Computer-implemented product development planning method

• US 6,233,493 B1
• Filed: 09/16/1998
• Issued: 05/15/2001
• Est. Priority Date: 09/16/1998
• Status: Expired due to Term

• Current Assignee: JDA Software Group Incorporated (Panasonic Holdings Corporation)
• Original Assignee: i2 Technologies Incorporated (Panasonic Holdings Corporation)
• Inventors: Kumar, Krishna, Cherneff, Jonathan M.
• Primary Examiner(s): Millin, Vincent
• Assistant Examiner(s): Nguyen, Cuong H.
• Application Number:
  US09/154,373
• Time in Patent Office: 972 Days
• Field of Search: 705/7-8, 700/213, 706/13-14, 706/10, 703/2, 703/14
• US Class Current: 700/95
• 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 computer-implemented system (10) for product development planning. The system (10) models a business enterprise in terms of its proposed products and the tasks and resources used to develop them. A optimizing engine comprised of a genetic algorithm (13) and a constraint engine (14) operates on the model to construct candidate product portfolios and schedules. Each schedule is evaluated and used to generate an “improved” candidate portfolio in accordance with genetic processing. This process continues to improve the product prioritization and pipeline schedule as measured in terms of an objective criterion such as profit maximization.

Claims

1. A computer system for modeling product development, comprising:

a plurality of product models defined from a product model type and stored by the computer system, each product model representing a product proposed to be manufactured by an enterprise;

a plurality of component models defined from a component model type and stored by the computer system, each component model representing a component from which a product is made;

a plurality of task models defined from a task model type and stored by the computer system, each task model representing a task to be performed in the development of a component;

a plurality of resource models defined from a resource model type and stored by the computer system, each resource model representing a resource available for use in performing a task;

at least one pipeline view that represents a set of tasks and assigned resources for producing a set of products; and

at least one product portfolio view that represents a set of the products.

2. The system of claim 1, further comprising a genetic algorithm for providing candidate portfolios for the portfolio view.

3. The system of claim 2, wherein chromosomes of the genetic algorithm represent potential product sequences.

4. The system of claim 1, further comprising a constraint engine for building candidate schedules for the pipeline view, wherein the constraint engine builds the schedules subject to constraints associated with the model.

5. The system of claim 4, wherein the constraint engine evaluates each schedule with a score based on whether the constraints are violated.

6. The system of claim 1, wherein the portfolio view provides financial measures associated with a portfolio.

7. The system of claim 1, wherein the task model type comprises a resource alternative attribute representing alternative resources for performing a task.

8. The system of claim 1, wherein the component model type comprises a task network attribute representing the tasks for providing a component.

9. The system of claim 1, wherein the resource model type comprises a capacity attribute representing rules for allocating resources to tasks.

10. A product development planning system, comprising:

an optimizing engine having a genetic algorithm and a constraint engine;

an enterprise model having at least the following components;

a plurality of product models defined from a product model type and stored by the computer system, each product model representing a product proposed to be manufactured by an enterprise;

a plurality of component models defined from a component model type and stored by the computer system, each component model representing a component from which a product is made;

a plurality of task models defined from a task model type and stored by the computer system, each task model representing a task to be performed in the development of a component;

a plurality of resource models defined from a resource model type and stored by the computer system, each resource model representing a resource available for use in performing a task;

at least one pipeline view representing a set of tasks and assigned resources for producing a set of products; and

at least one product portfolio view representing a set of the products;

the genetic algorithm is operable to provide sequences of products as candidates for the portfolio view;

the constraint engine being operable to provide schedules for the sequences subject to constraints of the enterprise model; and

the genetic algorithm and the constraint engine being operable to cooperate to evaluate the sequences in terms of constraint violations and to improve the sequences, thereby providing the portfolio view and the pipeline view.

11. The system of claim 10, wherein the optimizing engine is operable to respond to variations in the model input by a user, by modifying the portfolio view as incrementally affected by the variation.

12. The system of claim 10, wherein chromosomes of the genetic algorithm represent potential product priorities.

13. The system of claim 10, wherein the constraint engine evaluates each schedule with a score based on whether the constraints are violated.

14. The system of claim 10, wherein the portfolio view provides financial measures associated with the portfolio.

15. The system of claim 10, wherein the task models further represent resource alternatives for performing tasks.

16. The system of claim 10, wherein the component model type has a task network attribute representing the tasks for providing a component.

17. The system of claim 10, wherein the sequences are evaluated such that profit from the sequence is maximized.

18. The system of claim 10, further comprising a presentation layer for providing displays of the views and the model.

19. The system of claim 10, wherein the resource model type has a capacity attribute representing rules for allocating resources to tasks.

20. A method for product development planning, comprising:

modeling an enterprise with an enterprise model having at least the following components;

a plurality of product models defined from a product model type and stored by the computer system, each product model representing a product proposed to be manufactured by the enterprise;

a plurality of component models defined from a component model type and stored by the computer system, each component model representing a component from which a product is made;

a plurality of task models defined from a task model type and stored by the computer system, each task model representing a task to be performed in the development of a component; and

a plurality of resource models defined from a resource model type and stored by the computer system, each resource model representing a resource available for use in performing a task and rules for allocating the resource to the task;

selecting a sequence of the products as a candidate portfolio;

building a schedule for the sequence using a constraint engine that builds the schedule subject to constraints of the model;

evaluating the sequence in terms of violations of the constraints;

generating a new sequence based on the results of the evaluating step using a genetic algorithm; and

repeating the building, evaluating, and generating steps for a number of iterations.

21. The method of claim 20, further comprising responding to variations in the enterprise model input by a user by modifying a portfolio view as incrementally affected by the variation, the portfolio view representing a set of products.

22. The method of claim 20, further comprising selecting a sequence of the products using potential product priorities.

23. The method of claim 20, further comprising evaluating each schedule with a score based on whether the constraints are violated.

24. The method of claim 20, wherein the task models further represent resource alternatives for performing tasks.

25. The method of claim 20, wherein the component model type comprises a task network attribute representing the tasks for providing a component.

26. The method of claim 20, further comprising evaluating the sequences such that profit from the sequences is maximized.

27. The method of claim 20, further comprising providing a presentation layer that provides displays of the enterprise model.

28. The method of claim 20, wherein the resource model type comprises a capacity attribute representing rules for allocating resources to tasks.