Employing associative memory for enhanced lifecycle management

• US 10,235,445 B2
• Filed: 11/30/2016
• Issued: 03/19/2019
• Est. Priority Date: 02/09/2009
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Quadracci, Leonard J., Warn, Brian
• Primary Examiner(s): Zhen, Wei Y
• Assistant Examiner(s): Bourzik, Brahim
• Application Number:
  US15/365,370
• Publication Number:
  US 20170109428A1
• Time in Patent Office: 839 Days
• CPC Class Codes: G06F 16/2428 Query predicate definition using graphical user interfaces, including menus and forms G06F16/2423 takes precedence
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification

Abstract

A non-conformance analysis system may have an associative memory subsystem populated with information involving a plurality of entities defining different attributes of a component, with each entity being categorized under a user defined entity type, the entities and entity types forming an associative memory. A user input device may be used for enabling a user to input a query concerning the component, and to obtain information useful for managing a lifecycle of said component. An associative memory entity analytics engine in communication with the associative memory subsystem, and responsive to said user input device, searches the associative memory using the information provided in the query to retrieve entities helpful to the user in assessing the lifecycle of the component.

Claims

1. A non-conformance analysis system, comprising:

an associative memory subsystem having an associative learning memory populated with information involving a plurality of entities defining different attributes of a component, with each said entity being categorized under a user defined entity type, the entities and entity types being stored in said associative learning memory;

an input device configured to receive a free text query including at least one of words and numbers, concerning said component to obtain information related to managing a lifecycle of said component;

an associative memory entity analytics engine in communication with said associative memory subsystem, and responsive to said input device, said associative memory analytics engine including query software that uses the free text query to perform a plurality of searches of said associative learning memory to retrieve entities related to assessing said lifecycle of said component;

said associative memory entity analytics engine further using additional information received by the input device and relating to results of said free text query, to selectively update existing ones of said entities, and to selectively create new entities, in said associative learning memory; and

said associative memory entity analytics engine further providing a correlation value for each said entity type returned from said plurality of searches to indicate how well each said entity type correlates to said free text query, relative to other ones of said entity types returned from said plurality of searches, the correlation value being indicative of which ones of each of said returned entity types are more relevant than other ones of said returned entity types.

2. The system of claim 1, wherein said input device comprises a computer display terminal for displaying information relating to said retrieved entities.

3. The system of claim 1, further comprising a plurality of different types of information tools for containing information related to managing a lifecycle of said component.

4. The system of claim 1, wherein said associative memory entity analytics engine performs a search of said associative learning memory for each one of said words and numbers of the free text query.

5. The system of claim 3, further comprising a database update software system for updating said information tools with the additional information relating to results of the free text query.

6. The system of claim 3, further comprising a data mining tool in communication with said information tools and said associative learning memory subsystem, said data mining tool adapted to obtain specific information from said information tools that is used to create said entities and store said entities within said associative learning memory.

7. The system of claim 3, wherein said information tools comprise at least one of:

an historical database;

a transactional database; and

a wide area network.

8. A method for forming a system for managing a lifecycle of a component, said method comprising:

using an associative memory subsystem populated with information involving a plurality of entities, with each said entity being categorized under a pre-defined entity type, and the entity types and entities collectively being used by associative learning memory;

using an input device configured to receive a free text query including at least one of words and numbers, concerning information related to managing a non-conformance of said component;

using an entity analytics engine in communication with said input device and said associative memory subsystem to analyze entities stored in said associative learning memory and to retrieve specific ones of said entities stored in said associative learning memory that include information relating to managing a non-conformance of said component;

using the entity analytics engine to periodically update the associative learning memory with new information obtained from a data mining tool, and also using new information relating to results of said query, to thus update existing ones of said entities with additional information, and to create new entities when needed, in said associative learning memory; and

said entity analytics engine further providing a correlation value for each said entity type returned from results of said free text query to indicate how well each said entity type correlates to said free text query, relative to other ones of said entity types returned from said free text query, the correlation value being indicative of which ones of each of said returned entity types are more relevant than other ones of said returned entity types.

9. The method of claim 8, wherein said using an entity analytics engine comprises using an entity analytics engine having software that uses the free text query to perform a plurality of searches of said associative learning memory.

10. The method of claim 9, wherein said plurality of searches comprises independent searches for at least one of:

different words used in said free text query; and

different numbers used in said free text query.

11. The method of claim 8, wherein said specific ones of said entities include specific information related to determining a lifecycle of component.

12. The method of claim 8, further comprising using information from a plurality of different information sources to form said entities.

13. The method of claim 12, wherein forming said entities using said different information sources comprises at least one of:

forming said entities with information obtained from an historical database;

forming said entities with information obtained from a transactional database; and

forming said entities with information obtained from a wide area network.

14. The method of claim 13, further comprising updating said information tools with additional information.

15. The method of claim 8, further comprising displaying said information associated with said entities on said input device.

16. A method for managing a lifecycle of a component, comprising:

providing an associative memory subsystem having an associative learning memory;

said associative learning memory having information relating to said component, said information being organized in accordance with pre-defined entity types, where each said entity type has at least one entity representing a specific attribute;

using an entity analytics engine to search said associative learning memory using a free text query received by an input device in communication with said entity analytics engine;

using said entity analytics engine during said search to obtain all relevant entities containing attributes that may be related to said free text query;

outputting said relevant entities to a display;

using the entity analytics engine to periodically update the associative learning memory with new information obtained from a data mining tool;

further using said associative memory entity analytics engine to receive additional information received by the input device and relating to results of said free text query, and using the additional information to selectively update existing ones of said entities, and to selectively create new entities, in said associative learning memory; and

said associative memory entity analytics engine further providing a correlation value for each said entity type returned from said plurality of searches to indicate how well each said entity type correlates to said free text query, relative to other ones of said entity types returned from said plurality of searches, the correlation value being indicative of which ones of each of said returned types are more relevant than other ones of said returned entity types.

17. The method of claim 16, wherein said input device comprises said display.

18. The method of claim 16, wherein said using an entity analytics engine to search said associative learning memory using said free text query comprises using free text information provided by a user from said input device.