Integration assisting system and method

• US 7,120,517 B2
• Filed: 01/02/2001
• Issued: 10/10/2006
• Est. Priority Date: 01/02/2001
• Status: Expired due to Fees

• Current Assignee: Avraham Friedman
• Original Assignee: Avraham Friedman
• Inventors: Friedman, Avraham
• Primary Examiner(s): Black, Thomas G.
• Assistant Examiner(s): Marc, McDieunel
• Application Number:
  US10/250,549
• Publication Number:
  US 20050033477A1
• Time in Patent Office: 2,107 Days
• Field of Search: 700/245, 700/250, 700/264, 318/568.12
• US Class Current: 700/245
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

A self-intelligent component-based robotics system wherein at (202), system (100) is assembled. At (204) an optimal self configuration process is performed. At (206) a user inputs into the system a “system image” which represents one or more functions expected from the system. At (208) calibration is performed. Once calibration is completed, system 100 is being used at (210).

Claims

1. A self-predicting system, comprising:

a plurality of robotics components;

a memory staring therein a system configuration map; and

an input for a command to the system; and

a controller that receives at least one command from said input and that analyzes said command in view of said map, to predict a possible failure mode of the robotics system;

wherein said controller determines said failure mode based on at least one of initial speed final speed and acceleration of at least one of said components.

2. A system according to claim 1, wherein said controller comprises a database of failure scenarios and wherein said controller utilizes said database for said analysis.

3. A system according to claim 1, wherein said controller comprises a database of experience, learned by said controller in the use of said system and wherein said controller utilizes said database for said prediction.

4. A system according to claim 1, wherein said controller is a centralized component.

5. A system according to claim 1, wherein said controller comprises a plurality of controller components distributed between at least some of said components.

6. A self-predicting system, comprising:

a plurality of robotics components;

a memory storing therein a system configuration map; and

an input for a command to the system; and

a controller that receives at least one command from said input and tat analyzes said command in view of said map, to predict a possible failure mode of the systeim system;

wherein said controller determines said failure mode based on at least one of initial speed, final speed and acceleration of at least one of said components.

7. A system according to claim 6, wherein said controller comprises a database of failure scenarios and wherein said controller utilizes said database for said analysis.

8. A system according to claim 6, wherein said controller comprises a database of experience, learned by said controller in the use of said system and wherein said controller utilizes said database for said prediction.

9. A system according to claim 6, wherein said controller is a centralized component.

10. A system according to claim 6, wherein said controller comprises a plurality of controller components distributed between at least some of said components.

11. A system according to claim 6 wherein said input is a command from a user for the system to perform an act.