A carregar...
Publicação
Maintenance Management
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 618.38 KB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Maintenance management is defined as "all management activities that determine the maintenance requirements, objectives, strategies and responsibilities, and implementation of them by such means as maintenance planning, maintenance control, and improvement of maintenance activities and economics". The purpose of this research work is to present a brief review on key problems in maintenance management and on selected solutions to address these problems, particularly within aviation maintenance, framed within business analytics (BA), which comprises descriptive, predictive, and prescriptive perspectives. Unlike manufacturing, in which most activities are deterministic by nature, characterized by well-defined execution lead times and required resources, being it labor, tools, or parts and materials, maintenance presents an important stochastic component. Maintenance can be divided into preventive maintenance and corrective maintenance. The former refers to prespecified tasks, carried out at predetermined intervals, being its work essentially deterministic. The latter results from the probabilistic nature of failures, performed upon a fault is identified, being its work inherently stochastic. The workload resulting from corrective maintenance can be more than half of the total maintenance workload according to some studies, making it an important challenge for effective and efficient maintenance management. This research work is expected to be of interest for researchers and practitioners alike, by identifying the sources of uncertainty associated with maintenance management and by providing references on relevant methods to model and control such uncertainty.
Descrição
Funding Information:
Duarte Dinis acknowledges the Portuguese Fundação para a Ciência e a Tecnologia (FCT) for its financial support via the project UIDB/00667/2020 and UIDP/00667/2020 (UNIDEMI). This work is also financed by Portuguese funds through FCT, under the project UIDB/00097/2020 (CEGIST).
Palavras-chave
Maintenance management Capacity planning Spare parts management Scheduling Business analytics