Development of a Failure Prediction Strategy for Imaging Systems

Predictive maintenance offers great added value for patient safety, availability and safeguarding the clinical process. Through the exchange of relevant data from networked medical devices, increasingly automated decision-making and early failure prediction are possible. Using the early condition assessment and the maintenance measures derived it is possible to react preventively to these forecasts within the maintenance process. This can lead to the avoidance of cost-intensive and risky system failures. Various methodological approaches of qualitative and quantitative origin were examined to develop the strategy. Inventory records of the BG hospital group and analyses of the development statuses of various manufacturers for predictive maintenance served as the basis for this. Based on the analysis of the data and various expert interviews, these approaches were evaluated and strategies were designed. The combination of a manufacturer's solution with in-house measures turned out to be the most promising. The analysis and evaluation are carried out by the manufacturer and can then be used by the clinical engineers. Additional components of the generated error messages are measures for prevention or elimination. As a result, internal hospital expertise and an extended data basis for the evaluation of the system status are initially not absolutely necessary and a failure prediction can be incorporated into the clinical process. This enables an increase in own performance and improved transparency and efficiency. At present, failure prediction for the clinical side is therefore only possible in cooperation. Through additional measures such as the sensitisation of staff, training and the associated increase in specialist expertise, there is the possibility of reacting more quickly and precisely to failure predictions and of operating predictive maintenance partly in-house. Furthermore, with the help of the strategies developed, an optimisation of the existing maintenance strategy and working conditions within the hospitals can be achieved.