BRAND PROTECTION MANAGEMENT SYSTEM

• US 20090307032A1
• Filed: 08/03/2007
• Published: 12/10/2009
• Est. Priority Date: 08/03/2006
• Status: Abandoned Application

• Current Assignee: ITI Scotland Limited (Scottish Government)
• Original Assignee: ITI Scotland Limited (Scottish Government)
• Inventors: Todd, Stephen, MacLauchlan, Ken, Tribe, Raglan, Frey, Colin
• Application Number:
  US12/375,197
• Publication Number:
  US 20090307032A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

A product management system for monitoring the movement of products through a supply chain, the system being adapted to receive data from reader devices that capture data associated with the products as they move through the chain. The captured data is used to generate an event record for each product, at each stage in the supply chain. These records are used, together with at least one model of the supply chain, to detect anomalous events.

Claims

1. A method of detecting unauthorised events occurring in a product supply chain, the method comprising:

receiving data associated with an item at a plurality of points in a supply chain;

generating a respective event record for the data received, and

comparing said generated event records with at least one modelled supply chain that has one or more expected states to detect generated event records that not match the expected states of the supply chain model.

2. A method as claimed in claim 1 comprising reading a machine readable tag or label physically associated with the product, thereby to generate the data associated with the item.

3. A method as claimed in claim 1 comprising processing generated event records relating to a single item in the supply chain so as to compile a representative life history of that item.

4. A method as claimed in claim 1 comprising applying at least one pattern matching method to match generated event records against one or more supply chain models.

5. A method as claimed in claim 4, wherein the at least one the pattern matching method comprises Markov modelling of event probabilities.

6. A method as claimed claim 1 comprising using the generated data to predict future anomalous events.

7. A method as claimed in claim 1 comprising monitoring movement of products through a given one of the supply chains, so that multiple passes of the supply chain are made by multiple products and using the event records generated to detect or predict one or more anomalous patterns.

8. A method as claimed in as claimed in claim 1 wherein the supply chain is at least one of:

a drug and/or pharmaceutical product supply chain;

a drugs dispensing supply chain;

a spare parts supply chain, for example airline or automotive parts.

9. A product management system for use with data capture means for capturing data associated with items in a supply chain, the product management system comprising:

means for generating event records from data captured by the data capture means, each event record corresponding to data captured from an item at a point in a supply chain; and

processor means for processing each generated event record to compare said generated event records with at least one supply chain model, so as to detect any generated event records that do not match with said model supply chain.

10. A system as claimed in claim 9 comprising means for performing a predetermined action when the processor detects that one or more event records do not match said supply chain model.

11. A system as claimed in claim 9 comprising database means for storing the or each said supply chain model.

12. A system as claimed in claim 9, wherein the processor means are operable to map the generated event records to at least one said supply chain model.

13. A system as claimed in claim 12, wherein the mapping means comprises Markov modelling means.

14. A system as claimed in claim 9, wherein the processor means includes heuristic processing means.

15. A system as claimed in claim 9, wherein the processor means are operable to synthesize data from the generated event records.

16. A system as claimed in claim 9, wherein the processor means are operable to continually monitor the generated event records so as to detect automatically anomalies that represent potential threats.

17. A system as claimed in claim 9, wherein the processor means are operable to employ at least one of forward chaining rules and case based reasoning approaches.

18. A system as claimed in claim 9, wherein the product management system is configured for communication with the data capture means via a computer network.

19. A system as claimed in claim 9 configured to generate a predetermined response when an anomaly is detected by the processor means.

28. An apparatus comprising data capture means for capturing data associated with products in a supply chain and a product management system according to claim 9.

20. A method of detecting unauthorised events in a product supply chain, the method comprising:

monitoring movement of products through a supply chain or a part thereof using data captured from the products;

generating a respective event record for the data captured for each pass of the supply chain, and

using the event records generated to detect or predict one or more anomalous events.

21. A method as claimed in claim 20 comprising monitoring the movement of goods over a period in which multiple passes of the supply chain are made.

22. A method as claimed in claim 20 comprising using the event records to detect sequences or repeating patterns of events and using these to predict one or more future events.

23. A method as claimed in claim 20 comprising using a supply chain model together with the generated event records to detect or predict anomalous events.

24. A system for detecting unauthorised events occurring in a product supply chain, the system being configured to:

monitor movement of products through a supply chain using data captured from the products at a plurality of points in the chain over a period such that multiple passes are made by multiple products;

generate a respective event record for the data captured for each pass of the supply chain and

use the event records generated to detect or predict one or more anomalous patterns or future events.

25. A system as claimed in claim 24 adapted to monitor the movement of goods over a period in which multiple passes of the supply chain are made.

26. A system as claimed in claim 24 that is adapted to detect sequences or repeating patterns of events using the event records and use these to predict one or more anomalous patterns or future events.

27. A system as claimed in claim 24 that is adapted to use a supply chain model together with the generated event records to detect or predict anomalous events.

29. (canceled)