EP1307816A1 - System for determining error causes - Google Patents

System for determining error causes

Info

Publication number
EP1307816A1
EP1307816A1 EP20000960421 EP00960421A EP1307816A1 EP 1307816 A1 EP1307816 A1 EP 1307816A1 EP 20000960421 EP20000960421 EP 20000960421 EP 00960421 A EP00960421 A EP 00960421A EP 1307816 A1 EP1307816 A1 EP 1307816A1
Authority
EP
Grant status
Application
Patent type
Prior art keywords
error
fault
hypotheses
analysis
current
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP20000960421
Other languages
German (de)
French (fr)
Inventor
Manuel Greulich
Gerhard Vollmar
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
ABB Research Ltd
Original Assignee
ABB Research Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

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Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/22Detection or location of defective computer hardware by testing during standby operation or during idle time, e.g. start-up testing
    • G06F11/2257Detection or location of defective computer hardware by testing during standby operation or during idle time, e.g. start-up testing using expert systems

Abstract

The invention relates to a system for determining error causes, including an automatic determination of hypotheses in the frame of an error cause analysis and for automatic carrying out of the verification thereof, whereby the system comprises a data processing device (20), connected to a means of data input and visualisation (10) and a data store (30). The data processing device (20) comprises a processor unit for error cause analysis (21), a first comparator (22), a second comparator (23) and a hypothesis selection (24). The data store (30) comprises a general error model (33), an error events list (32), an empirical data bank (34) and a store region for depositing a protocol of current error cause analyses (31). The data processing device (20) is arranged for displaying the hypotheses suggested by the system to a user after the selection of an error event by said user from the displayed error events list (32) and, after selection of a hypothesis for verification, to carry out the verification thereof, log and display the determined error causes as the result.

Description

System for determining causes of errors

description

The invention relates to a system for determining the cause of failures, including a computer-aided generation of hypotheses and to perform its verification as part of a fault cause analysis. The system is designed to support the cause of the error search in the case of incoming error events in industrial plants.

For the fault cause analysis of different methods and techniques can be used. These include the Fault Tree Analysis (Fault Tree Analysis) or the error cause analysis (root cause analysis) in various versions, such as described in [Reliability Center, Inc .: Root Cause Failure Analysis Methods, Hopewell, United States, 1997] or [ASB Group Inc. , Risk and Reliability Division: root Cause Analysis Handbook: A Guide to Effective Incident Investigation, Knox ville, USA, 1999].

In such a fault cause analysis, the following steps are typically carried out:

1. Carry out an FMEA (Failure Mode And Effects Analysis) to determine the really important mistakes.

2. carry out the actual cause of the error analysis for each of the significant errors. The following sub-steps are carried out: a) ensuring all necessary information which allow conclusions about the course and causes of the error, for example, damaged components, capable of the same, interviews with operators, process data, etc. b) Organization of failure analysis. Determining the necessary resources and implementation plan. c) actual analysis, for example, based on fault tree and determining the error causes. Here, fault trees are set up with which the error causes can be determined based on the error event over several levels cause.

3. implementing the improvements. For this, the identified fault causes and recommendations for corrective actions to the appropriate decision makers to communicate and it is established an action plan under which the recommendations are carried out. Could this action plan will be successfully completed, the analysis is finished.

Hypotheses for causes of errors are needed in step 2c if repeated starting from the fault event the question is asked, could lead to the error event. Hypotheses are therefore speculate on the cause of the error based on empirical knowledge. hypotheses to be verified by the previously seized information will be used on the error and thus the hypothesis can be confirmed or refuted. If a hypothesis is confirmed in this way, the situation described by the hypothesis to a fact or a fact. For this fact, in turn, the question may be asked, could lead to this fact, that it be placed more hypotheses.

A disadvantage of the known method is that the creation of hypotheses and their verification depends on the experience of the error or the analysts. Even if appropriate fault trees, generated from fault models, for example, are present, they are not directly usable for the present failure analysis. Rather have such errors trees and also the hypotheses contained therein to the particular, be adapted to be examined error event. For this purpose, an experienced analyst error is necessary.

The invention has for its object to provide a system for determining the causes of errors that enables automated determination of hypotheses and their verification as part of a requisite fault cause analysis. This object is achieved by a system for determining the causes of errors that includes an automated determination of hypotheses and their verification, and having the features indicated in claim. 1 Advantageous embodiments are indicated in further claims.

The system supports a user in the analysis of selected fault events by making proposals for the execution of a general fault model. These proposals relate to an appropriate entry point in the model and in particular suitable hypothesis and verification options that enable efficient implementation of the fault cause analysis. To use the system experiences gained in already carried out error analyzes and are available in a library experience.

A further description of the invention and the advantages thereof will be given below with reference to embodiments which are illustrated in the drawing figures.

Show it:

Fig. 1 is a block diagram of a system according to the invention for automatic generation of hypotheses and their verification for determining the causes of errors, Fig. 2 is an illustration of the operation of the system,

Fig. 3 is a description of the current error event,

Fig. 4 shows a schematic representation of the general fault model,

Fig. 5 is a diagram for categorization of the error models,

Fig. 6 essential contents of a fault hypothesis,

Fig. 7 successive referencing error models, and

Fig. 8 shows the integration of a hypothesis information in the execution of the overall error model.

The proposed system can be implemented locally in a computer and used. Preferably, however, an implementation of the Internet, because then easily worldwide use for service purposes is possible. Fig. 1 shows the diagram of a system for automatic generation of hypotheses and their verification for determining the cause of failures. The system is divided into means for data input and visualization 10, a data processing device 20 and a data memory 30. As a means for file input and visualization is a common Web browser 11 is used. The data processing device 20 includes a processing unit for fault cause analysis 21, which coordinates the execution of the fault cause analysis. For processing additional components are available that support the detailed steps, namely a first comparator 22, a second comparator 23 and a hypothesis-selection 24. The processing unit for fault cause analysis 21 uses data from the data memory 30 in which an access to a fault events list 32, a general fault model 33 and an experience database takes place 34th Intermediate and final results of failure analysis are stored in a log current fault cause analysis 31st In the log 31 are added: the respectively selected current error event description, a suitable entry point in the overall error model, selected experience failure analysis, a list of selected information fault hypotheses and the result of the fault cause analysis, that is, the error causes determined. User input is requested by the processing unit for fault cause analysis 21 via the Web browser. 11 Results are presented to the user via the web browser. 11

Fig. 2 shows a flow diagram illustrating the operation of the system.

In step 100, the user through the web browser interface 11 selects one to be examined failure event from the list of error events 32 and stores it in the component log current fault cause analysis 31 from. The description of this current error event is discussed in more detail in Fig. 3.

In step 200, the system compares by means of the first comparator 22, the description of the current error event (see Fig. 3) with the contents of the general fault model 33 and proposes entry points to the error analysis before. The system uses this common attributes describing the current error event and the general fault model, such as error title, error text effects Auswir-, error code and error location, and checked the values ​​of equality and similarity. A suitable method that performs this check is, for example, the nearest neighbor method [I. Watson: Applying Case-Based Reasoning: Techniques for Enterprise Systems, Morgan Kaufmann Publishers, Inc., San Francisco, 1997, pages 23 to 33]. The structure of the general fault model, Figs. 4, Fig. 6 and Fig. 7. If the system suggests more suitable fault trees as the entry point for the failure analysis, the user selects the most appropriate. The system saves a description of the entry point in the component log current fault cause analysis 31st

In step 300, the system compares by means of the second comparator 23, the description of the current error event with the experience failure analysis of the empirical database 34 and proposes suitable experience failure analysis. Similar to step 200, the system compares here the common attributes of the current error event, and the experience failure analysis. The nearest neighbor method is suitable also for the similarity test. An experience error analysis shows how and with what result, a failure event was analyzed. Predominately summarized the key during the analysis hypotheses and their verification in a list. The user selects the most appropriate experience failure analysis. The system stores this experience failure analysis in the component log current fault cause analysis 31 from.

In step 400, the system conceived by the component hypotheses selection 24 lists all the selected experience hypotheses together and suggests the user to candidates for a current error analysis before. The hypotheses are having particular regard to the

occurred in many fault analysis, had a key role in the cause identification, for example because the relevant verifications had a special significance, were considered especially important by the practitioner, for example, because an investigation into an entire complex of causes could be excluded, or, with very little effort had to be verified. The user selects those hypotheses, which he wants to use as part of the current error analysis. The system stores this experience hypotheses in the component log current fault cause analysis 31 from.

In step 500, the selected in step 400 hypotheses in the processing of the general fault model are integrated. To perform the error analysis, the system follows the general fault model and processes the hypotheses contained therein. For each hypothesis, the system checks by comparison of the attributes if appropriate experience hypotheses exist. In this case, the information including hypothesis verification is used, otherwise the hypothesis is maintained from the general model. The system stores the causes of errors detected as the result of the fault cause analysis in the component current protocol fault cause analysis 31..

Fig. 3 shows the view of a current error event. For this purpose, the error event in the attributes error text effects of the error, time at which the error occurred, the error code used internally in the error code list and the fault will be described. In addition, reference is made to other system records that reflect the process situation at the time of the error. This includes the process data, as recorded by the control system, the operator log and the work reports from the Maintenance Management System.

Fig. 4 shows the schematic view of a fault model. The uppermost level includes a process model having a plurality of process steps. Each process step can be further divided into process steps. there are error events and critical process components to each process step.

The next lower level of the model includes fault trees. Fault trees are shown in FIG. 5 can be seen, categorized. A fault tree can be composed of several sub-trees. This is indicated in Fig. 5 by the arrows and is explained in more detail in Fig. 7. The nodes of a fault tree represent fault hypotheses. Essential content component of a fault hypothesis is a checklist for verification. The contents of a hypothesis is discussed in more detail in Fig. 6.

Fig. 5 shows the classification of fault models. The prepared thereon industry-specific fault models are features of a particular industry, such as fault models for the cement industry or error models for the steel industry. This category of fault models has as the top node the error event. An error event is an undesirable condition that affects the production.

A second category of FIG. 5 describes component faults. These models are universal, so are applicable in different industries. Typically refer hypotheses of industry-specific fault models for component failures models.

The third category of fault models describes very generally applicable fault relationships. Such errors, for example, have their roots in inadequate training of staff, organizational grievances or problems in maintenance. These models are underlain the industry-specific fault models and component fault models.

Fig. 6 shows the essential contents of a fault hypothesis in the example of a cleaning system of steel plates. The hypothesis includes a description of fault relationships. In addition, the affected component or the affected part-system of the hypothesis is associated. A checklist describes criteria such as the hypothesis can be verified. For each criterion, the cost of diagnosis is specified. The hypothesis may be underlain complex independent fault trees. This reference is in the fault tree reference.

Fig. 7 shows an example of the error event 'Unzureichenende product quality' as fault trees refer to each other and complex and extensive fault relationships can be modeliiert as in this manner. Fig. 8 illustrates the example of FIG. 7 engages and shows how the fault hypothesis 'error in the cleaning system' when processing the general fault model is replaced by a fitting experience hypothesis. The entire fault tree (as shown left), by the far smaller fault tree the experience hypothesis be replaced, which can significantly reduce the overhead of processing (right in the illustration).

Claims

claims
1. System for determining the cause of failures including an automated determination of hypotheses in a Fehierursachenanalyse and for automated implementation whose verification, wherein the system comprises a data processing device (20) provided with means for data input and visualization (10) and (with a data memory 30 ) is connected, and wherein
a) data processing means (20) includes a processing unit (for fault cause analysis 21), a first comparator (22), a second comparator (23), and a hypothesis selecting (24), b) the data storage (30) a general fault model ( 33), an error events list (32), an empirical database (34) and a memory area for storing a. contains Protocol current fault cause analysis (31), and c) the data processing device (20) is adapted to display after selection of a fault event from the displayed error events list (32) by a user, proposed to it by the system hypotheses by selection verifying the hypotheses, perform the verification, and as a result to monitor causes of errors detected or display.
2. System according to claim 1, characterized in that the means for data input and visualization (10) include a web browser (11), with the use of which allows the user input and intermediate and final results of analysis can be displayed.
3. System according to claim 1 or 2, characterized in that the data processing device (20) is adapted
(a) in a first step 100) display the error events list (32) to the user and one selected by him error event or selected error events in the log current fault cause analysis (31) to store, (b) in a second step 200) by means of the first comparator (22) to compare the belonging to a selected current error event description of the error event with the contents of the general fault model (33), and from the general fault model (33) to display appropriate error trees to perform the further analysis, and after selecting a fault tree for this to store in the log current fault cause analysis (31), (c) in a third step 300) display (by means of the second comparator 23) the description of the current error event with experience failure analysis of the empirical database (34) to compare and suitable experience failure analysis, and after selection experience of error analyzes it in Prot storing okoll current Fehierursachenanalyse (31), (d) in a fourth step (400) by means of the unidirectional component hypotheses selection 24) in a list summarize the hypotheses contained in the selected experience failure analysis and display, and upon selection of hypotheses this in save log current Fehierursachenanalyse (31), and e) work through the general fault model (33) in a fifth step (500) using the stored data from the record current Fehierursachenanalyse (31), thereby to carry out a verification of the selected hypothesis and as a result storing the determined verification error causes in the current protocol Fehierursachenanalyse (31).
EP20000960421 2000-08-09 2000-08-09 System for determining error causes Withdrawn EP1307816A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/EP2000/007730 WO2002013015A1 (en) 2000-08-09 2000-08-09 System for determining error causes
US10364004 US6952658B2 (en) 2000-08-09 2003-02-10 System for determining fault causes

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EP1307816A1 true true EP1307816A1 (en) 2003-05-07

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EP (1) EP1307816A1 (en)
WO (1) WO2002013015A1 (en)

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Also Published As

Publication number Publication date Type
US6952658B2 (en) 2005-10-04 grant
US20040158434A1 (en) 2004-08-12 application
WO2002013015A1 (en) 2002-02-14 application

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