An Intelligent System for Management of Medical Equipment Maintenance
Introduction:This paper proposes an intelligent system for managing medical equipment maintenance in healthcare facilities. The system utilizes machine learning algorithms and data analytics to predict equipment failures, schedule maintenance tasks, and manage spare parts inventory efficiently. The...
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| Format: | Article |
| Language: | English |
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Mashhad University of Medical Sciences
2023-07-01
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| Series: | Patient Safety and Quality Improvement Journal |
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| Online Access: | https://psj.mums.ac.ir/article_23132_a6a11d2e77fdc6157f2568ffad9894a2.pdf |
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| author | Abbas Izadi Mohamad Amin Bakhshali Hadi Ghasemifard Omid Sarrafzadeh |
| author_facet | Abbas Izadi Mohamad Amin Bakhshali Hadi Ghasemifard Omid Sarrafzadeh |
| author_sort | Abbas Izadi |
| collection | DOAJ |
| description | Introduction:This paper proposes an intelligent system for managing medical equipment maintenance in healthcare facilities. The system utilizes machine learning algorithms and data analytics to predict equipment failures, schedule maintenance tasks, and manage spare parts inventory efficiently. The aim is to improve equipment availability and reliability, reduce maintenance costs, and increase patient safety.Materials and Methods: The proposed system consists of several modules: data collection, preprocessing, equipment failure prediction, maintenance scheduling, spare parts inventory management, and integration. Real-world data is used to evaluate and compare the system's performance with other maintenance management approaches. Results: The results demonstrate that the proposed system can accurately predict equipment failures, schedule maintenance tasks efficiently, and manage spare parts inventory effectively. This improves equipment availability and reliability, reduces maintenance costs, and ensures that spare parts are available when needed without incurring excessive inventory costs.Conclusion:Overall, the proposed intelligent system for managing medical equipment maintenance is an effective solution for healthcare facilities to optimize maintenance operations, reduce costs, and ensure patient safety. |
| format | Article |
| id | doaj-art-61d19b6bb94447c8b7957d08e49d4d66 |
| institution | Matheson Library |
| issn | 2345-4482 2345-4490 |
| language | English |
| publishDate | 2023-07-01 |
| publisher | Mashhad University of Medical Sciences |
| record_format | Article |
| series | Patient Safety and Quality Improvement Journal |
| spelling | doaj-art-61d19b6bb94447c8b7957d08e49d4d662025-07-29T08:40:19ZengMashhad University of Medical SciencesPatient Safety and Quality Improvement Journal2345-44822345-44902023-07-0111316116710.22038/psj.2023.74922.140723132An Intelligent System for Management of Medical Equipment MaintenanceAbbas Izadi0Mohamad Amin Bakhshali1Hadi Ghasemifard2Omid Sarrafzadeh3Deputy of Treatment, Mashhad University of Medical Sciences, Mashhad, IranDepartment of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, IranDeputy of Treatment, Mashhad University of Medical Sciences, Mashhad, IranDeputy of Treatment, Mashhad University of Medical Sciences, Mashhad, IranIntroduction:This paper proposes an intelligent system for managing medical equipment maintenance in healthcare facilities. The system utilizes machine learning algorithms and data analytics to predict equipment failures, schedule maintenance tasks, and manage spare parts inventory efficiently. The aim is to improve equipment availability and reliability, reduce maintenance costs, and increase patient safety.Materials and Methods: The proposed system consists of several modules: data collection, preprocessing, equipment failure prediction, maintenance scheduling, spare parts inventory management, and integration. Real-world data is used to evaluate and compare the system's performance with other maintenance management approaches. Results: The results demonstrate that the proposed system can accurately predict equipment failures, schedule maintenance tasks efficiently, and manage spare parts inventory effectively. This improves equipment availability and reliability, reduces maintenance costs, and ensures that spare parts are available when needed without incurring excessive inventory costs.Conclusion:Overall, the proposed intelligent system for managing medical equipment maintenance is an effective solution for healthcare facilities to optimize maintenance operations, reduce costs, and ensure patient safety.https://psj.mums.ac.ir/article_23132_a6a11d2e77fdc6157f2568ffad9894a2.pdfmedical e1quipmentmaintenance managementintelligent systemmachine learning |
| spellingShingle | Abbas Izadi Mohamad Amin Bakhshali Hadi Ghasemifard Omid Sarrafzadeh An Intelligent System for Management of Medical Equipment Maintenance Patient Safety and Quality Improvement Journal medical e1quipment maintenance management intelligent system machine learning |
| title | An Intelligent System for Management of Medical Equipment Maintenance |
| title_full | An Intelligent System for Management of Medical Equipment Maintenance |
| title_fullStr | An Intelligent System for Management of Medical Equipment Maintenance |
| title_full_unstemmed | An Intelligent System for Management of Medical Equipment Maintenance |
| title_short | An Intelligent System for Management of Medical Equipment Maintenance |
| title_sort | intelligent system for management of medical equipment maintenance |
| topic | medical e1quipment maintenance management intelligent system machine learning |
| url | https://psj.mums.ac.ir/article_23132_a6a11d2e77fdc6157f2568ffad9894a2.pdf |
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