Stochastic analyses for managing risk of delay in Duri oil construction projects, Indonesia

Sandhyavitri, Ari

doi:10.1080/15623599.2019.1644762

Cited by 6 publications

(6 citation statements)

References 18 publications

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“…Comparison of the results of the study with the previous research indicated that the owner's financial problems were found to be the most critical causes of delay in the oil and gas construction industry of the countries such as Iran and India (Fallahnejad, 2013;Prasad et al, 2019). As stated by Zakeri et al (1996) and Sandhyavitri (2019), changes in design and specifications are one of the significant causes of delays in oil construction projects in Iran and Indonesia. Moreover, our findings are supported by prior research conducted by Zakeri et al (1996) and Ravand and Salai (2011) that low efficiency of equipment and low productivity of labor are critical delay factors in construction projects in Iran.…”

Section: Discussionmentioning

confidence: 97%

Identifying and prioritizing delay factors in Iran’s oil construction projects

Kazemi

Kim

Kazemi

2020

IJESM

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Purpose Successful implementation of construction projects is one of the crucial factors for the economic development of every country. The main part of the countries’ capital is allocated to civil and infrastructure projects annually, most of which are accomplished with delay. Construction projects are often criticized for overrunning time and budgets. Analyzing the factors causing delay is essential for omitting them and timely implementation of these projects. Due to the importance of oil projects, this study aims to investigate and analyze the factors causing a delay in Iran’s oil construction projects. Design/methodology/approach In this research, after a broad literature review, using the fuzzy Delphi method, a total of 75 delay factors were identified under 11 major categories of owner, contractor, consultant, equipment, labor, materials, design, contract and contractual relations, laws and regulations, environmental factors, and managerial factors. Then, by using the best-worst method, the factors were prioritized. Findings The results showed that sanction, governmental management systems, weak project management by the contractor, technical and managerial weaknesses of the consultant, financial problems and delay in payment by the owner, low efficiency of the equipment, low productivity of the workforce, changes in laws and regulations, inappropriate organizational structure linking to the project, changes in the design, and changes in the price of materials are the most crucial factors causing a delay in Iran’s oil construction projects. Research limitations/implications These findings are expected to have significant contributions to Iran’s oil construction industry in controlling the time overruns in construction contracts. Originality/value The main contribution of this study is to develop a comprehensive framework in which, causes of delay in Iran’s oil construction projects are addressed and prioritized.

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Section: Discussionmentioning

confidence: 97%

Identifying and prioritizing delay factors in Iran’s oil construction projects

Kazemi

Kim

Kazemi

2020

IJESM

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“…Based on the literature review, it was identi ed that there were approximately 30 to 49 risk factors inherent in the type of oil project [6,7,27].…”

Section: Applied Materials and Technologymentioning

confidence: 99%

“…Over the years, various risk factors of project delays in the construction industry have been reviewed from many articles such as [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…e simulation of stochastic models was developed for estimating and predicting a range of output values under certain operational conditions suited to industrial purposes under uncertainty [7,9]. ese article objectives were to; (i) identify risk factors causing project delay, (ii) establish a list of risk indexes, and (iii) simulate the risks using Monte Carlo simulations as well as the sensitivity risks.…”

Section: Introductionmentioning

confidence: 99%

“…Risk Frequency and Impact en, risk assessments were performed to classify risk according to their index. e risk index was classi ed into three simple main categories [7,11] as follow:  e low-risk category was calculated as a very low to low relative risk importance index. e low risk is considered insigni cant to cause project delay.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simulations of the Crude Oil Tank Refurbishment Project Risks Using Monte Carlo

Sandhyavitri

Arvin²,

Restuhadi³

2022

J. Appl. Mat. Tech.

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Simulation technology has assisted project stakeholders in predicting a range of the project results in the future under risks and uncertainties. The objectives of this article are to improve a comprehensive project planning in the perspective of the project scheduling by conducting simulations for the refurbishment of crude oil tank project risks using Monte Carlo simulations. The practical approaches for simulating the risks encompassed 3 stages: risk identification, assessment, and risk analysis using the Monte Carlo simulations. The implementation of Monte Carlo simulation in the form of stochastic approach however were not new, but the application of these approaches in the area of oil industrial projects was challenging. A Free Water Knock-Out (FWKO) tank project located in Duri, Indonesia was taken as a case study. The initial FWKO project duration was set up to be 180 working days, and it was delayed (up to 140% from the initial duration of the project planning). This study conducted deep questioner surveys from 25 oil industry stakeholders. It was identified 29 risk factors have been considered as the major causes of the project delay. The risk factors were then calculated qualitatively for performing risk indexes. Based on the risk simulations (after 1000 iterations) using Monte Carlo simulations utilizing @risk application package (under uncertainties) there was found that the possibility of this project would experience delays at the range of 47 days (126%) to 80 days (144%) from the initial project planning. This simulation had also identified the most sensitive activities causing project delays. The results was presented in the form of the spider graph diagram which assisted the project main stakeholders in developing a strategic decision during project planning phase.

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