An Univariable Approach for Forecasting Workload in the Maintenance Industry

Paulo Silva, Fernando Perez Tellez, John Cardiff

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.

Keywords


Time series, machine learning, forecast, workload

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