Self-diagnosis and self-repair system for image forming apparatus

• US 5,239,547 A
• Filed: 09/26/1990
• Issued: 08/24/1993
• Est. Priority Date: 09/21/1990
• Status: Expired due to Fees

• Current Assignee: Mita Industrial Co., Ltd. (Kyocera Corporation)
• Original Assignee: Mita Industrial Co., Ltd. (Kyocera Corporation)
• Inventors: Shimomura, Yoshiki, Yoshikawa, Hiroyuki, Tomiyama, Tetsuo, Umeda, Yasushi
• Primary Examiner(s): Beausoliel, Jr., Robert W.
• Assistant Examiner(s): CHUNG, PHUNG M
• Application Number:
  US07/588,177
• Time in Patent Office: 1,063 Days
• Field of Search: 371/16.4, 371/15.1, 371/40.1, 371/10.1, 371/21.1, 371/23, 371/29.1, 355/207, 395/911, 395/912, 395/916
• US Class Current: 714/26
• CPC Class Codes: G03G 15/55 Self-diagnostics; Malfunction or lifetime display
• CPC Class Codes: G06F 11/0733 in a data processing system embedded in an image processing device, e.g. printer, facsimile, scanner
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/2257 using expert systems
• CPC Class Codes: Y10S 706/911 Nonmedical diagnostics

Abstract

The system of the present invention has a plurality of sensors 1a, 1b and 1c and a system control circuit which includes a case memory portion and a work script memory portion. In response to application of state data from the sensors 1a, 1b and 1c, the system converts the state data into symbolic data. Then the symbolic data is evaluated to judge whether or not a fault exists and to specify a fault symptom. As a result of the judgement, a fault symptom and a fault in the objective machine are determined. Thereafter, cases stored in the case memory portion are retrieved on the basis of the results of the fault diagnosis and a fault simulation. A case which closely resembles the present state of the objective machine is selected. Then, repair work described in the selected case is executed.

Claims

1. A self-repairing system for an image-forming apparatus which includes a plurality of interrelated elements, the interrelated elements including actuator elements which control operations carried out by the image-forming apparatus, and sensor means for sensing conditions in the image-forming apparatus and providing condition data indicative thereof, said self-repairing system comprising:

memory means including;

a first memory for storing characteristic data representative of various characteristics of the image-forming apparatus, interrelationship knowledge representative of the interrelationships of the elements of the image-forming apparatus, and diagnostic knowledge,

a second memory for storing repair case knowledge, and

a third memory for storing repair work script knowledge;

diagnostic means for determining whether the image-forming apparatus is in a normal or an abnormal condition based upon condition data from the sensor means, the characteristic data from the first memory and the diagnostic knowledge from the first memory; and

a repair plan inference means, responsive to a determination by the diagnostic means that the image-forming apparatus is in an abnormal condition, for inferring a repair case from the repair case knowledge from the second memory and a work script from the work script knowledge from the third memory to provide a repair plan to select one of the actuator elements for influencing one of the operations in the image-forming apparatus.

2. A self-repairing system as claimed in claim 1, wherein the repair case knowledge is organized into repair cases which each include pre-repair condition data and work index data and the work script knowledge is organized into work scripts which each list a work for influencing an actuator element.

3. A self-repairing system as claimed in claim 2, wherein said self-repairing system comprises conversion means for converting condition data from the sensor means to symbolic data, and wherein the diagnostic means determines the condition of the image-forming apparatus from symbolic data provided by the conversion means, and the diagnostic knowledge from the first memory.

4. A self-repairing system as claimed in claim 3, wherein the diagnostic means comprises:

means for identifying a fault symptom;

fault simulation means for identifying a fault cause based upon the interrelationship knowledge and symbolic data from the conversion means; and

wherein

the repair plan inference means selects a repair case based upon a fault symptom identified by the symptom identifying means and a fault cause identified by the fault simulation means.

5. A self-repairing system as claimed in claim 4, wherein the repair plan inference means compares the pre-repair condition data of a selected repair case to the condition data from the sensor means, and work antecedent data associated with a work indicated by the work index data of the selected repair case to the condition data from the sensor means.

6. A self-repairing system as claimed in claim 5, wherein the repair plan inference means infers a different work for influencing one of the actuator elements to change condition data received from the sensor means to be the same as the pre-repair condition data of the work indicated by the selected repair case when the pre-repair condition data of the selected repair case is different from received condition data.

7. A self-repairing system as claimed in claim 6, wherein the repair plan inference means infers a failure cause which causes an indicated work to fail, and thereafter infers corrective work.

8. A self-repairing system as claimed in claim 7, wherein for inferring failure causes and corrective work, the repair plan inference means retrieves all repair cases having pre-repair condition data that are different from some of the received condition data and that are common to all the retrieved cases, and thereafter searches to locate a corrective work in the selected work script to influence an actuator element to cause the different received condition data to become the same as corresponding data in the retrieved cases.

9. A self-repairing system as claimed in claim 8, wherein if the corrective work is successfully executed along with remaining works indicated by the selected repair case, the repair plan inference means infers a new repair case based upon the selected repair case, condition data received before execution of the corrective work, and the corrective work.

10. A self-repairing system as claimed claim 9, wherein the inference engine infers a new work script based upon the condition data received before execution of the corrective work and the corrective work.

11. A self-repairing system as claimed in claim 10, wherein said self-repairing system further comprises updating means for updating certain of the characteristic data based upon symbolic data provided by the conversion means, after the image-forming apparatus has been returned to the normal condition.

12. A self-repairing system as claimed in claim 11, wherein the characteristic data comprises reference value data and the interrelationship knowledge comprises mathematical model knowledge.

13. A self-repairing system as claimed in claim 12, wherein the reference value data represent desired operating ranges for parameters of the elements of the apparatus and wherein the updating means changes an original desired operating range to a new desired operating range if, after the image-forming apparatus has been returned to the normal condition, a parameter falls outside of its original desired operating range.

14. A self-repairing system as claimed in claim 4, wherein the repair plan inference means prioritizes selected repair cases on the basis of the pre-repair condition data thereof and the received condition data.

15. A self-repairing system as claimed in claim 14, wherein the repair plan inference means further prioritizes repair cases on the basis of success rates and failure rates of the cases.

16. A self-repairing system for an image-forming apparatus which includes a plurality of interrelated elements, the interrelated elements including actuator elements which control operations carried out by the image-forming apparatus, and sensor means for sensing conditions in the image-forming apparatus and providing condition data indicative thereof, said self-repairing system comprising:

memory means including;

a first memory for storing characteristic data representative of various characteristics of the image-forming apparatus, interrelationship knowledge representative of the interrelationships of the elements of the image-forming apparatus, and diagnostic knowledge,

a second memory for storing repair case knowledge, and

a third memory for storing repair work script knowledge,

diagnostic means for determining whether the image-forming apparatus is in a normal or an abnormal condition based upon condition data from the sensor means, the characteristic data from the first memory and the diagnostic knowledge from the first memory; and

a repair plan inference means, responsive to a determination by the diagnostic means that the image-forming apparatus is in an abnormal condition, for inferring a first repair plan based upon a repair case from the repair case knowledge from the second memory and a work script from the work script knowledge from the third memory, and a second repair plan in the event that the first repair plan is unsuccessful in returning the image-forming apparatus to the normal condition.

17. A self-repairing system as claimed in claim 16, wherein the repair plan inference means infers the second repair plan based upon a new repair case derived thereby.

18. A self-repairing system as claimed in claim 17, wherein the repair plan inference means infers the second repair plan based upon an inferred fault candidate, simulated fault affects, and inferred secondary affects, and thereafter registers the inferred second repair plan as a new repair case.

19. A self-repairing system as claimed in claim 18, wherein said self-repairing system further comprises updating means for updating the characteristic data based upon received condition data after the image-forming apparatus has been returned to the normal condition.

20. A self-repairing image-forming apparatus comprising:

interrelated elements including actuator elements which control operations in the image-forming apparatus;

sensor means for sensing conditions in the image-forming apparatus and providing condition data indicative thereof;

memory means including a first memory for storing image-forming apparatus characteristic data, interrelationship knowledge, and diagnostic knowledge, a second memory for storing repair case knowledge organized into repair cases, and a third memory for storing repair work script knowledge organized into work scripts;

diagnostic means for determining whether the image-forming apparatus is in a normal or an abnormal condition based upon condition data from the sensor means, the characteristic data from the first memory and the diagnostic knowledge from the first memory;

a repair plan inferring means, responsive to a determination by the diagnostic means that the image-forming apparatus is in an abnormal condition, for inferring a repair case to select one of the actuator elements for influencing one of the operations in the image-forming apparatus; and

actuator control means for controlling an actuator means selected by the inferring of a repair case by the repair plan inferring means to influence the operation.

21. A self-repairing image-forming apparatus as claimed in claim 20, comprising conversion means for converting condition data from the sensor means to symbolic data and wherein the diagnostic means determines the condition of the image-forming apparatus from symbolic data from the conversion means and the diagnostic knowledge from the first memory.

22. A self-repairing image-forming apparatus as claimed in claim 21, further comprising updating means for updating the characteristic data.

23. A self-repairing image-forming apparatus as claimed in claim 22, wherein the characteristic data comprises reference value data and the interrelationship knowledge comprises mathematical model knowledge.

24. A self-repairing method for carrying out repair of an image-forming apparatus which has a plurality of interrelated elements, the interrelated elements including actuator elements for carrying out operations in the apparatus, and memory means which stores characteristic data representative of various characteristics of the apparatus, interrelationship knowledge representative of the interrelationships of the elements of the apparatus, diagnostic knowledge, repair case knowledge, and repair work script knowledge, said method comprising the steps of:

receiving condition data indicative of the condition of the apparatus;

determining whether the apparatus is in a normal or an abnormal condition based upon the received condition data, the characteristic data and the diagnostic knowledge;

if the apparatus is in an abnormal condition, applying the repair case knowledge and the work script knowledge to infer a repair plan for influencing one of the actuator elements to change one of the operations in the apparatus.

25. A self-repairing method as claimed in claim 24, wherein said step of applying the repair case knowledge and the work script knowledge comprises the steps of:

applying the interrelationship knowledge to identify a fault cause; and

retrieving repair cases from the repair case knowledge and a repair work script from the work script knowledge which correspond with the identified fault cause.

26. A self-repairing method as claimed in claim 25,

wherein the diagnostic knowledge comprises function evaluation knowledge,

wherein said step of determining the condition of the image-forming apparatus comprises comparing the received condition data to the function evaluation knowledge to identify a fault symptom, and

wherein said step of retrieving repair cases from the repair case knowledge comprises the steps of retrieving cases which correspond with the identified fault cause and the identified fault symptom.

27. A self-repairing method as claimed in claim 26, wherein said step of retrieving repair cases from the repair case knowledge comprises the step of prioritizing the retrieved cases to obtain a highest priority repair case.

28. A self-repairing method as claimed in claim 27, wherein the repair cases each comprise a repair work index field containing repair work index data and the work scripts include repair works which are associated with the work index data, and

wherein said step of applying the repair case knowledge and the work script knowledge comprises the step of executing a repair work which is indicated by the repair work index data of the highest priority repair case and which is included in the retrieved work script.

29. A self-repairing method as claimed in claim 27, wherein the repair cases comprise a success rate field containing a success rate value and wherein, if after execution of the indicated repair work, the image-forming apparatus has been returned to its normal condition, the success rate value of the highest priority repair case is incremented.

30. A self-repairing method as claimed in claim 29, wherein the repair case comprises a failure rate field containing a failure rate value and

wherein, if after execution of the indicated repair work, the image-forming apparatus has not been returned to its normal condition, the failure rate value of the highest priority repair case is incremented and a next highest priority repair case is applied as the highest priority repair case.

31. A self-repairing method as claimed in claim 30, wherein said method comprises the steps of:

if there is not a next highest priority repair case,

inferring new repair works,

inferring secondary affects attributable to each inferred new repair work based upon the interrelationship data,

selecting a new repair work having the least inferred secondary affects from among the inferred new repair works, and

influencing the actuator element capable of changing operation of the apparatus in accordance with the selected new repair work.

32. A self-repairing method as claimed in claim 31, wherein the steps of inferring new repair works comprise the steps of inferring sequences of steps for reducing an inferred secondary affect and applying the repair plan knowledge to select a preferred sequence, and wherein the repair plan knowledge comprises knowledge that

(a) a preferred sequence must not include a step which is contradictory with a step in the selected new repair work,

(b) the preferred sequence must be inferred to have minimum further secondary affects, and

(c) the preferred sequence is aborted if a limit of an operating parameter is reached during performance of the preferred sequence.

33. A method of self-repair as claimed in claim 32, wherein if a selected new repair work fails, an alternative new repair work is selected on the basis of the next least number of inferred secondary affects.

34. A self-repairing method as claimed in claim 27, wherein the repair cases have pre-repair condition fields for containing pre-repair characteristic data, and

wherein said step of applying the repair case knowledge and the work script knowledge comprises the steps of comparing whether received condition data is the same as the pre-repair characteristic data of the highest priority repair case.

35. A self-repairing method as claimed in claim 34, wherein the repair cases have work index data fields for containing repair work index data, and the work scripts have repair works listed together with associated data representative of an antecedent condition for the work and an anticipated consequence of the work, and wherein said method comprises the steps of:

if the received condition data are the same as the pre-repair characteristic data of the highest priority repair case, executing a selected repair work indicated by the repair work index data provided by the priority repair case; and

if condition data from the sensor means are not the same as the pre-repair characteristics of the priority repair case, comparing the work antecedent data associated with the indicated repair work to received condition data which corresponds therewith, and

if the antecedent data of the indicated repair work and the corresponding received condition data are the same,

executing the indicated repair work, and

if the antecedent data and the received corresponding condition data are not the same,

determining whether the retrieved work script includes another repair work for influencing one of the actuator elements so that the corresponding received data will be the same as the antecedent data of the indicated repair work,

and if the work script includes another repair work for so influencing one of the actuator elements, executing said another repair work.

36. A self-repairing method as claimed in claim 35, wherein after said another repair work has been executed, said method comprises executing repair works listed in the retrieved repair work script according to the repair work index data provided by the highest priority repair case.

37. A self-repairing method as claimed in claim 36, comprising the steps of,

if after execution of said another repair work, the received condition data differs from the anticipated consequence of said another repair work, inferring a new repair case and a new work script.

38. A self-repairing method as claimed in claim 37, comprising the steps of converting received condition data to symbolic data.

39. A self-repairing method as claimed in claim 38, wherein the diagnostic knowledge comprises function evaluation knowledge, and wherein said step of determining whether the apparatus is in a normal or an abnormal condition comprises the steps of comparing the symbolic data with the function evaluation knowledge.

40. A self-repairing method as claimed in claim 38, wherein the characteristic data comprises reference value data and said method further comprises the step of updating the stored reference value data based upon the condition data from the sensor means after the apparatus has been returned to its normal condition.

41. A self-repairing method as claimed in claim 40, wherein the reference value data represent desired operating ranges for parameters associated with the elements of the apparatus, and said step of updating the reference value data comprises the steps of changing an original desired operating range to a new desired operating range.

42. A self-repairing method for carrying out repair of an image-forming apparatus which has a plurality of interrelated elements, the interrelated elements including actuator elements for carrying out operations in the apparatus, sensor means for sensing conditions in the apparatus and providing condition data indicative thereof, and memory means which stores characteristic data representative of various characteristics of the apparatus, interrelation knowledge representative of the interrelationships of the elements of the apparatus, diagnostic knowledge, repair case knowledge, and repair work script knowledge, said method comprising the steps of:

receiving condition data;

determining whether the apparatus is in a normal or an abnormal condition based upon the received condition data, the characteristic data and the diagnostic knowledge;

if the apparatus is in an abnormal condition, applying the repair case knowledge and the work script knowledge to infer a repair work for influencing one of the actuator elements to obtain an anticipated condition of the actuator element, and

if the inferred repair work fails to influence the actuator element to the anticipated condition, inferring new repair case knowledge based upon the applied case knowledge and work script knowledge.

43. A self-repairing method as claimed in claim 42, wherein said method comprises the step of inferring new work script knowledge.

44. A self-repairing method as claimed in claim 43, wherein said step of inferring new repair case knowledge comprises the steps of:

retrieving all repair cases from the repair case knowledge which comprise pre-repair condition data that is common to all the retrieved repair cases and that is different from received condition data which corresponds to the common pre-repair condition data.

45. A self-repairing method as claimed in claim 44, wherein said step of inferring new repair case knowledge comprises the steps of

inferring that a difference between the common pre-repair condition data and the corresponding received condition data is the reason for failure of the inferred repair work to return the image-forming apparatus to its normal condition,

locating within a work script from the applied work script knowledge a corrective work for causing the corresponding received condition data to be the same as the pre-repair condition data of one of the retrieved repair cases, and

executing the corrective work to influence one of the actuator elements.

46. A self-repairing method as claimed in claim 45, wherein said method comprises the steps,

if the corrective repair work changed the corresponding received condition data to be the same as the pre-repair condition data, inferring new repair case knowledge and new work script knowledge by registering a new repair case which includes pre-repair condition data identical to characteristic data indicative of the condition of the image-forming apparatus when the apparatus was determined to be in an abnormal condition, and repair work index data which indicate a repair plan including the corrective repair work and repair works indicated by the repair work index data of said one of the repair cases.

47. A self-repairing method as claimed in claim 42,

wherein the repair case knowledge comprises repair cases which each have pre-repair condition fields that contain pre-repair characteristic data, and the work script knowledge comprises work scripts that are associated with fault causes in the image-forming apparatus and each work script includes repair work data indicative of at least one repair work and,

wherein said step of determining the condition of the image forming apparatus comprises the step of identifying a fault symptom based upon received condition data and the diagnostic knowledge,

wherein said step of applying the repair case knowledge and the work script knowledge comprises the steps of applying the interrelationship knowledge to identify a fault cause, and retrieving repair cases that correspond with the identified fault cause and the identified fault symptom, and retrieving a work script that corresponds with the identified fault cause and,

wherein said step of inferring new repair case knowledge comprises the steps of sorting all repair cases from the retrieved cases which have pre-repair characteristic data that are common to all the retrieved cases and that differ from received condition data which corresponds with the common pre-repair characteristic data,

inferring that the reason why the inferred repair work failed to influence the actuator element according to the anticipated condition was because some of the received condition data differed from some of the common pre-repair condition data,

locating a corrective repair work in the retrieved work script, and

executing the corrective repair work to change the different received condition data to be the same as its corresponding pre-repair condition data in the sorted repair cases.

48. A self-repairing method as claimed in claim 47, wherein said method comprises the steps of if the corrective repair work failed to change the different received condition data to be the same as its corresponding pre-repair condition data, inferring that the reason why the corrective work failed was because other received condition data was different from its corresponding common pre-repair condition data.