Hierarchical methodology for productivity measurement and improvement of productions systems

• US 20040148047A1
• Filed: 12/12/2003
• Published: 07/29/2004
• Est. Priority Date: 12/18/2001
• Status: Abandoned Application

• Current Assignee: University of Toledo
• Original Assignee: University of Toledo
• Inventors: Huang, Samuel H, Dismukes, John P, Razzak, Mousalam A, wang, Ge, Su, Qi, Kothamasu, Ranganath
• Application Number:
  US10/450,863
• Publication Number:
  US 20040148047A1
• Time in Patent Office: Days
• US Class Current: 700/100
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 2219/32294 Maximize throughput of cell
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

A hierarchical method, computer system, and computer product for causelly relating productivity to a production system to provide an integrated analysis of the system which measures, monitors, analyses and, optionally, simlates performance of the production system based on a common set of productivity metrics for throughput effictiveness, cycle time effectiveness, throughput and inventory (FIG. 5, C(ma), P(m), L(in), P(a), L(out), P(out), C(md)).

Claims

1. A hierarchical method for causally relating productivity to a production system to provide an integrated productivity analysis of the system, comprising:

a) identifying an array of production operations including any one or more of the following;

process, transportation and storage;

b) modeling the system as an interconnected array of unit production processes (UPP) reflecting actual or desired material flow sequence through the system;

c) applying at least one set of UPP interconnections to factor the system into at least one set of UPP subsystems for description and analysis; and

d) assessing each UPP and each subsystem to calculate at least one productivity metric of each UPP, UPP subsystem and the system.

2. The method of claim 1, in which the UPP subsystems include any one or more of the following:

series, parallel, assembly, expansion, and complex, with rework modes applicable to each.

3. The method of claim 2, in which each UPP comprises input transport rates from an upstream UPP, and output transport rates to a downstream UPP, input and output storage buffers for work in process, and a unit process step.

4. The method of claim 1, in which algorithms are applied to calculate the productivity metrics of unit based overall equipment effectiveness (OEE), cycle time effectiveness (CTE), production throughput of good product (P_g) and UPP inventory level (L_upp), based on any one or more of the following:

factory data for equipment time parameters, theoretical cycle time, actual cycle time, arrival and departure rates, and input and output buffer levels.

5. The method of claim 1, in which algorithms are applied to calculate UPP subsystem and/or system level productivity metrics of overall throughput effectiveness (OTE_F), cycle time effectiveness (CTE_F), production throughput of good product (P_G(F)) and UPP subsystem or factory inventory level (L_F), based on factory data and the productivity metrics for each UPP.

6. The method of claim 1, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and/or production system is conducted using spreadsheet analysis tools which represent an actual factory architecture or the system.

7. The method of claim 6, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and systems is conducted using a flowchart tool and a graphical user interface for data input and metrics output in appropriate spreadsheet or chart format.

8. The method of claim 7, comprising:

creating UPPs required to represent the generic subsystem types,

creating data input and metrics output boxes for standard input and output of data and results,

linking the UPPs to represent the experimental material flow sequence, or system architecture, with recognition algorithms applied to identify generic subsystem types, and

calculating productivity metrics for each UPP, UPP subsystem, and the overall system.

9. The method of claim 8, in which the UPPs include regular, assembly and expansion.

10. The method of claim 1, further comprising building an automated simulation model comprising importing data in spreadsheet form from a flowcharting and measurement tool, and representing interconnectivity of the system and actual and theoretical performance characteristics.

11. The method of claim 10, in which the simulation model comprises a rapid what-if scenario analysis of existing production facilities or systems, wherein specific changes needed for bottleneck removal and productivity improvement are identified.

12. The method of claim 11, in which the scenario analysis is linked to market demand.

13. The method of claim 11, in which the simulation model comprises rapid assessment and development of new factory designs optimized for specific manufacturing performance.

14. The method of claim 1, wherein the UPP includes any one or more of the following:

equipment, subsystem, product line, factory, transportation system, and supply chain (which includes transportation-systems and manufacturing systems).

15. The method of claim 1, wherein measurement and analysis of the system are conducted using a spreadsheet analysis and a visual flowcharting and measurement tool coded with the algorithms for unit-based productivity measurement at the equipment, subsystem and system level.

16. The method of claim 15, wherein the measurement and analysis of the system is conducted for single and/or multiple product types.

17. The method of claim 15, wherein data representing interconnectivity of the system and intrinsic performance characteristics are transferred from the flowcharting and measurement tool via at least one or more spreadsheets to set up an equivalent manufacturing array in a discrete event simulation software package.

18. The method of claim 17, wherein development and implementation of a dynamic simulation is used to assess scenarios for eliminating bottlenecks and tailoring performance, and to develop new designs optimized for specific requirements in the production system.

19. The method of claim 17, wherein the production system includes any one or more of the following:

equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

20. The method of claim 1, wherein the method is used to analyze overall equipment effectiveness.

21. A method for hierarchical representation of a production system for measuring, monitoring, analyzing and/or simulating production performance of the production system based on a common set of productivity metrics for throughput effectiveness, cycle time effectiveness, throughput and inventory, comprising:

a) identifying an array of production operations including any one or more of the following;

process, transportation, and storage;

b) providing a description of the production system as an interconnected array of unit production processes (UPP) reflecting an actual material flow sequence through the system;

c) applying at least one set of UPP subsystems to factor an overall system flowchart into UPP subsystems, and combining the subsystems to represent the overall production system;

d) analyzing productivity metrics of each UPP, each UPP subsystem, and the overall system; and

e) converting the overall system flowchart to a discrete event simulation description, and enabling comparative performance assessment of various production scenarios useful for performance improvement and system design.

22. The method of claim 21, in which the UPP subsystems include any one or more of the following:

series, parallel, assembly, expansion, and complex, with rework modes applicable to each.

23. The method of claim 21, in which each UPP comprises input transport rates from an upstream UPP, and output transport rates to a downstream UPP, input and output storage buffers for work in process, and a unit process step.

24. The method of claim 21, in which algorithms are applied to calculate the productivity metrics of unit based overall equipment effectiveness (OEE), cycle time effectiveness (CTE), production throughput of good product (P_g) and UPP inventory level (L_upp), based on any one or more of the following:

factory data for equipment time parameters, theoretical cycle time, actual cycle time, arrival and departure rates, and input and output buffer levels.

25. The method of claim 21, in which algorithms are applied to calculate UPP subsystem and/or system level productivity metrics of overall throughput effectiveness (OTE_F), cycle time effectiveness (CTE_F), production throughput of good product (P_G(F)) and UPP subsystem or factory inventory level (L_F), based on factory data and the productivity metrics for each UPP.

26. The method of claim 21, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and/or production system is conducted using spreadsheet analysis tools which represent an actual factory architecture or the system.

27. The method of claim 26, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and systems is conducted using a flowchart tool and a graphical user interface for data input and metrics output in appropriate spreadsheet or chart format.

28. The method of claim 27, comprising:

creating UPPs required to represent the generic subsystem types,

creating data input and metrics output boxes for standard input and output of data and results,

linking the UPPs to represent the experimental material flow sequence, or system architecture, with recognition algorithms applied to identify generic subsystem types, and

calculating productivity metrics for each UPP, UPP subsystem, and the overall system.

29. The method of claim 28, in which the UPPs include regular, assembly and expansion.

30. The method of claim 21, further comprising building an automated simulation model comprising importing data in spreadsheet form from a flowcharting and measurement tool, and representing interconnectivity of the system and actual and theoretical performance characteristics.

31. The method of claim 21, in which the simulation model comprises a rapid what-if scenario analysis of existing production facilities or systems, wherein specific changes needed for bottleneck removal and productivity improvement are identified.

32. The method of claim 21, in which the scenario analysis is linked to market demand.

33. The method of claim 21, in which the simulation model comprises rapid assessment and development of new factory designs optimized for specific manufacturing performance.

34. The method of claim 21, wherein the UPP includes anyone or more of the following:

equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

35. The method of claim 21, wherein measurement and analysis of the system are conducted using a spreadsheet analysis and a visual flowcharting and measurement tool coded with the algorithms for unit-based productivity measurement, for single or multiple product types, at the equipment, subsystem and system level.

36. The method of claim 33, wherein the measurement and analysis of the system is conducted for single and multiple product types.

37. The method of claim 35, wherein data representing interconnectivity of the system and intrinsic performance characteristics are transferred from the flowcharting and measurement tool via at least one spreadsheet to set up an equivalent manufacturing array in a discrete event simulation software package.

38. The method of claim 37, wherein development and implementation of a dynamic simulation used to assess scenarios for eliminating bottlenecks and tailoring performance, and to develop new designs optimized for specific requirements in the production system.

39. The method of claim 21, wherein the production system includes any one or more of the following:

equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

40. The method of claim 21, wherein the method is used to analyze overall equipment effectiveness.

41. The method of claim 21, wherein the system layout or architecture is determined by factoring the system into unique combinations of UPP subsystems.

42. A method for analysis of system level productivity comprising:

a) establishing a unique layout or architecture for arranging at least one set of unit production processes (UPPs) in a complex system;

b) calculating overall equipment effectiveness (OEE) and, optionally, other parameters of individual UPP'"'"'s;

c) calculating overall throughput effectiveness (OTE_F) of the UPP subsystems and the system;

d) calculating good production output (P_G(F)) of the UPP subsystems and the system;

e) calculating cycle time efficiency (CTE_F) of the UPP subsystems and the system; and

f) calculating factory level inventory (L_F) of the UPP subsystems and the system.

43. The method of claim 42, wherein the system layout or architecture is determined by factoring the complex system into unique combinations of UPP subsystems.

44. The method of claim 42, in which the UPP subsystems include any one or more of the following:

series, parallel, assembly, expansion, and complex, with rework modes applicable to each.

45. The method of claim 42, in which each UPP comprises input transport rates from an upstream UPP, and output transport rates to a downstream UPP, input and output storage buffers for work in process, and a unit process step.

46. The method of claim 42, in which algorithms are applied to calculate the productivity metrics of unit based overall equipment effectiveness (OEE), cycle time effectiveness (CTE), production throughput of good product (P_g) and UPP inventory level (L_upp), based on any one or more of the following:

factory data for equipment time parameters, theoretical cycle time, actual cycle time, arrival and departure rates, and input and output buffer levels.

47. The method of claim 42, in which algorithms are applied to calculate UPP subsystem and/or system level productivity metrics of overall throughput effectiveness (OTE_F), cycle time effectiveness (CTE_F), production throughput of good product (P_G(F)) and UPP subsystem or factory inventory level (L_F), based on factory data and the productivity metrics for each UPP.

48. The method of claim 42, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and/or production system is conducted using spreadsheet analysis tools which represent an actual factory architecture or the system.

49. The method of claim 48, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and systems is conducted using a flowchart tool and a graphical user interface for data input and metrics output in appropriate spreadsheet or chart format.

50. The method of claim 49, comprising:

creating UPPs required to represent the generic subsystem types,

creating data input and metrics output boxes for standard input and output of data and results,

linking the UPPS to represent the experimental material flow sequence, or system architecture, with recognition algorithms applied to identify generic subsystem types, and

calculating productivity metrics for each UPP, UPP subsystem, and the overall system.

51. The method of claim 50, in which the UPPs include regular, assembly and expansion.

52. The method of claim 42, further comprising building an automated simulation model comprising importing data in spreadsheet form from a flowcharting and measurement tool, and representing interconnectivity of the system and actual and theoretical performance characteristics.

53. The method of claim 42, in which the simulation model comprises a rapid what-if scenario analysis of existing production facilities or, systems, wherein specific changes needed for bottleneck removal and productivity improvement are identified.

54. The method of claim 42, in which the scenario analysis is linked to market demand.

55. The method of claim 42, in which the simulation model comprises rapid assessment and development of new factory designs optimized for specific manufacturing performance.

56. The method of claim 42, wherein the UPP includes any one or more of the following equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

57. The method of claim 42, wherein measurement and analysis of the system are conducted using a spreadsheet analysis and a visual flowcharting and measurement tool coded with the algorithms for unit-based productivity measurement at the equipment, subsystem and system level.

58. The method of claim 42, wherein the measurement and analysis of the system is conducted for single and/or multiple product types.

59. The method of claim 57, wherein data representing interconnectivity of the system and intrinsic performance characteristics are transferred from the flowcharting and measurement tool via at least one or more spreadsheets to set up an equivalent manufacturing array in a discrete event simulation software package.

60. The method of claim 59, wherein development and implementation of a dynamic simulation is used to assess scenarios for eliminating bottlenecks and tailoring performance, and to develop new designs optimized for specific requirements in the production system.

61. The method of claim 42, wherein the production system includes any one or more of the following:

equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

62. The method of claim 42, wherein the method is used to analyze overall equipment effectiveness.

63. The method of claim 42, wherein the system layout or architecture is determined by factoring the system into unique combinations of UPP subsystems.

64. A computer system for relating productivity to a production system to provide an integrated productivity analysis of the system comprising:

a) identifying an array of production operations including any one or more of the following;

process, transportation and storage;

b) modeling the system as an interconnected array of unit production processes (UPP) reflecting actual or desired material flow sequence through the system;

c) applying at least one set of UPP interconnections to factor the system into at least one set of UPP subsystems for description and analysis; and

d) assessing each UPP and each subsystem to calculate at least one productivity metric of each UPP, UPP subsystem and the system.

65. A computer system of claim 64, in which the UPP subsystems include any one or more of the following:

series, parallel, assembly, expansion, and complex, with rework modes applicable to each.

66. A computer system of claim 64, in which each UPP comprises input transport rates from an upstream UPP, and output transport rates to a downstream UPP, input and output storage buffers for work in process, and a unit process step.

67. A computer system of claim 64, in which algorithms are applied to calculate the productivity metrics of unit based overall equipment effectiveness (OEE), cycle time effectiveness (CTE), production throughput of good product (P_g) and UPP inventory level (L_upp) based on any one or more of the following:

factory data for equipment time parameters, theoretical cycle time, actual cycle time, arrival and departure rates, and input and output buffer levels.

68. A computer system of claim 64, in which algorithms are applied to calculate UPP subsystem and/or system level productivity metrics of overall throughput effectiveness (OTE_F), cycle time effectiveness (CTE_F), production throughput of good product (P_G(F)) and UPP subsystem or factory inventory level (L_F), based on factory data and the productivity metrics for each UPP.

69. A computer system of claim 64, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and/or production system is conducted using spreadsheet analysis tools which represent an actual factory architecture or the system.

70. A computer system of claim 64, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and systems is conducted using a flowchart tool and a graphical user interface for data input and metrics output in appropriate spreadsheet or chart format.

71. A computer system of claim 70, comprising:

creating UPPs required to represent the generic subsystem types,

creating data input and metrics output boxes for standard input and output of data and results,

linking the UPPs to represent the experimental material flow sequence, or system architecture, with recognition algorithms applied to identify the generic subsystem types, and

calculating productivity metrics for each UPP, UPP subsystem, and the overall system.

72. A computer system of claim 71, in which the UPPs include regular, assembly and expansion.

73. A computer system of claim 64, further comprising building an automated simulation model comprising importing data in spreadsheet form from a flowcharting and measurement tool, and representing interconnectivity of the system and actual and theoretical performance characteristics.

74. A computer system of claim 64, in which the simulation model comprises a rapid what-if scenario analysis of existing production facilities or systems, wherein specific changes needed for bottleneck removal and productivity improvement are identified.

75. A computer system of claim 64, in which the scenario analysis is linked to market demand.

76. A computer system of claim 64, in which the simulation model comprises rapid assessment and development of new factory designs optimized for specific manufacturing performance.

77. A computer system of claim 64, wherein the UPP includes any one or more of the following:

equipment, subsystem, product line, manufacturing process,, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

78. A computer system of claim 64, wherein measurement and analysis of the system are conducted using a spreadsheet analysis and a visual flowcharting and measurement tool coded with the algorithms for unit-based productivity measurement at the equipment, subsystem and system level.

79. A computer system of claim 78, wherein the measurement and analysis of the system is conducted for single and/or multiple product types.

80. A computer system of claim 64, wherein data representing interconnectivity of the system and intrinsic performance characteristics are transferred from the flowcharting and measurement tool via at least one or more appropriate spreadsheets to set up an equivalent manufacturing array in a discrete event simulation software package.

81. A computer system of claim 80, wherein development and implementation of a dynamic simulation is used to assess scenarios for eliminating bottlenecks and tailoring performance, and to develop new designs optimized for specific requirements in the production system.

82. A computer system of claim 64, wherein the production system includes any one or more of the following:

equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

83. A computer system of claim 64, wherein the method is used to analyze overall equipment effectiveness.

84. A computer system for hierarchical representation of a production system for measuring, monitoring, analyzing and/or simulating production performance of the production system based on a common set of productivity metrics for throughput effectiveness, cycle time effectiveness, throughput and inventory, comprising:

a) identifying an array of production operations including any one or more of the following;

process, transportation, and storage;

.

b) providing a description of the production system as an interconnected array of unit production processes (UPP) reflecting an actual material flow sequence through the system;

c) applying at least one set of UPP subsystems to factor an overall system flowchart into UPP subsystems, and combining the subsystems to represent the overall production system;

d) analyzing productivity metrics of each UPP, each UPP subsystem, and the overall system; and

e) converting the flowchart to a discrete event simulation description, and enabling comparative performance assessment of various production scenarios useful for performance improvement and system design.

85. A computer program product comprising a program storage device readable by a computer system tangibly embodying a program of instructions executed by the computer system to perform in a process for causally relating productivity to a production system, the process comprising:

a) identifying an array of production operations including any one or more of the following;

process, transportation and storage;

b) modeling the system as an interconnected array of unit production processes (UPP) reflecting actual or desired material flow sequence through the system;

c) applying at least one set of UPP interconnections to factor the system into at least one set of UPP subsystems for description and analysis; and

d) assessing each UPP and each subsystem type to calculate at least one productivity metric of each UPP, UPP subsystem and the system.

86. The method of claim 85, in which the UPP subsystems include any one or more of the following:

series, parallel, assembly, expansion, and complex, with rework modes applicable to each.

87. The method of claim 85, in which each UPP comprises input transport rates from an upstream UPP, and output transport rates to a downstream UPP, input and output storage buffers for work in process, and a unit process step.

88. The method of claim 85, in which algorithms are applied to calculate the productivity metrics of unit based overall equipment effectiveness (OEE), cycle time effectiveness (CTE), production throughput of good product (P_g) and UPP inventory level (L_upp), based on any one or more of the following:

factory data for equipment time parameters, theoretical cycle time, actual cycle time, arrival and departure rates, and input and output buffer levels.

89. The method of claim 85, in which algorithms are applied to calculate UPP subsystem and/or system level productivity metrics of overall throughput effectiveness (OTE_F), cycle time effectiveness (CTE_F), production throughput of good product (P_G(F)) and UPP subsystem or factory inventory level (L_F), based on factory data and the productivity metrics for each UPP.

90. The method of claim 85, in which measurement, monitoring and quantitative calculation of the productivity metrics for the UPPs, the UPP subsystems, and/or production system is conducted using spreadsheet analysis tools which represent an actual factory architecture or the system.

91. The method of claim 85, in which measurement, monitoring and quantitative calculation of the metrics for the UPPS, the UPP subsystems, and systems is conducted using a flowchart tool and a graphical user interface for data input and metrics output in appropriate spreadsheet or chart format.

92. The method of claim 91, comprising:

creating UPPs required to represent the generic subsystem types,

creating data input and metrics output boxes for standard input and output of data and results,

linking the UPPs to represent the experimental material flow sequence, or system architecture, with recognition algorithms applied to identify the generic subsystem types, and

calculating productivity metrics for each UPP, UPP subsystem, and the overall system.

93. The method of claim 92, in which the UPPs include regular, assembly and expansion.

94. The method of claim 85, further comprising building an automated simulation model comprising importing data in spreadsheet form from a flowcharting and measurement tool, and representing interconnectivity of the system and actual and theoretical performance characteristics.

95. The method of claim 85, in which the simulation model comprises a rapid what-if scenario analysis of existing production facilities or systems, wherein specific changes needed for bottleneck removal and productivity improvement are identified.

96. The method of claim 85, in which the scenario analysis is linked to market demand.

97. The method of claim 85, in which the simulation model comprises rapid assessment and development of new factory designs optimized for specific manufacturing performance.

98. The method of claim 85, wherein the UPP includes any one or more of the following:

equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

99. A computer program of claim 85, wherein measurement and analysis of the system are conducted using a spreadsheet analysis and a visual flowcharting and measurement tool coded with the algorithms for unit-based productivity measurement at the equipment, subsystem and system level.

100. The method of claim 99, wherein the measurement and analysis of the system is conducted for single and/or multiple product types.

101. A computer program of claim 99, wherein data representing interconnectivity of the system and intrinsic performance characteristics are transferred from the flowcharting and measurement tool via at least one or more spreadsheets to set up an equivalent manufacturing array in a discrete event simulation software package.

102. A computer program of claim 101, wherein development and implementation of a dynamic simulation is used to assess scenarios for eliminating bottlenecks and tailoring performance, and to develop new designs optimized for specific requirements in the production system.

103. A computer program of claim 85, wherein the production system includes any one or more of the following:

equipment, subsystem, product line, manufacturing process, factory, transportation system, and supply chains (which includes transportation systems and manufacturing systems).

104. A computer program of claim 85, wherein the method used to analyze overall equipment effectiveness.