Prescriptive Maintenance: Building Alternative Plans for Smart Operations

Henrique Marques
AerologLab-ITA, Aeronautics Institute of Technology, São José dos Campos, São Paulo, Brazil

Alessandro Giacotto
AerologLab-ITA, Aeronautics Institute of Technology, São José dos Campos, São Paulo, Brazil

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp19162027

Ingår i: FT2019. Proceedings of the 10th Aerospace Technology Congress, October 8-9, 2019, Stockholm, Sweden

Linköping Electronic Conference Proceedings 162:27, s. 231-236

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Publicerad: 2019-10-23

ISBN: 978-91-7519-006-8

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


Smart operations require the ability to generate alternative plans whenever a change in operations occurs in an unplanned manner. Alternate maintenance plans, in a highly dynamic context such as airline operations, require the ability to foresee small developments in terms of labor allocation, repairable items and downtime, when and where they were not previously scheduled. In addition to being able to cause the disruption of the air transport network and consequent financial losses, it causes loss of trust in the company brand. Prescriptive maintenance is a potential technological response when using Artificial Intelligence to suggest alternative plans in a timely manner so that decision makers can reduce the impact on air operations. This paper proposes a framework for the construction of an integrated prescriptive maintenance solution that is certifiable by using auditable methods and extensible to complex systems of other industries. The adoption of prescriptive maintenance not only enhances the use of health management systems, widely available in modern aircraft fleets that have the potential to predict the remaining useful life of items of interest, but also allows identifying more than one response alternative to conflicts of interest in the conduction of the smart operations of air transport companies.


prescriptive maintenance, artificial intelligence, e-maintenance, smart operations, information fusion, diagnosis, prognosis


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