Total cost optimization of submersible irrigation pump maintenance using simulation

Abstract

Purpose

The unpredictable failure of submersible pump (SP) in groundwater irrigation systems has considerable negative economic consequences. The purpose of this paper is to develop a total cost minimization model that aims to optimize maintenance actions for SP. It reports on simulation-based stochastic scenario analysis for evaluating total cost of maintenance.

Design/methodology/approach

Stochastic simulation modeling has been performed for failure of pump motor and corresponding maintenance. Five alternative scenarios were compared for total cost over 15 years starting with empirical data from a northern Ethiopian site. Downtime probabilities and spare part supply uncertainty have been considered in the mathematical model. The model is also validated using multiple ways.

Findings

The scenario comparisons indicate that despite the challenges of accessing SP doing one motor rewinding for each purchased pump system upon failure (preferably with shorter supply lead time and variability) seems to result in lowest overall costs for the time horizon considered.

Practical implications

The model should help to make informed practical decision regarding planning and management of SP failure systems in a developing economy context. This should, therefore, lead to better revenue for smallholder farmers and improved food security in similar context.

Originality/value

There are limited number of publications that consider the life cycle costs with stochastic analysis when it comes to maintenance of SPs. To the best of the authors’ knowledge, no paper has previously directly addressed maintenance cost optimization for SP in irrigation. The study could be used to develop more sophisticated stochastic models with more efficient algorithms and consideration of additional sources of stochasticity for such system.

Citation

Hatsey, N.H. and Birkie, S.E. (2021), "Total cost optimization of submersible irrigation pump maintenance using simulation", Journal of Quality in Maintenance Engineering, Vol. 27 No. 1, pp. 187-202. https://doi.org/10.1108/JQME-08-2018-0064