Prioritization of risk events in PPP wind power projects using integrated FMEA and Monte Carlo simulation

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Date

2021

Authors

Akçay, Emre Caner

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Open Access Color

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Civil Engineering
(2000)
The Atılım University Department of Civil Engineering was founded in 2000 as a pioneer for the Departments of Civil Engineering among the foundation schools of Ankara. It offers education in English. The Department of Civil Engineering has an academic staff qualified in all areas of the education offered. In addition to a high level of academic learning that benefits from learning opportunities through practice at its seven laboratories, the Department also offers a Cooperative Education program conducted in cooperation with renowned organizations in the construction sector. Accredited by MÜDEK (Association of Evaluation and Accreditation of Engineering Programs) (in 2018), our Department has been granted the longest period of accreditation to ever achieve through the association (six years). The accreditation is recognized by ENAEE (European Network for Accreditation of Engineering Education), and other international accreditation boards.

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The popularity of public private partnership (PPP) projects has grown all over the world, especially indeveloping countries. The success of PPP projects heavily depends on how effectively risk assessments areperformed. Failure Mode and Effects Analysis (FMEA) enables risk assessment by considering the impact,the probability, and the detection rate of risk events. However, it is very difficult to predict a single value forthese variables. The objective of this research is to integrate FMEA and Monte Carlo simulation, and to usethis model to perform risk assessment and prioritization of risks in PPP projects. The proposed model wasapplied to a real wind power generation investment located in the Aegean region of Turkey. The top threeimportant risk events are “unfavorable wind speed”, “fluctuation in exchange rates”, and “interest ratevolatility”. The model perfumed to the satisfaction of experts. The primary contributions of this researchinclude (1) a method that allows the identification of the risk events in PPP projects; (2) a model that performsrisk assessment and prioritization of risk events in PPP projects; (3) an integrated FMEA and Monte Carlosimulation model that performs stochastic risk assessment in PPP projects. Both public agencies and privateconsortia should benefit from the proposed model.

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Source

Journal of Construction Engineering, Management & Innovation (Online)

Volume

4

Issue

2

Start Page

80

End Page

91

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