BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to smart products lifecycle management (sPLM) systems and, more particularly, to a product lifecycle management system that can be used with smart products such as unmanned aircraft systems.

2. Description of the Related Art

New information and communication technologies—such as sensor networks, predictive analytics, and cloud computing—are enabling a fast growth of connected “smart products.” Embedded computing and networking functionalities into products are now common features. They provide several fundamental capabilities to smart products. A smart product (1) possesses a globally unique identification; (2) is able to retain or store data about itself; (3) is able to continuously monitor its status and environment; (4) could react and adapt to environmental and operational conditions; (5) is able to maintain optimal performance; and, (6) could actively communicate with the user, environment, and/or other products and systems.

These capabilities provide smart products with a certain degree of intelligence that enables them to perform reasoning based on known knowledge, and to learn new knowledge from past/present experience. The degree of intelligence of smart products depends on how well they handle information, identify and solve problems, and make good decisions. The increasing use of sensors within smart products provides the data needed for intelligence. Data analytics provides the tools and technologies needed to increase the degree of intelligence.

Based on statistical and machine-learning techniques, data analytics helps a product not only to understand what has happened (descriptive analytics) and why it happened (diagnostic analytics), but also to determine what could happen (predictive analytics) and what should it do (prescriptive analytics). The predictive analytics is the key technology to use past and current behaviors to improve decisions for future actions. This technology can be implemented inside the physical product itself or completely outside the physical product using a cloud-based service. Either way, an up-to-date analytics model is a necessary foundation for such a technology.

Creating smart products requires developing physical products and analytics models in a transdisciplinary way across mechatronics, software, and service domains. A lifecycle approach is necessary to capture data and information required by all stakeholders, as well as to exchange that data/information among heterogeneous processes, tools, and information systems. Conventional product lifecycle management (PLM) provides a shared platform for creating, managing, and disseminating product-related information across the extended enterprise. It also provides capabilities to access, use, and maintain product definition information, as well as the business processes related to all lifecycle activities as they may be required by any stakeholder. Conventional PLM, however, focuses on physical product related information management and is not designed for smart products that intensively involve data analytics. Accordingly, there is a need in the art for a system that can be used to record, manage, and track multidisciplinary data generated throughout a smart product's lifecycle stages.

BRIEF SUMMARY OF THE INVENTION

The present invention provides a product lifecycle management system that can be used with smart products such as unmanned aircraft systems. The platform of the present invention includes “smart component” data models that incorporate analytics models as “parts” or “services” of products in their master records in the product lifecycle management system. These smart-component data models can be modularized, composed, reused, traced, maintained, and replaced on demand just like their physical counterparts. As an example, the platform was implemented as a prototype system that demonstrated the feasibility of the proposed data models in connection with an unmanned aircraft system.

More particularly, the present invention includes a system for managing a smart product. The system includes a product application installed 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 product, wherein at least one of analytical models in the set of analytic models will be modified by the product application in response to use of the smart product. The system also includes 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 operation of the smart product based on modeling by the rule engine. The system further includes 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. The smart product may comprise an unmanned aerial vehicle. The set of data describing the plurality of physical components may comprise a type of vehicle, a type of airframe, a type of avionics, a payload, and a power system. The plurality of analytical components may comprise 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. The navigation model may include at least one of state estimation, perception, and situation awareness. The plurality of analytical components may include 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. The plurality of analytical components may include 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. The control model may include at least one of linear control, non-linear control, and learning-based control. The plurality of analytical components may include a mission plan for a specific task.

The present invention also includes a method for managing a smart product. The first step of the method involves providing a product application installed 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 product, wherein at least one of analytical models in the set of analytic models will be modified by the product application in response to use of the smart product, 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 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. The second step of the method involves updating the product lifecycle management system and the repository with any changes to the set of analytic models governing operation of the product.

