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Article

Predictive Maintenance (PdM) Structure Using Internet of Things (IoT) for Mechanical Equipment Used into Hospitals in Rwanda

1
African Center of Excellence in Internet of Things (ACEIoT), College of Science and Technology, University of Rwanda, Kigali P.O. Box 3900, Rwanda
2
Telecommunications/ICT4D Laboratory, The Abdus Salam International Centre for Theoretical Physics, Strada Costiera, 11-I-34151 Trieste, Italy
*
Author to whom correspondence should be addressed.
Future Internet 2020, 12(12), 224; https://doi.org/10.3390/fi12120224
Received: 26 October 2020 / Revised: 23 November 2020 / Accepted: 24 November 2020 / Published: 7 December 2020
(This article belongs to the Special Issue Internet of Things (IoT) for Industry 4.0)
The success of all industries relates to attaining the satisfaction to clients with a high level of services and productivity. The success main factor depends on the extent of maintaining their equipment. To date, the Rwandan hospitals that always have a long queue of patients that are waiting for service perform a repair after failure as common maintenance practice that may involve unplanned resources, cost, time, and completely or partially interrupt the remaining hospital activities. Aiming to reduce unplanned equipment downtime and increase their reliability, this paper proposes the Predictive Maintenance (PdM) structure while using Internet of Things (IoT) in order to predict early failure before it happens for mechanical equipment that is used in Rwandan hospitals. Because prediction relies on data, the structure design consists of a simplest developed real time data collector prototype with the purpose of collecting real time data for predictive model construction and equipment health status classification. The real time data in the form of time series have been collected from selected equipment components in King Faisal Hospital and then later used to build a proposed predictive time series model to be employed in proposed structure. The Long Short Term Memory (LSTM) Neural Network model is used to learn data and perform with an accuracy of 90% and 96% to different two selected components. View Full-Text
Keywords: Predictive Maintenance (PdM); Internet of Things (IoT); equipment; components; monitoring; reliability; failure Predictive Maintenance (PdM); Internet of Things (IoT); equipment; components; monitoring; reliability; failure
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MDPI and ACS Style

Niyonambaza, I.; Zennaro, M.; Uwitonze, A. Predictive Maintenance (PdM) Structure Using Internet of Things (IoT) for Mechanical Equipment Used into Hospitals in Rwanda. Future Internet 2020, 12, 224. https://doi.org/10.3390/fi12120224

AMA Style

Niyonambaza I, Zennaro M, Uwitonze A. Predictive Maintenance (PdM) Structure Using Internet of Things (IoT) for Mechanical Equipment Used into Hospitals in Rwanda. Future Internet. 2020; 12(12):224. https://doi.org/10.3390/fi12120224

Chicago/Turabian Style

Niyonambaza, Irene, Marco Zennaro, and Alfred Uwitonze. 2020. "Predictive Maintenance (PdM) Structure Using Internet of Things (IoT) for Mechanical Equipment Used into Hospitals in Rwanda" Future Internet 12, no. 12: 224. https://doi.org/10.3390/fi12120224

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