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APRT-FMEA buffer sizing method in scheduling of a wind farm construction project

Author(s):

Medium: journal article
Language(s): English
Published in: Engineering, Construction and Architectural Management, , n. 6, v. 26
Page(s): 1129-1150
DOI: 10.1108/ecam-04-2018-0161
Abstract:

Purpose

The purpose of this paper is to present an efficient model for project buffer sizing by taking failure mode and effects analysis (FMEA) into account to reach a more realistic schedule.

Design/methodology/approach

In the first phase of the project, several turbines were installed according to the primary schedule with an average duration of 142 days. Then, some of critical chain project management algorithms were separately applied in the implementation and installation of the other wind turbines. The adaptive procedure with resource tightness (APRT) method turned out to be the best method in terms of obtaining a more realistic schedule in this case study. Finally, FMEA was simultaneously applied with APRT.

Findings

Applying the hybrid method to the scheduling of the wind turbines, yielded the more realistic schedule than traditional.

Research limitations/implications

The proposed hybrid APRT-FMEA algorithm was implemented on a real wind farm construction project which was completed with 37 percent shorter duration than the initial estimation; in spite of the initial estimation of 142 days, the project completed in 103 days.

Practical implications

Introducing and implementing a new algorithm which is a combination of buffer sizing algorithms and one of the well-known and mostly used risk assessment methods in order to provide the more realistic project schedule in the construction of wind turbines.

Originality/value

Introducing and implementing a novel algorithm which is a combination of conventional buffer sizing method and one of the efficient risk assessment methods in order to make the schedule more realistic.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1108/ecam-04-2018-0161.
  • About this
    data sheet
  • Reference-ID
    10576754
  • Published on:
    26/02/2021
  • Last updated on:
    26/02/2021