Multiple Regressi on for the Forecast of Spare Parts for Medical Equipment

Zoila Esther Morales Tabares, Efren Vazquez Silva, Yailé Caballero Mota

Research output: Contribution to journalArticle


The constant search for efficiency in the provision of hospital services confronts the health sector with greater challenges in terms of managing the maintenance of medical equipment. Forecasting the demand for spare parts is a complex process due to their intermittent behaviour. As part of this process, the PREDSTOCK algorithm is proposed in this manuscript to predict the stock of spare parts for medical equipment using Multiple Regression as a quantitative estimation technique.
Translated title of the contributionRegresión Múltiple para el Pronóstico de Repuestos para Equipos Médicos
Original languageEnglish (US)
Pages (from-to)1-5
Number of pages5
JournalInternational Journal of Current Research
Issue number11
StatePublished - 30 Dec 2019


  • Forecast
  • Maintenance management
  • Medical equipment
  • Spare parts

CACES Knowledge Areas

  • 727A Industrial and process design


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