Throughout the medical equipment life cycle, preventive maintenance is considered one of the most important stages that should be managed properly. However, the need for better management and control by giving a reasonable prioritization for preventive maintenance becomes essential. The purpose of this study is to develop a comprehensive framework for preventive maintenance priority of medical equipment using Quality Function Deployment (QFD) and Fuzzy Logic (FL). The quality function deployment is proposed in order to identify the most important criteria that could impact preventive maintenance priority decision; meanwhile the role of the fuzzy logic is to generate a priority index of the list of equipment considering those criteria. The model validation was carried out on 140 pieces of medical equipment belonging to two hospitals. In application, we propose to classify the priority index into five classes. The results indicate that the strong correlation existence between risk-based criteria and preventive maintenance priority decision.
Comprehensive framework for preventive maintenance priority of medical equipment / Saleh, N.; Balestra, G.. - ELETTRONICO. - 2015-:(2015), pp. 1227-1230. (Intervento presentato al convegno 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 tenutosi a MiCo Center, Milano Congressi Center, ita nel 2015) [10.1109/EMBC.2015.7318588].
Comprehensive framework for preventive maintenance priority of medical equipment
Saleh N.;Balestra G.
2015
Abstract
Throughout the medical equipment life cycle, preventive maintenance is considered one of the most important stages that should be managed properly. However, the need for better management and control by giving a reasonable prioritization for preventive maintenance becomes essential. The purpose of this study is to develop a comprehensive framework for preventive maintenance priority of medical equipment using Quality Function Deployment (QFD) and Fuzzy Logic (FL). The quality function deployment is proposed in order to identify the most important criteria that could impact preventive maintenance priority decision; meanwhile the role of the fuzzy logic is to generate a priority index of the list of equipment considering those criteria. The model validation was carried out on 140 pieces of medical equipment belonging to two hospitals. In application, we propose to classify the priority index into five classes. The results indicate that the strong correlation existence between risk-based criteria and preventive maintenance priority decision.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2839002