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An Enhanced Delay Time Model to Support Evidence Based Maintenance in Healthcare Domain

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Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016 (AECIA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 565))

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Abstract

The concern for patient safety and regulatory requirements classically based on manufacturers’ recommendations discouraged evidence based maintenance, and thus limited the possibility of maintenance optimization within healthcare organization. Although, the need for preventive maintenance and its appropriate frequency have been debated extensively for decades, very few studies have been conducted to revise healthcare maintenance strategy and improve the effectiveness of clinical engineers work, as well as focus on tasks that could provide the highest return for their limited resources. In this paper, the shift from a compliance-based to a goal-based approach is well established in an improved proportional delay time framework taking into account hidden nature of failures, the influence of the utilization rate and maintenance effectiveness on medical devices degradation. To illustrate the model capabilities, a real case study from the healthcare domain is presented, the model parameters are estimated entirely using the collected maintenance data. Then, the optimal maintenance policy is determined by a multi-objective optimization to achieve the desired cost effectiveness.

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Author information

Authors and Affiliations

  1. Mechanical Engineering Laboratory, Faculty of Sciences and Techniques, Sidi Mohammed Ben Abdellah University, 2202, Fes, Morocco

    Hassana Mahfoud, Abdellah Elbarkany & Ahmed El Biyaali

Authors
  1. Hassana Mahfoud
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  2. Abdellah Elbarkany
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  3. Ahmed El Biyaali
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Corresponding author

Correspondence to Hassana Mahfoud .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Department of Mathematics and Computer, Faculty of Sciences and Techniques, Settat, Morocco

    Abdelkrim Haqiq

  3. Information Technology Department, Faculty of Computers and Information, Giza, Egypt

    Aboul Ella Hassanien

  4. VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

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Mahfoud, H., Elbarkany, A., El Biyaali, A. (2018). An Enhanced Delay Time Model to Support Evidence Based Maintenance in Healthcare Domain. In: Abraham, A., Haqiq, A., Ella Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016. AECIA 2016. Advances in Intelligent Systems and Computing, vol 565. Springer, Cham. https://doi.org/10.1007/978-3-319-60834-1_18

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  • DOI: https://doi.org/10.1007/978-3-319-60834-1_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60833-4

  • Online ISBN: 978-3-319-60834-1

  • eBook Packages: EngineeringEngineering (R0)

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