A machining diagnosis device (100) includes a machining data acquirer (3) to acquire, from a machining tool (1), machining data including a result of machining performed based on a machining condition, a cutting section extractor (4) to extract, from the acquired machining data, a cutting section corresponding to a stable machining period and machining data for the cutting section, a cleansing unit (8) to acquire the machining condition for cutting and perform, in accordance with the acquired machining condition, cleansing of the machining data extracted by the cutting section extractor (4), a feature calculator (9) to calculate a feature based on the cleansed machining data, and a machining diagnoser (11) to diagnose machining based on the calculated feature.

Conducting automatically a process failure mode and effect analysis, PFMEA, for a factory adapted to produce a product in a production process using a meta model, MM, stored or loaded in a data storage. The stored meta model, MM, comprises abstract factory model elements modeling an abstract factory, AF, including one or more service declarations modeling abstract services across different factories, wherein each service declaration comprises failure mode declarations for different failure modes.

A computer-based method for automated hazard detection for a technical system, the method includes the step of selecting an output failure mode of a component of a component fault tree of the technical system as a top level hazard. The computer-based method includes the step of generating a hazard information tree by means of a subtree of the component fault tree, wherein the subtree is selected by means of the top level hazard, wherein the subtree is modified by removing predefined nodes from the subtree and by enhancing output failure modes of the subtree with information from which component the output failure modes originate, wherein the modified subtree is saved in a memory unit as hazard information tree. The computer-based method includes the step of evaluating the hazard information tree, and providing a control signal comprising a result of the evaluation.

An information processing device including a CPU and a memory storing a program. The CPU generates a plurality of cause-and-effect models between variables based on a relationship between a plurality of mechanisms in a production process of a production line, a dependency between a plurality of events associated with the plurality of mechanisms, or a control-based relationship between the plurality of mechanisms, obtains a result of abnormality detection in the production line, calculates a contribution ratio of a variable contributing to abnormality in the result of abnormality detection, and estimates an abnormality causal factor for at least one of the plurality of cause-and-effect models based on the calculated contribution ratio of the variable contributing to abnormality.

The present invention relates to a device (106) for determining a reliability measure for a given function established by one or more functional blocks of a system component (105, 120, 130, 140) to be assessed. The device comprises input means (200) for receiving, for each functional block establishing said given function, information from one or more diagnostic blocks each representing a condition of the respective functional block of the system component to be assessed, said functional block being involved in establishing the given function, a module (201) arranged for classifying said conditions, for deriving diagnostic test interval information and for determining a functional block reliability estimation for each of the functional blocks based on the diagnostic test interval information and/or on the classified conditions, calculation means (202) adapted for determining a reliability measure for that given function established by the one or more functional blocks based on the one or more functional block reliability estimations, decision means (203) for deriving a decision from the reliability measures of the given function, output means (204) for outputting the decision in a format adapted for a physical interface of said system component.

Various embodiments include modeling a component fault tree for a circuit with an input-side and an output-side component. These include using a fault tree corresponding to a hazard for each respective component, obtaining information about the components of the circuit and a connection between components, and connecting the respective fault trees based on the circuit description. Each fault tree includes an input fault mode or a basic event and an output fault mode. The output fault mode and the input fault mode are each assigned to a component terminal. An output fault mode of the input-side component tree is connected to an input fault mode of the output-side component tree if: there is a connection between the assigned terminal of the input-side component and the output-side component and the output fault mode of the input-side component correlates to an input fault mode of the output-side component.

A data processor system for monitoring a complex system, the processor system configured to receive a plurality of pieces of state information and to merge at least the pieces of state information into a piece of failure information, at least one of the pieces of state information being associated with a confidence flag, and the piece of failure information also being associated with a confidence flag. The system performs the merging by implementing a fuzzy logic technique to produce the piece of failure information while taking account of the respective confidence flag of the pieces of state information and to produce the confidence flag associated with the failure information.

A method for monitoring the operation of a turbomachine controlled by a digital control system including at least one component, includes acquiring operating state information relating to the state of at least one component; determining, depending on the state information acquired, a current degraded configuration in which at least one of the components has failed; determining a classification of the current degraded configuration using at least one classification table stored in a storage device, the classification tables associating with at least one degraded configuration one classification expressing the level of criticality of the degraded configuration, the tables being obtained by calculating a conditional probability of a predefined anticipated event from the probability of occurrence of elementary events relating to a failure of one of the components; and estimating an operating time permitted for the turbomachine depending on the classification determined for the current degraded configuration.

A processor generates a first allocation matrix and accesses a representation of relationships between individual system elements, representing lower-level system elements to be considered at a current-level of design of a product, with each other. The processor creates an element entry in the first allocation matrix for at least a subset of the individual system elements and creates an element entry in the first allocation matrix for one or more directional relationships between the individual system elements as indicated in the representation. The processor creates function and requirements entries in the first allocation matrix based on pre-existing requirements for the product applicable to the current-level of design and generates additional function and requirements, as well as creates corresponding entries in the first allocation matrix, based on current-level architectural requirements, including at least functions and requirements for one or more of the directional relationships indicated in the representation.

A diagnosis unit (1) for detection, analysis, and data management of sensor data detected on an actuator (20), has at least one sensor (14, 15), a data processing unit (10), a data manager (11), and an interface unit (12). The at least one sensor (14, 15), the interface unit (12), and the data manager (11) are respectively, connected to the data processing unit (10), enabling data exchange. The diagnosis unit (1) is built into a module with the actuator (20).