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Subsea maintenance service delivery: A multi-variable analysis model for predicting potential delays in scheduled services

Efosa E. Uyiomendo (Department of Asset Maintenance, University of Stavanger, Stavanger, Norway)
Markeset Tore (Department of Mechanical Engineering (Operations and Maintenance), University of Stavanger, Stavanger, Norway)

Journal of Quality in Maintenance Engineering

ISSN: 1355-2511

Article publication date: 9 March 2015

Abstract

Purpose

The purpose of this paper is to propose a multi-variable analysis (MVA) model for predicting potential delays in the delivery of subsea inspection, maintenance and repair (IMR) services.

Design/methodology/approach

Based on data from 351 subsea IMR service jobs executed between 2006 and 2008, a MVA model is proposed for predicting the potential delays in the delivery of IMR services in different plausible scenarios.

Findings

A model for predicting the delays in IMR service delivery, based on four practical variables that are readily available during the planning phase, was developed and tested. The factors contributing to delays in petroleum subsea IMR services based on importance are: water depth, weather, job complexity, job uncertainty as well as job complexity mix.

Research limitations/implications

The MVA model is developed based on analyzing subsea IMR service jobs performed in the petroleum industry from 2006-2008. The model can be used in the planning stage to predict potential delays in service delivery based on practical variables available.

Originality/value

The research proposes a MVA model for predicting delays in service delivery. The model is useful for predicting potential delays in service delivery and for improving the plan based on model analysis results.

Keywords

Citation

Uyiomendo, E.E. and Tore, M. (2015), "Subsea maintenance service delivery: A multi-variable analysis model for predicting potential delays in scheduled services", Journal of Quality in Maintenance Engineering, Vol. 21 No. 1, pp. 34-54. https://doi.org/10.1108/JQME-11-2013-0071

Publisher

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Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited