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Further Investigations for Documents Information Retrieval Based on DWT Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Prediction of Medical Equipment Failure Rate: A Case Study

Authors : Rasha S. Aboul-Yazeed, Ahmed El-Bialy, Abdalla S. A. Mohamed

Published in: Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016

Publisher: Springer International Publishing

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Abstract

Medical equipment is one of the important inputs required for the provision of efficient healthcare services. Following maintenance programs will make the equipment last longer, work more efficiently and reduces the likelihood of equipment failure during critical processing operations. Prediction of these failures affects the efficiency and enlarges the uptime of medical equipment, minimizes sudden failures and even can prevent it. Therefore, time series analysis using autoregressive model (AR) has been used to analyze failure rate data. AR model uses the past behavior of the system output to predict its behavior in the future. The mean squared error (MSE) between model output and real-life data was less than 0.1 %. Moreover, it succeeded to predict duration of next failures.

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Metadata
Title
Prediction of Medical Equipment Failure Rate: A Case Study
Authors
Rasha S. Aboul-Yazeed
Ahmed El-Bialy
Abdalla S. A. Mohamed
Copyright Year
2017
Book
Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016

Print ISBN: 978-3-319-48307-8

Electronic ISBN: 978-3-319-48308-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-48308-5_62

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