Zusammenfassung von EPC2000 Art 056 für die Entscheidung T0182/20 vom 24.10.2023

In T 182/20 the invention concerned predicting future malfunctions of mechanical or electrical components based on the current values of one or more parameters. Beyond the server-based processing, the method in claim 1 comprised a number of technical features. Firstly, the method involved measuring specific parameters (e.g. temperature and lubricant condition in the bearings of a gas turbine), which the board considered to be inherently technical (G 1/19, points 85 and 99 of the Reasons). Furthermore, these measurements were used to predict specific malfunctions in particular components (e.g. a bearing defect in a gas turbine or an insulation defect in a transformer). The board considered that the choice of parameters for predicting the specified malfunctions reflected technical considerations about the functioning of the claimed mechanical or electrical components. On the other hand, the mathematical calculations in steps 3) and 4), when considered in isolation, were non-technical. These computations generated numerical data, i.e. the conditional probability of a future malfunction in an electrical or mechanical component and the question remained, whether these calculations contributed to the technical character of the invention. With reference to G 1/19 the board saw the conditional probability obtained by the method of claim 1 as an indirect measurement of the physical state (i.e. a particular failure) of a specific physical entity (i.e. a specific mechanical or electrical component). The mathematical framework in the claim is rooted in stochastic modelling and simulation, specifically Markov chains, which are recognised for credibly capturing and predicting the transition dynamics of systems based on empirical data. The fact that the result is a probability does not detract from its ability to provide a technically meaningful estimate of the component's state. Making accurate predictions in the real world, given all its uncertainties, is rarely possible. The board also saw a credible causal link between the measured parameters and the predicted malfunctions. For instance, a bearing defect in a gas turbine is likely to generate more heat, degrade lubricant, and cause vibrations in the shaft and/or casing. Therefore, temperature, lubricant condition, and shaft or casing vibrations are suitable parameters for predicting a bearing defect. In summary, the board was satisfied that the calculated probability provided a credible estimate of the future physical state of a specific physical entity and, therefore, could be seen as an indirect measurement. For these reasons, the board judged that the mathematical steps in claim 1 were part of a technical measurement method. The board remitted the case for further examination.