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After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

Author

Listed:
  • Asier Erguido
  • Adolfo Crespo
  • Eduardo Castellano
  • Jose Luis Flores

Abstract

After-sales maintenance services can be a very profitable source of income for original equipment manufacturers (OEMs) due to the increasing interest of assets’ users on performance-based contracts. However, when it concerns the product value-adding process, OEMs have traditionally been more focused on improving their production processes, rather than on complementing their products by offering after-sales services, consequently leading to difficulties in offering them efficiently. Furthermore, due to both the high uncertainty of the assets’ behaviour and the inherent challenges of managing the maintenance process (e.g. maintenance strategy to be followed or resources to be deployed), it is complex to make business out of the supply of after-sales services. Aiming at helping the business and maintenance decision-makers at this point, this paper proposes a framework for optimising the income of after-sales maintenance services through: (a) implementing advanced multi-objective opportunistic maintenance strategies that systematically consider the assets’ operational context in order to perform preventive maintenance during the most favourable conditions, (b) considering the specific OEMs’ and users’ needs and (c) assessing both endogenous and exogenous uncertainties that might condition the after-sales services’ profitability. The developed case study for the wind energy sector demonstrates the suitability of the presented framework for optimising the after-sales services.

Suggested Citation

  • Asier Erguido & Adolfo Crespo & Eduardo Castellano & Jose Luis Flores, 2018. "After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study," Journal of Risk and Reliability, , vol. 232(4), pages 352-367, August.
  • Handle: RePEc:sae:risrel:v:232:y:2018:i:4:p:352-367
    DOI: 10.1177/1748006X17753500
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