Populating digital twins for value chain networks

Abstract

A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.

What is claimed is: 
     
         1 . A method for serving digital twins comprising:
 receiving, by a processing system of a digital twin system, a request for a digital twin from a user device of a user associated with an enterprise, the enterprise deploying a sensor system to monitor one or more facilities of the enterprise;   determining, by the processing system, a workforce role of the user with respect to the enterprise;   generating, by the processing system, a role-based digital twin corresponding to the workforce role of the user based on a perspective view corresponding to the workforce role of the user, wherein the role-based digital twin depicts one or more states and/or entities that are related to the enterprise; and   providing, by the processing system, the role-based digital twin to the user device, wherein providing the role-based digital twin:   identifying, by the processing system, a set of data types that are used to populate the at least one of the states and/or entities of the role-based digital twin, wherein the set of data types include one or more sensor data feeds that are received from the sensor system deployed by the enterprise; and   connecting, by the processing system, the one or more sensor data streams to the role-based digital twin.   
     
     
         2 . The method of  claim 1 , wherein generating the role-based digital twin includes determining the perspective view corresponding to the workforce role of the user based on the workforce role of the user and a set of data types that are relevant to the workforce role of the user. 
     
     
         3 . The method of  claim 2 , wherein determining the perspective view corresponding to the workforce role of the user includes determining an appropriate granularity level for each data type of the set of data types. 
     
     
         4 . The method of  claim 3 , wherein the appropriate granularity level for at least one of the data types is defined in a default configuration corresponding to the workforce role. 
     
     
         5 . The method of  claim 3 , wherein the appropriate granularity level for at least one of the data types is determined based on previous interactions of the user with the role-based digital twin. 
     
     
         6 . The method of  claim 1 , wherein the sensor system includes an edge device that receives sensor data from a set of sensors within the sensor system and generates the sensor data stream that is provided to the digital twin system via a network. 
     
     
         7 . The method of  claim 6 , wherein the edge device receives sensor data from the set of sensors and selectively compresses the sensor data based on values indicated in the sensor data to obtain the sensor data stream. 
     
     
         8 . The method of  claim 6 , wherein connecting the one or more sensor streams includes:
 receiving the sensor data stream from the edge device; and   routing the sensor data stream to the user device that is presenting the role-based digital twin to the user.   
     
     
         9 . The method of  claim 6 , wherein connecting the one or more sensor streams includes:
 receiving the sensor data stream from the edge device; and   analyzing the sensor data stream to identify one or more fault conditions corresponding to an object being monitored by the sensor system; and   routing an indicator of the fault condition to the user device that is presenting the role-based digital twin to the user.   
     
     
         10 . The method of  claim 6 , wherein connecting the one or more sensor streams includes:
 receiving the sensor data stream from the edge device;   analyzing the sensor data stream to identify a recommendation corresponding to the workforce role of the user; and   routing an indicator of the recommendation to the user device that is presenting the role-based digital twin to the user.   
     
     
         11 . The method of  claim 6 , wherein connecting the one or more sensor streams includes:
 receiving the sensor data stream from the edge device;   analyzing the sensor data stream to identify a recommendation corresponding to the workforce role of the user; and   routing an indicator of the recommendation to the user device that is presenting the role-based digital twin to the user.   
     
     
         12 . The method of  claim 1 , wherein the workforce is a factory operations workforce. 
     
     
         13 . The method of  claim 1 , wherein the workforce is a plant operations workforce. 
     
     
         14 . The method of  claim 1 , wherein the workforce is a resource extraction operations workforce. 
     
     
         15 . The method of  claim 1 , wherein the workforce is a network operations workforce responsible for operating a network for an industrial production environment. 
     
     
         16 . The method of  claim 1 , wherein the workforce is a supply chain management workforce. 
     
     
         17 . The method of  claim 1 , wherein the workforce is a demand planning workforce. 
     
     
         18 . The method of  claim 1 , wherein the workforce is a logistics planning workforce. 
     
     
         19 . The method of  claim 1 , wherein the workforce is a vendor management workforce. 
     
     
         20 . The method of  claim 1 , wherein at least one workforce role is selected from among a CEO role, a COO role, a CFO role, a counsel role, a board member role, a CTO role, an information technology manager role, a chief information officer role, a chief data officer role, an investor role, an engineering manager role, a project manager role, an operations manager role, and a business development role. 
     
     
         21 . The method of  claim 1 , wherein at least one workforce role is selected from among a factory manager role, a factory operations role, a factory worker role, a power plant manager role, a power plant operations role, a power plant worker role, an equipment service role, and an equipment maintenance operator role. 
     
     
         22 . The method of  claim 1 , wherein at least one workforce role is selected from among a market maker role, an exchange manager role, a broker-dealer role, a trading role, a reconciliation role, a contract counterparty role, an exchange rate setting role, a market orchestration role, a market configuration role, and a contract configuration role. 
     
     
         23 . The method of  claim 1 , wherein at least one workforce role is selected from among a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a salesperson role, and a distribution center manager role.