Method for optimizing configuration of pick-and-place machine

• US 7,076,313 B2
• Filed: 06/06/2003
• Issued: 07/11/2006
• Est. Priority Date: 06/06/2003
• Status: Expired due to Fees

• Current Assignee: Visteon Global Technologies Incorporated (Visteon Corporation)
• Original Assignee: Visteon Global Technologies Incorporated (Visteon Corporation)
• Inventors: Welch, Kurt D.
• Primary Examiner(s): Paladini, Albert W.
• Assistant Examiner(s): Lee, Douglas S.
• Application Number:
  US10/456,263
• Publication Number:
  US 20040249492A1
• Time in Patent Office: 1,131 Days
• Field of Search: 700/28, 700/48, 700/97, 700/103, 700/121, 706/13, 706/14, 706/25, 706/62
• US Class Current: 700/28
• CPC Class Codes: B25J 9/1664 characterised by motion, path, trajectory planning
• CPC Class Codes: G05B 2219/40384 Optimize teached path by data acquisition followed by genetic algorithm
• CPC Class Codes: G05B 2219/40463 Shortest distance in time, or metric, time optimal
• CPC Class Codes: G05B 2219/45063 Pick and place manipulator
• CPC Class Codes: Y10T 29/5313 Means to assemble electrical device

Abstract

A method for optimizing the configuration of a pick-and-place machine utilizes a genetic algorithm that creates an initial population of possible configurations and selects an optimum configuration based upon lowest cycle time. The method then creates a next generation by selecting possible configurations from the prior generation and randomly mutating instructions. The method compares the mutated configuration having the lowest cycle time from the next generation and the configuration having the lowest cycle time from the prior generation, and selects the optimum configuration. The steps are repeated to evaluate additional generations of mutated configurations. After several mutated generations have been evaluated, the method creates a new initial population and evaluates the new initial population and mutated generations derived therefrom, compares the optimum configuration from the new initial populations with the optimum configuration from the prior initial population, and selects the optimum configuration. In this manner, the method may evaluate several initial populations and mutated generations therefrom in selecting the optimum configuration for use in operating the machine.

Claims

1. A method of optimizing a configuration of a pick-and-place machine comprising a plurality of placement devices, said configuration comprising a series of instructions that direct each placement device to pick up one of a plurality of electronic components at one of a plurality of feeders and place the component at a designated location on a substrate, said method comprising:

(a) creating an initial population of possible configurations to be a first generation,

(b) estimating cycle time for each possible configuration and selecting the possible configuration having a lowest estimated cycle time as an optimum configuration;

(c) creating a next generation of possible configurations by selecting the optimum configuration and certain possible configurations from the prior generation;

(d) randomly mutating at least one instruction of all the possible configurations of the next generation;

(e) estimating cycle time for each possible configuration of the next population,

(f.1) comparing the cycle time of the possible configuration of the next generation after mutation having the lowest cycle time with the cycle time of the optimum configuration, and of these two configurations selecting the configuration having the lower cycle time as an updated optimum configuration;

(f.2) setting the next generation after mutation as the prior generation;

(g) repeating steps (c) through (f.2) at least one time; and

(h) selecting the updated optimum configuration for use in operating the pick-and-place machine.

2. A method in accordance with claim 1 wherein the step of creating a next generation comprises selecting certain possible configurations from the prior generation based upon a fitness probability.

3. A method in accordance with claim 2 wherein the fitness probability is based upon a fitness factor determined by a standard deviation in individual cycle times of the placement devices.

4. A method in accordance with claim 1 wherein the step of mutating at least one instruction of the possible configuration comprises randomly selecting an instruction that directs a particular placement device to pick up a particular component, and directing a different placement device to pick up the particular component.

5. A method in accordance with claim 1 wherein the step of mutating at least one instruction of the possible configuration comprises randomly selecting an instruction that directs a particular placement device to pick up a particular component at a particular time, and directing the particular placement device to pick up the particular component at a different time.

6. A method in accordance with claim 1 wherein the possible configuration comprises a feeder set up, and wherein the step of mutating the possible configuration comprises changing the feeder set up.

7. A method in accordance with claim 1 wherein the step of creating the next generation includes selecting a new optimum configuration.

8. A method in accordance with claim 1 further comprising, following a predetermined stop event, creating a new initial population;

repeating steps (b) through (h); and

selecting a final optimum configuration in step (i) from the optimum configurations derived from the prior initial population and the new initial population.

9. A method in accordance with claim 2 wherein the fitness probability is determined by, for each possible configuration, calculating individual cycle times for the possible devices, determining a fitness actor based upon a standard deviation for the cycle times, squaring the difference between the fitness factor of each possible configuration and the highest fitness factor for the prior generation;

and randomly selecting possible configurations for the next generation based upon the squared difference.

10. A method in accordance with claim 1 wherein the step of mutating at least one instruction of the possible configuration comprises at least one of

(a) randomly selecting an instruction that directs a particular placement device to pick up a particular component, and selecting a different placement device to pick up the particular component;

(b) randomly selecting an instruction that directs a particular placement device to pick up a particular component at a particular time, and selecting a different time, or

(c) randomly changing the feeder set up.