Smart products lifecycle management platform
A Smart Products Lifecycle Management (sPLM) system that is built upon the smart component data model and the NPD 3 process model, is enabling engineers, data scientists, and other stakeholders to collaborate on a common platform to develop smart products. The sPLM system is validated by applying it to unmanned aircraft systems (UAS) development and operations, referred to as UsPLM. The UsPLM has shared lifecycle management functions that are provided as web services and can be applied to all digital models of UAS devices, software, autonomy functions, and missions. The individual models can be versioned, tracked, and be composed with other compatible models, if needed. The rule and scoring engines embedded in the UsPLM allow building and executing configuration rules, regulation rules, and various machine-learning models. This facilitates modular UAS architecture design so that the UAS has the flexibility to be reconfigured for various mission applications.
1. A system for managing a smart product, comprising:
a product application installed on a processor of the smart product and including a set of data describing a plurality of physical components of the smart product and a set of analytic models governing operation of the smart product, wherein at least one of analytical models in the set of analytic models is modified over time by the product application in response to use of the smart product to change how the smart product operates;
a product lifecycle management system running on computer hardware that is positioned remotely from and in communication with the product application, wherein the product lifecycle management system is programmed to include a rule engine for modeling operation of the smart product and a scoring engine for assessing the operation of the smart product based on modeling by the rule engine; and
a repository in communication with the product application and the product lifecycle management system for storing a copy of the set of data and the set of analytical models so that the copy of the set of analytical models includes any modifications to the at least one of the analytical models that have been made by the product application in response to use of the smart product.
2. The system of claim 1 , wherein the smart product comprises an unmanned aerial vehicle.
3. The system of claim 2 , wherein the set of data describing the plurality of physical components comprises a type of vehicle, a type of airframe, a type of avionics, a payload, and a power system.
4. The system of claim 3 , wherein one of the plurality of analytical models comprises an autonomous navigation system having at least one navigation model that can be adjusted over time to change how the unmanned aerial vehicle controls its movement.
5. The system of claim 4 , wherein the navigation model includes at least one of state estimation, perception, and situation awareness.
6. The system of claim 5 , wherein the plurality of analytical models includes an autonomous guidance system having at least one guidance model that can be adjusted over time to change how the unmanned aerial vehicle selects a path of travel.
7. The system of claim 6 , wherein the plurality of analytical models includes an autonomous control system having at least one control model that can be adjusted over time to change how the unmanned aerial vehicle controls its flight.
8. The system of claim 7 , wherein the control model includes at least one of linear control, non-linear control, and learning-based control.
9. The system of claim 8 , wherein the plurality of analytical models includes a mission plan for a specific task.
10. A method for managing a smart product, comprising the steps of:
installing a product application on the smart product and including a set of data describing a plurality of physical components of the smart product and a set of analytic models governing operation of the smart product, wherein at least one of analytical models in the set of analytic models is modified over time by the product application in response to use of the smart product to change how the smart product operates, a product lifecycle management system positioned remotely from and in communication with the product application, wherein the product lifecycle management system is programmed to include a rule engine for modeling operation of the smart product and a scoring engine for assessing the operation of the smart product based on modeling by the rule engine, and a repository in communication with the product application and the product lifecycle management system for storing the set of data and the set of analytical models so that the set of analytical models includes any modifications to the at least one of the analytical models made by the product application in response to use of the smart product; and
updating the product lifecycle management system and the repository with any changes to the set of analytic models governing the operation of the smart product.
11. The method of claim 10 , wherein the smart product comprises an unmanned aerial vehicle.
12. The method of claim 11 , wherein the set of data describing the plurality of physical components comprises a type of vehicle, a type of airframe, a type of avionics, a payload, and a power system.
13. The method of claim 12 , wherein one of the plurality of analytical models is an autonomous navigation system having at least one navigation model that can be adjusted over time to change how the unmanned aerial vehicle controls its movement.
14. The method of claim 13 , wherein the navigation model includes at least one of state estimation, perception, and situation awareness.
15. The method of claim 14 , wherein the plurality of analytical models includes an autonomous guidance system having at least one guidance model that can be adjusted over time to change how the unmanned aerial vehicle selects a path of travel.
16. The method of claim 15 , wherein the plurality of analytical models includes an autonomous control system having at least one control model that can be adjusted over time to change how the unmanned aerial vehicle controls its flight.
17. The method of claim 16 , wherein the control model includes at least one of linear control, non-linear control, and learning-based control.
18. The method of claim 17 , wherein the plurality of analytical models includes a mission plan for a specific task.