Abb Research Ltd.

Gerhard Vollmar

Jari Kallela

Manuel Greulich

Zaijun Hu

Raiko Milanovic

Szaniszlo Szöke

Szaniszlo Sz&ouml;ke

Pousga Kabore

Szanislo Szöke

A system is suitable for carrying out a method for the automated processing of fault hypotheses in a course of a fault cause analysis in the case of a fault event in a technical installation. A data processing system uses knowledge-based models for fault cause analysis and physical models of installation functions and processes that can be carried out by the technical installation. The system has a first unit for calculating and storing installation and process states. The first unit has access to the physical models and to data that is stored in a data server for the technical installation. The system has a second unit for hypothesis processing and an input/output device.

Method and system for automatically verifying fault hypotheses predetermined by a user

A method and system for generating an XML-based fault model for fault case analysis, i.e., fault events in industrial plants includes a data entry device connected to a word processor belonging to a data processor having access to a template memory and being connected to a first fault model memory, by which measures the data entry device is set up for data entry for compiling a fault model as a Word document and for storing the document in the model memory, a translator accessing the model memory and connected to a schematic memory storing XML types produced by transferring a template in the template memory into XML types, a second fault model memory storing XML instances produced by translating the document, and an XML engine accessing the schematic memory and the second memory and displaying an XML-based fault model stored therein through a display device and a web browser.

System and method for generating an XML-based fault model

A system and method for supporting a fault cause analysis in a afault event in a plant includes a data processor with memory storing a fault model of XML files accessed by a fault cause navigator and an operating/display device. Each fault model contains an industry-specific process model divided into process steps, with steps and defined fault events needed therefor assigned to plant components/systems, and fault trees assigned to fault events and having fault hypotheses. A checklist with symptoms for verification of the fault hypothesis is assigned to the fault hypotheses. The system enables navigation to the relevant step in the process model by the display and navigator, and presents a fault event list. Following fault event selection, critical components/systems corresponding thereto are found and displayed. Possible symptoms are generated and displayed in a checklist and hypotheses of possible fault causes, contained in the fault trees, are found and displayed.

System and method for supporting a fault cause analysis

A method and a system acquire and store data from a production plant in order to provide relevant data for a fault analysis. Here, the production plant is allocated a data server, with the aid of which production data acquired by measurement are buffered. By a data input of a data processing device, additional information, which an operator inputs, can be acquired. By an event monitoring functional unit belonging to the data processing device, an evaluation of production data is carried out cyclically, the event monitoring system has access to production data in the data server, as well as to the additional information, on the basis of monitoring criteria which are contained in a stored script, and stores relevant production data in one of a number of databases depending on the event detected.

Method and system for acquiring and storing data from a production plant

A method is described for the automated determination of fault events by evaluation of field data of a production installation within a system for determining the effectiveness (overall equipment effectiveness (OEE)) of the production installation and for the analysis of causes of faults. The determination of the fault events takes place using a data processing device and programs stored in it for carrying out the functions of a fault event detector and an OEE script configurer. The OEE script configurer accesses a prescribed productivity model specific to a production installation type, generates an OEE script with likewise prescribed configuration data taken into account and stores it in an OEE script memory. The fault event detector accesses the OEE script, calls up field data from a data server, derives fault events from the field data according to processing instructions of the OEE script, and stores them in a fault database.

Method for the automated determination of fault events

A method for automated generation of an extended fault tree structure adapted to a production installation or a specific installation is used within a system determining the effectiveness and analyzing causes of faults. Generation takes place using a data processor and stored programs for carrying out functions of a hypothesis verifier, a fault data classifier, and a hypothesis configurer, and also based upon a prescribed general hierarchical fault tree structure produced by accessing data of a data server with the verifier, from which it derives fault events according to execution requirements of the verification script and stores these fault events, possibly together with previously entered fault events, in a fault database. At prescribable time intervals, the classifier carries out classification of the fault events by accessing the database, maps them as weighted causes of faults onto the tree structure, and displays or outputs the tree structure so extended.

Method for the automated generation of a fault tree structure

A system for determining fault causes, including automated determination of hypotheses in the context of a fault cause analysis and automated performance of hypotheses verification, has a data processing device connected to a data input and visualization device and to a data memory. The data processing device contains a processing unit for fault cause analysis, a first comparator, a second comparator and a hypothesis selector. The data memory contains a general fault model, a fault event list, an empirical database and a storage area to store a log of the current fault cause analysis. The data processing device, following the selection of a fault event from the displayed fault event list by a user, to display to the latter hypotheses suggested by the system, following the selection of hypotheses to be verified, to carry out hypotheses verification and, as the result, to log and display determined fault causes.

System for determining fault causes

A method and a system are described for determining the effectiveness of production installations, significant fault events that bring about deviations from a desired effectiveness and the causes of fault events. The production installation is connected to a data acquisition device, which is set up for continuous acquisition and ready-to-call-up storage of installation and production-related data. A service device is connected to the data acquisition device and has an input device for the input of additional installation and production-related descriptive data that cannot be called up from the data acquisition device. An online system part is set up for calling up installation and production-related data from the data acquisition device, calculating the effectiveness, detecting fault events, determining significant fault events by fault event evaluation, and determining in each case the causes of faults. An offline system part is provided and contains a number of generic fault models and assessment models.

System and method for determining the effectiveness of production installations, fault events and the causes of faults

A system and a method ascertain the optimum operating speed of a production machine that is configured to operate in a specific speed range. The production machine is assigned a data acquisition device that acquires production data, in particular time and duration of machine downtimes caused by fault events, and also production unit numbers per unit time. A data processing device acquires additional information, by using a data input device, in particular the respective reason for a failure, and also the description of the product to be processed in each case. Using a production-data acquisition device, production data can be called up from the data acquisition device and linked with the additional information from the data input device. An assessment function ascertains an operating speed from the production data and a stored assessment model. An optimization function forms an optimum operating speed desired value by linking the ascertained operating speed with production unit costs.

System and method for ascertaining the optimum operating speed of a production machine

A method, a device, and a corresponding system for controlling a discrete production process produce or process in a number of production steps. Each step uses a machine, so that different intermediate products are produced. Buffer times are defined and taken into account during which one machine is able to continue to operate for the duration of the failure of one of the machines of a preceding production step by processing a stock of intermediate products corresponding to the associated buffer time and stored in a buffer during the production. In this case, production data are acquired continuously for each machine and, with access to these production data, statistically averaged repair times MTTR (Mean Time to Repair) are calculated cyclically by using a MTTR calculator. Based on these times MTTR , buffer times are calculated by using a T calculator and are fed to a device for controlling the production process as desired values for buffer times.

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Meckenheim, Germany

Gerhard Vollmar