Title: Enhancing reliability/availability in asset management with retrofitting: a wind turbine case study

Authors: Suna Cinar; Ferenc Szidarovszky; Mehmet Bayram Yildirim

Addresses: Department of Industrial, System and Manufacturing Engineering, Wichita State University, 1845 Fairmount Street, Box 35, Wichita, KS 67260-0035, USA ' Department of Mathematics, Corvinus University, Budapest, Fövam ter 8 H-1093, Hungary ' Department of Industrial, System and Manufacturing Engineering, Wichita State University, 1845 Fairmount Street, Box 35, Wichita, KS 67260-0035, USA

Abstract: In this study, a mixed-integer linear programming (MILP) modelling approach is proposed to identify the optimum maintenance or retrofitting schedule under budget and energy production constraint(s) by improving failure rate of assets. The proposed reliability/availability asset management with retrofitting (RAAMWR) model seeks to maximise the total net profit subject to achieving a target reliability/availability value and minimise the total improvement cost subject to a budgetary constraint. We apply our model to a case study involving wind turbines (WTs). The results of this study show that to reach the target reliability value with improved failure rate data, model selects retrofitting due to lower loss time and high energy production rate of retrofitting options. This optimal retrofitting choice is not only due to low loss time, but also improving the existing failure rate of an asset to reach the target reliability. In addition, the effects of key parameters on total cost, such as operation and maintenance (O&M) cost, retrofitting cost, budget allocated for retrofitting, and different target reliability values on the optimal improvement policy were considered.

Keywords: mixed-integer linear programming; MILP; wind turbine; reliability; asset management; availability; retrofitting; optimisation.

DOI: 10.1504/IJOR.2021.119410

International Journal of Operational Research, 2021 Vol.42 No.3, pp.400 - 421

Received: 25 May 2018
Accepted: 26 May 2019
Published online: 03 Dec 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article