Dynamic maintenance plan for an industrial robot

• US 8,185,346 B2
• Filed: 03/03/2008
• Issued: 05/22/2012
• Est. Priority Date: 03/02/2007
• Status: Active Grant

• Current Assignee: ABB Schweiz AG (ABB Limited)
• Original Assignee: ABB Research Ltd. (ABB Limited)
• Inventors: Sjöstrand, Niclas, Blanc, Dominique, Lindin, Anders
• Primary Examiner(s): Huynh, Phuong
• Application Number:
  US12/073,225
• Publication Number:
  US 20080228314A1
• Time in Patent Office: 1,541 Days
• Field of Search: 702175-189, 702/113, 702118-123
• US Class Current: 702/175
• CPC Class Codes: G05B 2219/32226 Computer assisted repair, maintenance of system components
• CPC Class Codes: G05B 2219/32233 Scheduling repair
• CPC Class Codes: G05B 2219/32234 Maintenance planning
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

A method for establishing a dynamic maintenance scheduling tool for a specific part of a machinery based on condensed prior knowledge of the part of the machinery in a population of machineries. The scheduling tool is in turn used in a method for establishing a dynamic maintenance schedule for a specific part of a specific machinery, wherein parameters related to the usage, including relevant parameters representing factors influencing the lifetime of the specific parts, are utilized as input data to the dynamic maintenance scheduling tool for the specific part of the machinery, whereupon a dynamic maintenance schedule for the specific part of the specific machinery is achieved as output data from the scheduling tool. The method is in particular dedicated to industrial robot systems.

Claims

1. A method in a maintenance scheduling tool implemented in a computer system for generating a dynamic maintenance schedule for a part of a machinery, the method comprising:

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part, and

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

wherein said estimating replacement time for said selected part comprises;

performing a multiple linear regression based on data for failure times, failure information and costs for preventive replacement of said selected part for stating said part'"'"'s function probability and using said function probability for estimating an optimal time for replacing the part, and

performing, using a computer, an estimation of replacement time of the part based on collected information of the lifetime intervals and replacement times for said part.

2. The method according to claim 1, further comprising:

evaluating a quality of said estimation of replacement time for said selected part based on verified collected information on prior knowledge about replacement times for said selected part.

3. The method according to claim 1, wherein said selecting a critical part comprises at least one of:

an analysis of statistical data based on collected information of parts that usually break down and parts that are replaced to increase a function possibility,

an analysis based on spare part sale, and

a Weibull analysis performed on failure data of critical parts of the machinery.

4. The method according to claim 1, wherein said identifying influence factors comprises at least one of:

performing a multiple linear regression analysis on lifetimes and different factors impact on the lifetimes of said machinery part resulting in said identification of the influence factors for the part and a graduation of the impact of said identified influence factors, and

performing a graduation of said influence factors impact on the lifetime of said selected critical part based on statistical information extracted from experience and knowledge among men skilled in the art if no failure information is available for said selected critical part.

5. The method according to claim 2, wherein said evaluating the quality of said estimation of replacement time for said selected part comprises at least one of:

reviewing lifetime and replacement time according to collected information of the lifetime intervals and replacement times for said selected part, and

reviewing complete failure information, with respect to the specific critical part and performing a validation and verification of estimated replacement times by use of statistical data related to said critical part collected from responsible managers or field service engineers.

6. The method according to claim 1, wherein a process of establishing a full dynamic cost optimized maintenance scheduling tool for said part of the machinery comprises:

selecting a critical part,

performing a multiple linear regression based on data for failure times, failure information and costs for preventive replacement of said selected part for stating a function probability of the part and a cost analysis estimating the optimal time for replacing the part,

performing a review with schedules for the usage of the part, and

creating a tool enabling a user to fill out set up values as a percentage of the maximum values of the influence factors for said specific part for a robot and generating a maintenance schedule for said specific part based on the usage of the robot and the costs for the replacement taken into account.

7. The method according to claim 6, wherein said generation of a full dynamic maintenance scheduling tool further comprises:

updating replacement time, influence factors and cost optimized maintenance based on recent recorded failure information for the part.

8. The method according to claim 3, wherein generation of a simplified dynamic maintenance scheduling tool comprises:

selecting a critical part,

estimating the replacement time for the part based on experience and knowledge among men skilled in the art of industrial robots, and

generating a dynamic scheduling tool based on factors influencing the lifetime of the part and on the usage of the part.

9. The method according to claim 8, wherein said generation of a simplified dynamic maintenance scheduling tool further comprises:

updating replacement time and influence factors based on recent recorded failure information for the part.

10. The method according to claim 1, wherein said maintenance scheduling tool implemented in said computer system generates said dynamic maintenance schedule for a specific part of a specific machinery, further comprising:

inputting data into said dynamic maintenance scheduling tool, wherein said data are parameters related to the usage, including relevant parameters representing factors influencing the lifetime of said specific part, and

outputting from said dynamic maintenance scheduling tool a dynamic maintenance schedule for said specific part of said specific part of the machinery.

11. The method for establishing a dynamic maintenance schedule for a specific machinery individual according to claim 10, further comprising:

identifying the specific parts relevant for said maintenance schedule,

performing said dynamic maintenance schedule for each said relevant part of the machinery, and

compiling the obtained dynamic maintenance schedule for each said relevant part into a complete dynamic maintenance schedule for the machinery individual.

12. The method for establishing a dynamic maintenance schedule for a population of specific machinery individuals according to claim 10, further comprising:

identifying the specific parts relevant for said maintenance schedule of said population of specific machinery individuals,

performing said dynamic maintenance schedule for each said relevant part of said population, and

compiling the obtained dynamic maintenance schedule for each said relevant part into a complete dynamic maintenance schedule for said population of specific machinery individuals.

13. A computer program product, comprising:

a non-transitory computer readable containing computer instructions stored thereon for causing a computer processor to perform a method in a maintenance schedule tool for generating a dynamic maintenance schedule for a part of a machinery, the method comprising

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part, and

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

wherein said estimating replacement time for said selected part comprises;

performing a multiple linear regression based on data for failure times, failure information and costs for preventive replacement of said selected part for stating said part'"'"'s function probability and using said function probability for estimating an optimal time for replacing the part, and

performing an estimation of replacement time of the part based on collected information of the lifetime intervals and replacement times for said part.

14. A dynamic maintenance scheduling tool, comprising:

the computer program product comprising;

a non-transitory computer readable containing computer instructions stored thereon for causing a computer processor to perform a method in a maintenance schedule tool for generating a dynamic maintenance schedule for a part of a machinery, the method comprising

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part, and

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

wherein said estimating replacement time for said selected part comprises;

performing a multiple linear regression based on data for failure times, failure information and costs for preventive replacement of said selected part for stating said part'"'"'s function probability and using said function probability for estimating an optimal time for replacing the part, and

performing an estimation of replacement time of the part based on collected information of the lifetime intervals and replacement times for said part, and

a database for storing data associated with the machineries, as well as information necessary for performing the processing of the tool, said database being accessible by the computer program processing said dynamic maintenance scheduling tool.

15. A system, comprising:

a computer program product comprising;

a non-transitory computer readable containing computer instructions stored thereon for causing a computer processor to perform a method in a maintenance schedule tool for generating a dynamic maintenance schedule for a part of a machinery, the method comprising

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part, and

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

wherein said estimating replacement time for said selected part comprises;

performing a multiple linear regression based on data for failure times, failure information and costs for preventive replacement of said selected part for stating said part'"'"'s function probability and using said function probability for estimating an optimal time for replacing the part, and

performing an estimation of replacement time of the part based on collected information of the lifetime intervals and replacement times for said part;

a database for storing data associated with the machineries, as well as information necessary for performing the processing of the tool, said database being accessible by the computer program processing said dynamic maintenance scheduling tool; and

a computer for executing the computer instructions.

16. A method in a maintenance scheduling tool implemented in a computer system for generating a dynamic maintenance schedule for a part of a machinery, the method comprising:

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part, and

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

wherein said identifying influence factors comprises;

performing a multiple linear regression analysis on lifetimes and different factors impact on the lifetimes of said machinery part resulting in said identification of the influence factors for the part and a graduation of the impact of said identified influence factors, and

performing, using a computer, a graduation of said influence factors impact on the lifetime of said selected critical part based on statistical information extracted from experience and knowledge among men skilled in the art if no failure information is available for said selected critical part.

17. A method in a maintenance scheduling tool implemented in a computer system for generating a dynamic maintenance schedule for a part of a machinery, the method comprising:

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part,

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time, and

evaluating a quality of said estimation of replacement time for said selected part based on

verified collected information on prior knowledge about replacement times for said selected part,

wherein said evaluating the quality of said estimation of replacement time for said selected part comprises;

reviewing lifetime and replacement time according to collected information of the lifetime intervals and replacement times for said selected part, and

reviewing, using a computer, complete failure information, with respect to the specific critical part and performing a validation and verification of estimated replacement times by use of statistical data related to said critical part collected from responsible managers or field service engineers.

18. A method in a maintenance scheduling tool implemented in a computer system for generating a dynamic maintenance schedule for a part of a machinery, the method comprising:

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part, and

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

wherein a process of establishing a full dynamic cost optimized maintenance scheduling tool for said part of the machinery comprises;

selecting a critical part,

performing a multiple linear regression based on data for failure times, failure information and costs for preventive replacement of said selected part for stating a function probability of the part and a cost analysis estimating the optimal time for replacing the part,

performing a review with schedules for the usage of the part, and

creating, using a computer, a tool enabling a user to fill out set up values as a percentage of the maximum values of the influence factors for said specific part for a robot and generating a maintenance schedule for said specific part based on the usage of the robot and the costs for the replacement taken into account.

19. The method according to claim 18, wherein said generation of a full dynamic maintenance scheduling tool further comprises:

updating replacement time, influence factors and cost optimized maintenance based on recent recorded failure information for the part.

20. A method in a maintenance scheduling tool implemented in a computer system for generating a dynamic maintenance schedule for a part of a machinery, the method comprising:

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part, and

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

wherein said selecting a critical part comprises;

an analysis of statistical data based on collected information of parts that usually break down and parts that are replaced to increase a function possibility,

an analysis based on spare part sale, and

a Weibull analysis performed on failure data of critical parts of the machinery, and

wherein generation of a simplified dynamic maintenance scheduling tool comprises;

selecting a critical part,

estimating the replacement time for the part based on experience and knowledge among men skilled in the art of industrial robots, and

generating, using a computer, a dynamic scheduling tool based on factors influencing the lifetime of the part and on the usage of the part.

21. The method according to claim 20, wherein said generation of a simplified dynamic maintenance scheduling tool further comprises:

updating replacement time and influence factors based on recent recorded failure information for the part.

22. A method in a maintenance scheduling tool implemented in a computer system for generating a dynamic maintenance schedule for a part of a machinery, the method comprising:

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part,

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

inputting data into said dynamic maintenance scheduling tool, wherein said data are parameters related to the usage, including relevant parameters representing factors influencing the lifetime of said specific part,

outputting from said dynamic maintenance scheduling tool a dynamic maintenance schedule for said specific part of said specific part of the machinery,

identifying the specific parts relevant for said maintenance schedule,

performing said dynamic maintenance schedule for each said relevant part of the machinery, and

compiling, using a computer, the obtained dynamic maintenance schedule for each said relevant part into a complete dynamic maintenance schedule for the machinery individual.

23. A method in a maintenance scheduling tool implemented in a computer system for generating a dynamic maintenance schedule for a part of a machinery, the method comprising:

selecting a critical part of the machinery,

identifying influence factors having influence on a lifetime of said selected part,

estimating replacement time for said selected part,

creating said maintenance schedule for said part of the machinery based on said identification of the influence factors and said estimated replacement time,

inputting data into said dynamic maintenance scheduling tool, wherein said data are parameters related to the usage, including relevant parameters representing factors influencing the lifetime of said specific part,

outputting from said dynamic maintenance scheduling tool a dynamic maintenance schedule for said specific part of said specific part of the machinery,

identifying the specific parts relevant for said maintenance schedule of a population of specific machinery individuals,

performing said dynamic maintenance schedule for each said relevant part of said population, and

compiling, using a computer, the obtained dynamic maintenance schedule for each said relevant part into a complete dynamic maintenance schedule for said population of specific machinery individuals.