Supply Chain Digital Hub for Context-Aware Network Visibility
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Solution Overview
Problem
Current supply chain management systems lack an end-to-end comprehension of supply chain networks and events, leading to fragmented representations and assumptions among different applications, resulting in underperforming or incorrect decisions, especially when collaborating with competitors, and causing broken partnerships and loss of value.
Innovation Solution
A digital hub that integrates inter- and intra-enterprise data with external sources, utilizing machine learning, autonomous intelligent software agents, and natural language processing to provide context-aware insights and support business goal-aware planning, inventory, and capacity sharing, while connecting external data sources for enhanced supply chain visibility and collaboration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If supply chain applications are siloed and isolated behind firewalls, then data security and system independence are maintained, but end-to-end comprehension of supply chain networks is lost and fragmented representations occur
Solution Approach 1:
The patent introduces a digital hub as an intermediary component that sits between siloed supply chain applications and external data sources. This hub aggregates data from multiple isolated systems without requiring them to break their security boundaries, providing end-to-end visibility while maintaining system independence and data security protocols.
Solution Approach 2:
The system segments the supply chain network into discrete data domains that remain isolated behind their respective firewalls, while the digital hub provides a virtual integration layer. This segmentation allows each application to maintain its security boundaries while the hub creates a unified view through controlled data exchange.
2Productivity
If planners collaborate across supply chain entities, then decision-making improves, but inconsistent representations and assumptions lead to underperforming or incorrect decisions
Solution Approach 1:
The digital hub enforces homogeneous data representations and assumptions across all collaborating planners by standardizing data formats, validation rules, and business logic. This ensures that all participants work with consistent representations of supply chain entities, eliminating the inconsistency that leads to poor decision-making.
Solution Approach 2:
The system implements feedback mechanisms that validate and reconcile representations and assumptions across different planning applications. When inconsistencies are detected, the hub provides feedback to planners to resolve conflicts before decisions are made, ensuring alignment across the collaboration network.
3Loss of information
If diverse supply chain data sources are integrated, then holistic visibility is achieved, but system complexity increases
Solution Approach 1:
The digital hub serves as a mediating layer between diverse data sources and end users, abstracting away the complexity of integrating multiple heterogeneous systems. It provides standardized interfaces and data models that simplify access to diverse supply chain data without requiring direct integration between all systems.
Solution Approach 2:
The hub implements universal data models and interfaces that can accommodate diverse supply chain data sources through a common framework. This multi-functional approach allows the same system architecture to handle various data types and sources without proportionally increasing complexity.
Data Source
AI summary
A system and method are disclosed including a digital hub and a cloud database. The digital hub encodes, as a virtual supply chain network, the structure, one or more objectives, and one or more states of a supply chain network and contextualizes data received from one or more supply chain entities and one or more external data sources with the virtual supply chain network. The digital hub further employs machine learning to extract insights from the contextualized data and monitors external data sources for an event that may impact the one or more objectives of the supply chain network. Responsive to identifying an event that may impact the one or more objectives, the digital hub automatically adjusts one or more of robotic warehouse systems, robotic inventory systems, automated guided vehicles, mobile racking units, automated robotic production machinery, and robotic devices.