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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 8 Issue 11 pp. 1159-1168 , 2018

A petri net based reliability block diagram model for category I medical devices reliability analysis Pages 1159-1168 Right click to download the paper Download PDF

Authors: L. Childs, K. Jenab, S. Moslehpour

DOI: 10.5267/j.msl.2018.8.008

Keywords: Medical equipment, Medical field, Petri Net, Reliability, Reliability block diagrams, Technology

Abstract: The medical industry incorporates technology and breaks different types of equipment into three various categories determined according to the technologies and their usage. The first category, which is the focus of this article, consists of devices that are directly linked to the life of the patients, for example a ventilator. The purpose of this study is to develop a new reliability technique, based on the Reliability Block Diagram (RBD) and Petri Net, for Category 1 equipment. The RBD, focuses on showing how the failure of different parts could affect the sub-systems of the equipment and how those failures could cause an overall system failure. The second method, Petri Net, is a tool that is used to analyze various types of information processing systems. Combining these two methods will allow the user to determine the reliability of the different systems and subsystems with various pieces of equipment. The knowledge gained by this analysis will be used to determine the likelihood that the failure of specific subsystems will cause an overall system failure. The overall anticipated result is to thoroughly develop this new methodology. The complete process that is used to finish the calculation process for the subsystems will be shown, in addition to the completion of the final Reliability Block Diagram.

How to cite this paper
Childs, L., Jenab, K & Moslehpour, S. (2018). A petri net based reliability block diagram model for category I medical devices reliability analysis.Management Science Letters , 8(11), 1159-1168.

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Journal: Management Science Letters | Year: 2018 | Volume: 8 | Issue: 11 | Views: 2659 | Reviews: 0

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