Predictive Maintenance in Healthcare System: A Survey

Abstract

Medical devices are a vital component of healthcare systems, the advantages they may give continue to grow as they are crucial for the safe and effective prevention, diagnosis, treatment, and rehabilitation of illnesses and diseases. Therefore, it is critical to maintain them in good operating order to ensure optimum availability, minimal failures, and guarantee patients’ and users’ safety. The stages involved in medical devices regulation and management are complex, but they are necessary to ensure their quality, safety, and compatibility with the settings in which they are used. Medical equipment complexity has increased due to technological advancement and the traditional maintenance strategies do not meet the needs of today’s healthcare organizations. Therefore, integrating information technology, social networking technologies, digitization and management of medical devices, and the use of big data technologies and Machine Learning (ML) techniques has the potential to significantly improve healthcare services. Integrating autonomous and intelligent systems where data and sophisticated data analytics may be employed led to enhanced equipment data collecting via the deployment of information and communication technologies, notably intelligent devices. With this advancement came an increase in Predictive Maintenance (PdM) solutions. PdM has become a commonly used approach, described as a set of procedures used to evaluate the condition of equipment and predict future failures. These estimations are then utilized to schedule maintenance activities through smart scheduling of maintenance procedures, which aids in preventing or at least minimizing the impacts of unanticipated failures. The purpose of this article is to present a Systematic Literature Review (SLR) exploring and reviewing prior research on the subject of PdM and the developments of this method, particularly in the medical field. In addition to supporting new research projects in the PdM sector, this paper offers a good foundation for understanding PdM approaches, their key findings, problems, and potential. This review focuses on two scientific databases from which a substantial number of articles dedicated solely to PdM in the medical field have been retrieved for analysis. Our research led us to conclude that, despite the many potential benefits of predictive maintenance in the medical field, the concept is still being under-exploited and faces many obstacles.