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Artificial intelligence system for control tower and enterprise management … — Strong Force Vcn Portfolio 2019, Llc (US20220058569A1)

Strong Force Vcn Portfolio 2019, Llc · Google Patents

Google Patents · Patents · License: Open Access

charleshowardcella strongforcevcnportfolio2019

patent, google patents, intellectual property, US20220058569A1, Strong Force Vcn Portfolio 2019, Llc, Charles Howard Cella, en, 2022

ABSTRACT

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.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a bypass continuation of International Application No. PCT/US2020/059227, filed Nov. 5, 2020, which claims the benefit of priority to the following U.S. Provisional Patent Applications: Ser. No. 62/931,193, filed Nov. 5, 2019, entitled âMETHODS AND SYSTEMS OF VALUE CHAIN NETWORK MANAGEMENT PLATFORM;â Ser. No. 62/969,153 filed Feb. 3, 2020, entitled âMETHODS AND SYSTEMS OF VALUE CHAIN NETWORK MANAGEMENT PLATFORM;â Ser. No. 63/016,976 filed Apr. 28, 2020, entitled âDIGITAL TWIN SYSTEMS AND METHODS FOR FACILITATING VALUE CHAIN NETWORKS AND LOGISTICS;â Ser. No. 63/054,606 filed Jul. 21, 2020, entitled âDIGITAL TWIN SYSTEMS AND METHODS FOR FACILITATING VALUE CHAIN NETWORKS AND LOGISTICS;â Ser. No. 63/069,533, filed Aug. 24, 2020, entitled âINFORMATION TECHNOLOGY SYSTEMS AND METHODS FOR VALUE CHAIN ARTIFICIAL INTELLIGENCE LEVERAGING DIGITAL TWINS;â and Ser. No. 63/087,292, filed Oct. 4, 2020, entitled âEXECUTIVE CONTROL TOWER AND ENTERPRISE MANAGEMENT PLATFORM FOR VALUE CHAIN NETWORK.â Each of the above applications is hereby incorporated by reference in its entirety as if fully set forth herein.

FIELD

The present disclosure relates to information technology methods and systems for management of value chain network entities, including supply chain and demand management entities. The present disclosure also relates to the field of enterprise management platforms, more particularly involving data management, artificial intelligence, network connectivity and digital twins

BACKGROUND

Historically, many of the various categories of goods purchased and used by household consumers, by businesses and by other customers were been supplied mainly through a relatively linear fashion, in which manufacturers and other suppliers of finished goods, components, and other items handed off items to shipping companies, freight forwarders and the like, who delivered them to warehouses for temporary storage, to retailers, where customers purchased them, or directly to customer locations. Manufacturers and retailers undertook various sales and marketing activities to encourage and meet demand by customers, including designing products, positioning them on shelves and in advertising, setting prices, and the like.

Orders for products were fulfilled by manufacturers through a supply chain, such as depicted in FIG. 1 , where suppliers 122 in various supply environments 160 , operating production facilities 134 or acting as resellers or distributors for others, made a product 130 available at a point of origin 102 in response to an order. The product 130 was passed through the supply chain, being conveyed and stored via various hauling facilities 138 and distribution facilities 134 , such as warehouses 132 , fulfillment centers 112 and delivery systems 114 , such as trucks and other vehicles, trains, and the like. In many cases, maritime facilities and infrastructure, such as ships, barges, docks and ports provided transport over waterways between the points of origin 102 and one or more destinations 104 .

Organizations have access to an almost unlimited amount of data. With the advent of smart connected devices, wearable technologies, the Internet of Things (IoT), and the like, the amount of data available to an organization that is planning, overseeing, managing and operating a value chain network has increased dramatically and will likely to continue to do so. For example, in a manufacturing facility, warehouse, campus, or other operating environment, there may be hundreds to thousands of IoT sensors that provide metrics such as vibration data that measure the vibration signatures of important machinery, temperatures throughout the facility, motion sensors that can track throughput, asset tracking sensors and beacons to locate items, cameras and optical sensors, chemical and biological sensors, and many others. Additionally, as wearable technologies become more prevalent, wearables may provide insight into the movement, health indicators, physiological states, activity states, movements, and other characteristics of workers. Furthermore, as organizations implement CRM systems, ERP systems, operations systems, information technology systems, advanced analytics and other systems that leverage information and information technology, organizations have access to an increasingly wide array of other large data sets, such as marketing data, sales data, operational data, information technology data, performance data, customer data, financial data, market data, pricing data, supply chain data, and the like, including data sets generated by or for the organization and third-party data sets.

The presence of more data and data of new types offers many opportunities for organizations to achieve competitive advantages; however, it also presents problems, such as of complexity and volume, such that users can be overwhelmed, missing opportunities for insight. A need exists for methods and systems that allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations.

SUMMARY

According to some embodiments of the present disclosure, methods and systems are provided herein for an information technology system that may include a cloud-based management platform with a micro-services architecture; a set of interfaces, network connectivity facilities, adaptive intelligence facilities, data storage facilities, and monitoring facilities; and a set of applications for enabling an enterprise to manage a set of value chain network entities from a point of origin to a point of customer use.

In embodiments, provided herein are methods, systems, components and other elements for an information technology system that may include a cloud-based management platform with a micro-services architecture, the platform having a set of interfaces for accessing and configuring features of the platform; a set of network connectivity facilities for enabling a set of value chain network entities to connect to the platform; a set of adaptive intelligence facilities for automating a set of capabilities of the platform; a set of data storage facilities for storing data collected and handled by the platform; and a set of monitoring facilities for monitoring the value chain network entities; wherein the platform hosts a set of applications for enabling an enterprise to manage a set of value chain network entities from a point of origin of a product of the enterprise to a point of customer use.

In embodiments. the set of interfaces includes at least one of a demand management interface and a supply chain management interface. In embodiments, the set of network connectivity facilities includes a 5G network system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes an Internet of Things system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes a cognitive networking system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes a peer-to-peer network system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes an edge intelligence system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a robotic process automation system. In embodiments, the set of adaptive intelligence facilities includes a self-configuring data collection system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a digital twin system representing attributes of at least one value chain network entity of the value chain network entities controlled by the enterprise. In embodiments, the set of adaptive intelligence includes a smart contract system that is configured to automate a set of interactions among the value chain network entities.

In embodiments, the set of data storage facilities uses a distributed data architecture. In embodiments, the set of data storage facilities uses a blockchain. In embodiments, the set of data storage facilities uses a distributed ledger. In embodiments, the set of data storage facilities uses a graph database representing a set of hierarchical relationships of the value chain network entities. In embodiments, the set of monitoring facilities includes an Internet of Things monitoring system. In embodiments, the set of monitoring facilities includes a sensor system deployed in an infrastructure facility operated by the enterprise. In embodiments, the set of applications includes a set of applications of at least two types from among a set of supply chain management applications, demand management applications, intelligent product applications, and enterprise resource management applications. In embodiments, the set of applications includes an asset management application.

In embodiments, the value chain network entities are selected from the group consisting of products, suppliers, producers, manufacturers, retailers, businesses, owners, operators, operating facilities, customers, consumers, workers, mobile devices, wearable devices, distributors, resellers, supply chain infrastructure facilities, supply chain processes, logistics processes, reverse logistics processes, demand prediction processes, demand management processes, demand aggregation processes, machines, ships, barges, warehouses, maritime ports, airports, airways, waterways, roadways, railways, bridges, tunnels, online retailers, ecommerce sites, demand factors, supply factors, delivery systems, floating assets, points of origin, points of destination, points of storage, points of use, networks, information technology systems, software platforms, distribution centers, fulfillment centers, containers, container handling facilities, customs, export control, border control, drones, robots, autonomous vehicles, hauling facilities, drones/robots/AVs, waterways, and port infrastructure facilities. In embodiments, the platform manages a set of demand factors, a set of supply factors, and a set of supply chain infrastructure facilities.

In embodiments, the supply factors are factors selected from the group consisting of Component availability, material availability, component location, material location, component pricing, material pricing, taxation, tariff, impost, duty, import regulation, export regulation, border control, trade regulation, customs, navigation, traffic, congestion, vehicle capacity, ship capacity, container capacity, package capacity, vehicle availability, ship availability, container availability, package availability, vehicle location, ship location, container location, port location, port availability, port capacity, storage availability, storage capacity, warehouse availability, warehouse capacity, fulfillment center location, fulfillment center availability, fulfillment center capacity, asset owner identity, system compatibility, worker availability, worker competency, worker location, goods pricing, fuel pricing, energy pricing, route availability, route distance, route cost, and route safety factors.

In embodiments, the demand factors are factors selected from the group consisting of product availability, product pricing, delivery timing, need for refill, need for replacement, manufacturer recall, need for upgrade, need for maintenance, need for update, need for repair, need for consumable, taste, preference, inferred need, inferred want, group demand, individual demand, family demand, business demand, need for workflow, need for process, need for procedure, need for treatment, need for improvement, need for diagnosis, compatibility to system, compatibility to product, compatibility to style, compatibility to brand, demographic, psychographic, geolocation, indoor location, destination, route, home location, visit location, workplace location, business location, personality, mood, emotion, customer behavior, business type, business activity, personal activity, wealth, income, purchasing history, shopping history, search history, engagement history, clickstream history, website history, online navigation history, group behavior, family behavior, family membership, customer identity, group identity, business identity, customer profile, business profile, group profile, family profile, declared interest, and inferred interest factors.

In embodiments, the supply chain infrastructure facilities are facilities selected from the group consisting of ship, container ship, boat, barge, maritime port, crane, container, container handling, shipyard, maritime dock, warehouse, distribution, fulfillment, fueling, refueling, nuclear refueling, waste removal, food supply, beverage supply, drone, robot, autonomous vehicle, aircraft, automotive, truck, train, lift, forklift, hauling facilities, conveyor, loading dock, waterway, bridge, tunnel, airport, depot, vehicle station, train station, weigh station, inspection, roadway, railway, highway, customs house, and border control facilities.

CROSS-REFERENCE TO RELATED APPLICATIONS

FIELD

BACKGROUND

SUMMARY

In embodiments, the set of applications involves a set selected from the group consisting of supply chain, asset management, risk management, inventory management, demand management, demand prediction, demand aggregation, pricing, positioning, placement, promotion, blockchain, smart contract, infrastructure management, facility management, analytics, finance, trading, tax, regulatory, identity management, commerce, ecommerce, payments, security, safety, vendor management, process management, compatibility testing, compatibility management, infrastructure testing, incident management, predictive maintenance, logistics, monitoring, remote control, automation, self-configuration, self-healing, self-organization, logistics, reverse logistics, waste reduction, augmented reality, virtual reality, mixed reality, demand customer profiling, entity profiling, enterprise profiling, worker profiling, workforce profiling, component supply policy management, product design, product configuration, product updating, product maintenance, product support, product testing, warehousing, distribution, fulfillment, kit configuration, kit deployment, kit support, kit updating, kit maintenance, kit modification, kit management, shipping fleet management, vehicle fleet management, workforce management, maritime fleet management, navigation, routing, shipping management, opportunity matching, search, advertisement, entity discovery, entity search, distribution, delivery, and enterprise resource planning applications.

In embodiments, an information technology system, includes a cloud-based management platform with a micro-services architecture, the platform having a set of interfaces that are configured to access and configure features of the platform, a set of network connectivity facilities that are configured to direct a set of value chain network entities to connect to the features of the platform, a set of adaptive intelligence facilities that are configured to automate a set of capabilities of the platform related to at least one of the value chain network entities and the features of the platform, a set of data storage facilities that are configured to store data collected and handled by the platform, and a set of monitoring facilities that are configured to monitor the value chain network entities, wherein the interfaces, the network connectivity facilities, the adaptive intelligence facilities, the data storage facilities, and the monitoring facilities are coordinated for monitoring and management of the value chain network entities; a set of applications that are configured to direct an enterprise to manage the value chain network entities of the platform from a point of origin to a point of customer use; and a unified set of robotic process automation systems that provide coordinated automation among at least two types of applications from among a set of demand management applications, a set of supply chain applications, a set of intelligent product applications, and a set of enterprise resource management applications for a category of goods with respect to the value chain network entities of the platform.

In embodiments, the unified set of robotic process automation systems automate a process selected from the group consisting of selection of a quantity of product for an order, selection of a carrier for a shipment, selection of a vendor for a component, selection of a vendor for a finished goods order, selection of a variation of a product for marketing, selection of an assortment of goods for a shelf, determination of a price for a finished good, configuration of a service offer related to a product, configuration of product bundle, configuration of a product kit, configuration of a product package, configuration of a product display, configuration of a product image, configuration of a product description, configuration of a website navigation path related to a product, determination of an inventory level for a product, selection of a logistics type, configuration of a schedule for product delivery, configuration of a logistics schedule, configuration of a set of inputs for machine learning, preparation of product documentation, preparation of disclosures about a product, configuration of a product for a set of local requirements, configuration of a set of products for compatibility, configuration of a request for proposals, ordering of equipment for a warehouse, ordering of equipment for a fulfillment center, classification of a product defect in an image, inspection of a product in an image, inspection of product quality data from a set of sensors, inspection of data from a set of onboard diagnostics on a. product, inspection of diagnostic data from an Internet of Things system, review of sensor data from environmental sensors in a set of supply chain environments, selection of inputs for a digital twin, selection of outputs from a digital twin, selection of visual elements for presentation in a digital twin, diagnosis of sources of delay in a supply chain, diagnosis of sources of scarcity in a supply chain, diagnosis of sources of congestion in a supply chain, diagnosis of sources of cost overruns in a supply chain, diagnosis of sources of product defects in a supply chain, and prediction of maintenance requirements in supply chain infrastructure.

In embodiments, one of the processes automated by the robotic process automation system involves selection of a quantity of product for an order. In embodiments, one of the processes automated by the robotic process automation system involves selection of a carrier for a shipment. In embodiments, wherein one of the processes automated by the robotic process automation system involves selection of a vendor for a component. In embodiments, wherein one of the processes automated by the robotic process automation system involves selection of a vendor for a finished goods order. In embodiments, wherein one of the processes automated by the robotic process automation system involves selection of a variation of a product for marketing. In embodiments, wherein one of the processes automated by the robotic process automation system involves selection of an assortment of goods for a shelf. In embodiments, wherein one of the processes automated by the robotic process automation system involves determination of a price for a finished good.

In embodiments, one of the processes automated by the robotic process automation system involves configuration of a service offer related to a product. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a product bundle. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a product kit. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a product package. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a product display. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a product image. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a product description. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a website navigation path related to a product.

In embodiments, one of the processes automated by the robotic process automation system involves determination of an inventory level for a product. In embodiments, wherein one of the processes automated by the robotic process automation system involves selection of a logistics type. In embodiments, wherein one of the processes automated by the robotic process automation system involves configuration of a schedule for product delivery. In embodiments, one of the processes automated by the robotic process automation system involves configuration of a logistics schedule. In embodiments, one of the processes automated by the robotic process automation system involves configuration of a set of inputs for machine learning. In embodiments, one of the processes automated by the robotic process automation system involves preparation of product documentation. In embodiments, one of the processes automated by the robotic process automation system involves preparation of disclosures about a product. In embodiments, one of the processes automated by the robotic process automation system involves configuration of a product for a set of local requirements. In embodiments, one of the processes automated by the robotic process automation system involves configuration of a set of products for compatibility. In embodiments, one of the processes automated by the robotic process automation system involves configuration of a request for proposals. In embodiments, one of the processes automated by the robotic process automation system involves ordering of equipment for a warehouse. In embodiments, one of the processes automated by the robotic process automation system involves ordering of equipment for a fulfillment center. In embodiments, one of the processes automated by the robotic process automation system involves classification of a product defect in an image. In embodiments, one of the processes automated by the robotic process automation system involves inspection of a product in an image. In embodiments, one of the processes automated by the robotic process automation system involves inspection of product quality data from a set of sensors. In embodiments, one of the processes automated by the robotic process automation system involves inspection of data from a set of onboard diagnostics on a. product.

In embodiments, one of the processes automated by the robotic process automation system involves inspection of diagnostic data from an Internet of Things system. In embodiments, one of the processes automated by the robotic process automation system involves review of sensor data from environmental sensors in a set of supply chain environments. In embodiments, one of the processes automated by the robotic process automation system involves selection of inputs for a digital twin. In embodiments, one of the processes automated by the robotic process automation system involves selection of outputs from a digital twin. In embodiments, one of the processes automated by the robotic process automation system involves selection of visual elements for presentation in a digital twin. In embodiments, one of the processes automated by the robotic process automation system involves diagnosis of sources of delay in a supply chain. In embodiments, one of the processes automated by the robotic process automation system involves diagnosis of sources of scarcity in a supply chain. In embodiments, one of the processes automated by the robotic process automation system involves diagnosis of sources of congestion in a supply chain. In embodiments, one of the processes automated by the robotic process automation system involves diagnosis of sources of cost overruns in a supply chain. In embodiments, one of the processes automated by the robotic process automation system involves diagnosis of sources of product defects in a supply chain. In embodiments, one of the processes automated by the robotic process automation system involves prediction of maintenance requirements in supply chain infrastructure.

In embodiments, the set of demand management applications, supply chain applications, intelligent product applications and enterprise resource management applications are selected from the group consisting of supply chain, asset management, risk management, inventory management, demand management, demand prediction, demand aggregation, pricing, positioning, placement, promotion, blockchain, smart contract, infrastructure management, facility management, analytics, finance, trading, tax, regulatory, identity management, commerce, ecommerce, payments, security, safety, vendor management, process management, compatibility testing, compatibility management, infrastructure testing, incident management, predictive maintenance, logistics, monitoring, remote control, automation, self-configuration, self-healing, self-organization, logistics, reverse logistics, waste reduction, augmented reality, virtual reality, mixed reality, demand customer profiling, entity profiling, enterprise profiling, worker profiling, workforce profiling, component supply policy management, product design, product configuration, product updating, product maintenance, product support, product testing, warehousing, distribution, fulfillment, kit configuration, kit deployment, kit support, kit updating, kit maintenance, kit modification, kit management, shipping fleet management, vehicle fleet management, workforce management, maritime fleet management, navigation, routing, shipping management, opportunity matching, search, advertisement, entity discovery, entity search, distribution, delivery, and enterprise resource planning applications.

In embodiments, the set of interfaces includes at least one of a demand management interface and a supply chain management interface. In embodiments, the set of network connectivity facilities includes a 5G network system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes an Internet of Things system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes a cognitive networking system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes a peer-to-peer network system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes an edge intelligence system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a robotic process automation system. In embodiments, the set of adaptive intelligence facilities includes a self-configuring data collection system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a digital twin system representing attributes of value chain network entity controlled by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a smart contract system that is configured to automate a set of interactions among a set of value chain network entities.

In embodiments, the set of data storage facilities uses a distributed data architecture. In embodiments, the set of data storage facilities uses a blockchain. In embodiments, the set of data storage facilities uses a distributed ledger. In embodiments, the set of data storage facilities uses graph database representing a set of hierarchical relationships of the value chain network entities. In embodiments, the set of monitoring facilities includes an Internet of Things monitoring system. In embodiments, the set of monitoring facilities includes a sensor system deployed in an infrastructure facility operated by an enterprise. In embodiments, the set of applications includes a set of applications of at least two types from among a set of supply chain management applications, demand management applications, intelligent product applications and enterprise resource management applications. In embodiments, the set of applications includes an asset management application.

In embodiments, wherein the platform manages a set of demand factors, a set of supply factors, and a set of supply chain infrastructure facilities.

In embodiments, an information technology system, includes a cloud-based management platform with a micro-services architecture, the platform having a set of interfaces that are configured to access and configure features of the platform, a set of network connectivity facilities that are configured to direct a set of value chain network entities to connect to the features of the platform, a set of adaptive intelligence facilities that are configured to automate a set of capabilities of the platform related to at least one of the value chain network entities and the features of the platform, a set of data storage facilities that are configured to store data collected and handled by the platform, and a set of monitoring facilities that are configured to monitor the value chain network entities, wherein the interfaces, the network connectivity facilities, the adaptive intelligence facilities, the data storage facilities, and the monitoring facilities are coordinated for monitoring and management of the value chain network entities; a set of applications that are configured to direct an enterprise to manage the value chain network entities of the platform from a point of origin to a point of customer use; and a set of microservices layers including an application layer supporting at least one supply chain application and at least one demand management application, wherein the microservices layers include a data collection layer that collects information from a set of Internet of Things resources that collect information with respect to supply chain entities and demand management entities related to the value chain network entities of the platform.

In embodiments, the set of Internet of Things resources that collect information with respect to supply chain entities and demand management entities collects information from entities selected from the group consisting of products, suppliers, producers, manufacturers, retailers, businesses, owners, operators, operating facilities, customers, consumers, workers, mobile devices, wearable devices, distributors, resellers, supply chain infrastructure facilities, supply chain processes, logistics processes, reverse logistics processes, demand prediction processes, demand management processes, demand aggregation processes, machines, ships, barges, warehouses, maritime ports, airports, airways, waterways, roadways, railways, bridges, tunnels, online retailers, ecommerce sites, demand factors, supply factors, delivery systems, floating assets, points of origin, points of destination, points of storage, points of use, networks, information technology systems, software platforms, distribution centers, fulfillment centers, containers, container handling facilities, customs, export control, border control, drones, robots, autonomous vehicles, hauling facilities, drones/robots/AVs, waterways, and port infrastructure facilities.

In embodiments, the set of Internet of Things resources is selected from the group consisting of camera systems, lighting systems, motion sensing systems, weighing systems, inspection systems, machine vision systems, environmental sensor systems, onboard sensor systems, onboard diagnostic systems, environmental control systems, sensor-enabled network switching and routing systems, RF sensing systems, magnetic sensing systems, pressure monitoring systems, vibration monitoring systems, temperature monitoring systems, heat flow monitoring systems, biological measurement systems, chemical measurement systems, ultrasonic monitoring systems, radiography systems, LIDAR-based monitoring systems, access control systems, penetrating wave sensing systems, SONAR-based monitoring systems, radar-based monitoring systems, computed tomography systems, magnetic resonance imaging systems, and network monitoring systems.

In embodiments, the set of Internet of Things resources includes a set of camera systems. In embodiments, the set of Internet of Things resources includes a set of lighting systems. In embodiments, the set of Internet of Things resources includes a set of machine vision systems. In embodiments, the set of Internet of Things resources includes a set of motion sensing systems.

In embodiments, the set of Internet of Things resources includes a set of weighing systems. In embodiments, the set of Internet of Things resources includes a set of inspection systems. In embodiments, the set of Internet of Things resources includes a set of environmental sensor systems. In embodiments, the set of Internet of Things resources includes a set of onboard sensor systems. In embodiments, the set of Internet of Things resources includes a set of onboard diagnostic systems. In embodiments, the set of Internet of Things resources includes a set of environmental control systems. In embodiments, the set of Internet of Things resources includes a set of sensor-enabled network switching and routing systems. In embodiments, the set of Internet of Things resources includes a set of RF sensing systems.

In embodiments, the set of Internet of Things resources includes a set of magnetic sensing systems. In embodiments, the set of Internet of Things resources includes a set of pressure monitoring systems. In embodiments, the set of Internet of Things resources includes a set of vibration monitoring systems. In embodiments, the set of Internet of Things resources includes a set of temperature monitoring systems. In embodiments, the set of Internet of Things resources includes a set of heat flow monitoring systems. In embodiments, the set of Internet of Things resources includes a set of biological measurement systems. In embodiments, the set of Internet of Things resources includes a set of chemical measurement systems. In embodiments, the set of Internet of Things resources includes a set of ultrasonic monitoring systems. In embodiments, the set of Internet of Things resources includes a set of radiography systems. In embodiments, the set of Internet of Things resources includes a set of LIDAR-based monitoring systems. In embodiments, the set of Internet of Things resources includes a set of access control systems. In embodiments, the set of Internet of Things resources includes a set of penetrating wave sensing systems. In embodiments, the set of Internet of Things resources includes a set of SONAR-based monitoring systems. In embodiments, the set of Internet of Things resources includes a set of radar-based monitoring systems. In embodiments, the set of Internet of Things resources includes a set of computed tomography systems. In embodiments, the set of Internet of Things resources includes a set of magnetic resonance imaging systems. In embodiments, the set of Internet of Things resources includes a set of network monitoring systems. In embodiments, the set of interfaces includes at least one of a demand management interface and a supply chain management interface.

In embodiments, the set of applications is at least one of demand management applications, supply chain applications, intelligent product applications, and enterprise resource management applications that are selected from the group consisting of supply chain, asset management, risk management, inventory management, demand management, demand prediction, demand aggregation, pricing, positioning, placement, promotion, blockchain, smart contract, infrastructure management, facility management, analytics, finance, trading, tax, regulatory, identity management, commerce, ecommerce, payments, security, safety, vendor management, process management, compatibility testing, compatibility management, infrastructure testing, incident management, predictive maintenance, logistics, monitoring, remote control, automation, self-configuration, self-healing, self-organization, logistics, reverse logistics, waste reduction, augmented reality, virtual reality, mixed reality, demand customer profiling, entity profiling, enterprise profiling, worker profiling, workforce profiling, component supply policy management, product design, product configuration, product updating, product maintenance, product support, product testing, warehousing, distribution, fulfillment, kit configuration, kit deployment, kit support, kit updating, kit maintenance, kit modification, kit management, shipping fleet management, vehicle fleet management, workforce management, maritime fleet management, navigation, routing, shipping management, opportunity matching, search, advertisement, entity discovery, entity search, distribution, delivery, and enterprise resource planning applications.

In embodiments, the set of network connectivity facilities includes a 5G network system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes an Internet of Things system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of network connectivity facilities includes a cognitive networking system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, wherein the set of network connectivity facilities includes a peer-to-peer network system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes an edge intelligence system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a robotic process automation system. In embodiments, the set of adaptive intelligence includes a self-configuring data collection system deployed in a supply chain infrastructure facility operated by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a digital twin system representing attributes of value chain network entity controlled by the enterprise. In embodiments, the set of adaptive intelligence facilities includes a smart contract system that is configured to automate a set of interactions among a set of value chain network entities. In embodiments, the set of data storage facilities uses a distributed data architecture. In embodiments, the set of data storage facilities uses a blockchain. In embodiments, the set of data storage facilities uses a distributed ledger. In embodiments, the set of data storage facilities uses a graph database representing a set of hierarchical relationships of value chain network entities. In embodiments, the set of monitoring includes an Internet of Things monitoring system. In embodiments, the set of monitoring facilities includes a sensor system deployed in an infrastructure facility operated by an enterprise. In embodiments, the set of applications includes a set of applications of at least two types from among a set of supply chain management applications, demand management applications, intelligent product applications and enterprise resource management applications. In embodiments, the set of applications includes an asset management application.

In embodiments, the platform manages a set of demand factors, a set of supply factors and a set of supply chain infrastructure facilities.

<div id="p-0047" num="0046" class="description-li

CLAIMS

Claims ( 8 )

What is claimed is:

1 . A value chain system that provides recommendations for designing a logistics system comprising:

a machine learning system that trains a machine-learned model that outputs a logistics design recommendation given a respective set of input features relating to a specific respective logistics system, wherein the machine learning system trains the machine-learned model based on training data sets that define features of logistics systems and outcomes of the logistics systems; an artificial intelligence system that receives a request for logistics system design and determines a logistics system design recommendation based on the machine-learned model 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, wherein the digital twin system: executes a logistics simulation based on the logistics environment digital twin and the one or more physical asset digital twins,

issues a logistics system design request from the artificial intelligence system based on a state of the logistics simulation; and

adjusts the state of the logistics simulation based on the logistics system design recommendation output by the artificial intelligence system in response to the logistics system design request.

2 . The value chain system of claim 1 , wherein the digital twin system outputs a graphical representation of the environment digital twin to a display, whereby a user views the simulation via the display.

3 . The value chain system of claim 1 , wherein the digital twin system outputs a simulation outcome of the simulation to the machine learning system, and the machine learning system reinforces the machine-learned model used to determine the logistics system design recommendation based on the simulation outcome.

4 . The value chain system of claim 1 , wherein the artificial intelligence system receives the request from a logistics design system that designs logistics systems, wherein the request includes one or more logistics factors corresponding to a proposed logistics solution of an organization.

5 . The value chain system of claim 4 , wherein the logistics factors include one or more of: a type of product corresponding to the proposed logistics solution, one or more features of the type of product, a location of a manufacturing site, a location of a distribution facility, a location of a warehouse, a location of a customer base, proposed expansion areas of the organization, and supply chain features.

6 . The value chain system of claim 1 , wherein the logistics design system provides outcome data relating to the logistics system design recommendation to the machine learning system, and the machine learning system reinforces the machine-learned model that are used to determine the logistics system design recommendation based on the outcome data.

7 . The value chain system of claim 1 , wherein the artificial intelligence system determines the logistics system design recommendation to minimize delay times.

8 . The value chain system of claim 1 , wherein the artificial intelligence system determines the logistics system design recommendation to comply with regulatory requirements.

US17/461,351

2019-11-05

2021-08-30

Artificial intelligence system for control tower and enterprise management platform managing logistics system

Pending

US20220058569A1

( en )

Priority Applications (1)

Application Number

Priority Date

Filing Date

Title

US17/461,351

US20220058569A1

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2019-11-05

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