An Univariable Approach for Forecasting Workload in the Maintenance Industry

Authors

  • Paulo Silva Technological University Dublin
  • Fernando Perez Tellez Technological University Dublin
  • John Cardiff Technological University Dublin

DOI:

https://doi.org/10.13053/cys-24-2-3399

Keywords:

Time series, machine learning, forecast, workload

Abstract

The forecasting of the workload in the maintenance industry is of great value to improve human resources allocation and reduce overwork. In this paper, we discuss the problem and the challenges it pertains. We analyze data from a company operating in the industry and present the results of several forecasting models.

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Published

2020-06-23

Issue

Vol. 24 No. 2 (2020): Thematic Issue on Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez)

Section

Articles of the Thematic Issue

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