at the project's activities-level using a planning/scheduling spreadsheet model and a MCS tool suitable for spreadsheets. The model is able to calculate the contribution of each risk from the determined contingency at both the project level for both the time and cost at the decision-maker confidence level.The model represents a direct implementation for a Risk Planning Contingency Model (RPCM); which involves four modules as follows: (1) Risk Register (RR), (2) Risk Allocator (RA), (3) Risk Simulator (RS), and (4) Contingency Calculator (CC). These modules are hosted in a critical path model scheduling spreadsheet to facilitate risk management. In addition, a simulation engine add-in is used for analyzing the probability distribution for the project time and cost outcomes. In order to verify the proposed model, the process and analysis have been applied to a case study project. The results show that the RPCM is capable to rank and estimate the residual risks in an easy, fast, and effective way.

scholarly journals PSM: A New Approach to Probabilistic Scheduling

2021 ◽  
Author(s):  
Benyamin Tedjakusuma
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Critical Path ◽  
Project Schedule ◽  
Microsoft Excel ◽  
New Approach ◽  
Probabilistic Scheduling ◽  
Scheduling Method ◽  
Duration Estimation ◽  
Ongoing Project

A new scheduling method, where probability values can be assigned to activity durations, is proposed in this thesis. Probabilistic Scheduling Method (PSM) accepts activity durations tagged with probability or confidence intervals. Tests were carried out using examples of 3,7, and 9 activities to evaluate PSM's practical capability. The comparisons of PSM to Critical Path Method (CPM), Performance Evaluation and Review Technique (PERT), and Monte Carlo application to PERT (MC PERT) conclude that PSM results in similar most probable duration estimation. Further tests were implemented to evaluate PSM's capability to project schedule revision on an ongoing project. A microsoft Excel application was used to organize tests data and calculations. PSM computations are more industry friendly. They allow for a range of duration associated with a range of probabilites. PSM provides flexibility and simplicity, and also dependency information that will benefit its user in decision making

Study on Application of Monte Carlo Simulation in Construction Schedule Management

2013 ◽  
Vol 859 ◽  
pp. 284-288
Author(s):  
Yang Liu ◽  
Yan Li
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Critical Path ◽  
Total Duration ◽  
Control Points ◽  
Schedule Management ◽  
Simulation Results ◽  
Critical Paths ◽  
Construction Schedule

It has been proved that the construction schedule management was an uncertain problem. Traditional CPM method was a good way to define the total duration and critical paths but can not solve uncertainty. The paper use CPM to define the duration and critical path firstly, then defined the parameters with Delphi and make Monte Carlo simulation. Through simulation results, it is found that the probability to finish the work on time was only 68%. The following step is to make sensitivity analysis, through the calculation, the work which has large influence was found and treat as key control points. It is proved that Monte Carlo simulation is useful to solve the problem of construction schedule management.

scholarly journals PSM: A New Approach to Probabilistic Scheduling

2021 ◽  
Author(s):  
Benyamin Tedjakusuma
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Critical Path ◽  
Project Schedule ◽  
Microsoft Excel ◽  
New Approach ◽  
Probabilistic Scheduling ◽  
Scheduling Method ◽  
Duration Estimation ◽  
Ongoing Project

A new scheduling method, where probability values can be assigned to activity durations, is proposed in this thesis. Probabilistic Scheduling Method (PSM) accepts activity durations tagged with probability or confidence intervals. Tests were carried out using examples of 3,7, and 9 activities to evaluate PSM's practical capability. The comparisons of PSM to Critical Path Method (CPM), Performance Evaluation and Review Technique (PERT), and Monte Carlo application to PERT (MC PERT) conclude that PSM results in similar most probable duration estimation. Further tests were implemented to evaluate PSM's capability to project schedule revision on an ongoing project. A microsoft Excel application was used to organize tests data and calculations. PSM computations are more industry friendly. They allow for a range of duration associated with a range of probabilites. PSM provides flexibility and simplicity, and also dependency information that will benefit its user in decision making

scholarly journals Comparative Analysis of Risk Reduction Using PERT/CPM Techniques

2019 ◽  
pp. 144-147
Author(s):  
Suchi Pandey ◽  
Hira Singh Yadav
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Program Evaluation ◽  
Comparative Analysis ◽  
Risk Reduction ◽  
Critical Path ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Analysis Method ◽  
The Cost

This paper analyzed the traditional probability analysis method for duration risk in program evaluation and review technique (PERT) and Critical Path Method (CPM). On the basis of that it simulates the project’s duration and analyzes the risk by Monte Carlo simulation method. The PERT/CPM produce begins with the hard work of developing an estimate of the cost each activity when it is performed in the planning way (including any crashing).

Scheduling Aircraft Ground Handling Operations Under Uncertainty Using Critical Path Analysis and Monte Carlo Simulation

2020 ◽  
Vol 1 (1) ◽  
pp. 37-45
Author(s):  
Kaveh Sheibani
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Path Analysis ◽  
Critical Path ◽  
Weather Conditions ◽  
Turnaround Time ◽  
Accurate Estimate ◽  
Critical Path Analysis ◽  
Short Period ◽  
Ground Handling

Aircraft ground handling is an integral part of airline operations. Although ground handling operations usually are straightforward, it could be very complicated in certain situations, such as troubling cargo loading and unloading incidents, weather conditions or improper use of equipment and breakdowns. Ground handlers need to orchestrate a number of activities within a confined area around airplane in a short period of time. Punctuality is important for airlines and resulting increased efficiencies. In this article, scheduling aircraft ground handling operations with uncertain durations using the critical path analysis, the Monte Carlo simulation is considered with the aim of improving aircraft ground services during the turnaround. Having an accurate estimate of aircraft turnaround time considering its type and load, the recourses would be assigned to the ground operations more efficiently. A case study of a long-range wide-body twin-engine jet aircraft is discussed in detail. The results indicate that the proposed method gives improved scheduling relative to the routines observed at a hub airport.

Outbursts of comet Schwassmann-Wachmann 1, and the cloud of interplanetary boulders

1974 ◽  
Vol 22 ◽  
pp. 307 ◽  
Author(s):  
Zdenek Sekanina
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Interplanetary Space ◽  
Porous Matrix ◽  
Maximum Diameter ◽  
Expansion Velocity ◽  
Solid Constituent ◽  
Meteoric Material ◽  
Periodic Comet

AbstractIt is suggested that the outbursts of Periodic Comet Schwassmann-Wachmann 1 are triggered by impacts of interplanetary boulders on the surface of the comet’s nucleus. The existence of a cloud of such boulders in interplanetary space was predicted by Harwit (1967). We have used the hypothesis to calculate the characteristics of the outbursts – such as their mean rate, optically important dimensions of ejected debris, expansion velocity of the ejecta, maximum diameter of the expanding cloud before it fades out, and the magnitude of the accompanying orbital impulse – and found them reasonably consistent with observations, if the solid constituent of the comet is assumed in the form of a porous matrix of lowstrength meteoric material. A Monte Carlo method was applied to simulate the distributions of impacts, their directions and impact velocities.

Monte Carlo Algorithms for Moments of Transition Arrays

1988 ◽  
Vol 102 ◽  
pp. 79-81
Author(s):  
A. Goldberg ◽  
S.D. Bloom
Keyword(s):  
Monte Carlo ◽  
State Vector ◽  
Basis Vector ◽  
Collective State ◽  
Dispersion Characteristics ◽  
Dipole Strength ◽  
The Third ◽  
Monte Carlo Algorithms ◽  
Third Moment ◽  
Very High

AbstractClosed expressions for the first, second, and (in some cases) the third moment of atomic transition arrays now exist. Recently a method has been developed for getting to very high moments (up to the 12th and beyond) in cases where a “collective” state-vector (i.e. a state-vector containing the entire electric dipole strength) can be created from each eigenstate in the parent configuration. Both of these approaches give exact results. Herein we describe astatistical(or Monte Carlo) approach which requires onlyonerepresentative state-vector |RV> for the entire parent manifold to get estimates of transition moments of high order. The representation is achieved through the random amplitudes associated with each basis vector making up |RV>. This also gives rise to the dispersion characterizing the method, which has been applied to a system (in the M shell) with≈250,000 lines where we have calculated up to the 5th moment. It turns out that the dispersion in the moments decreases with the size of the manifold, making its application to very big systems statistically advantageous. A discussion of the method and these dispersion characteristics will be presented.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

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