Blockchain Supply Chain Forecasting with Smart Contracts
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Solution Overview
Problem
Current supply chain management systems lack efficient tracking and forecasting capabilities, particularly in ensuring the quality and timely delivery of physical objects, which can lead to inventory discrepancies and failed deliveries.
Innovation Solution
A supply chain forecasting system integrated with blockchain technology, which utilizes hyperspectral imaging and IoT devices to track inventory and quality in real-time, enabling smart contracts for secure and transparent delivery processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional supply chain management systems are used, then implementation is simpler and cost is lower, but tracking accuracy and forecasting capability are insufficient
Solution Approach 1:
The supply chain is divided into discrete blocks on the blockchain, each representing a specific transaction or event. This segmentation allows for precise tracking of individual items through multiple handoffs while maintaining a unified ledger, resolving the contradiction between tracking precision and system complexity.
Solution Approach 2:
The patent introduces hyperspectral imaging technology as an intermediary to objectively measure and verify product quality attributes. This intermediary provides precise measurement data that is then recorded on the blockchain, enabling accurate tracking without requiring complex manual verification systems.
2Measurement precision
If real-time quality monitoring using hyperspectral imaging is implemented, then quality control precision is improved, but energy consumption and device complexity increase
Solution Approach 1:
Hyperspectral imaging is performed at periodic checkpoints throughout the supply chain rather than continuously. This periodic monitoring maintains quality control precision while significantly reducing energy consumption compared to continuous monitoring, as the system only activates imaging at predetermined stages of the supply chain.
3Reliability
If blockchain smart contracts are used for automated delivery, then delivery reliability is improved, but system complexity and implementation cost increase
Solution Approach 1:
Smart contracts are programmed to automatically execute delivery transactions when predefined conditions are met, such as quality thresholds being satisfied or delivery locations being reached. This self-service capability eliminates the need for manual intervention in routine delivery processes, improving reliability while the automation actually reduces operational complexity over time.
Solution Approach 2:
The system incorporates real-time feedback loops where hyperspectral imaging data and location information continuously update the smart contract state. This feedback mechanism ensures that automated decisions are based on current conditions, improving delivery reliability without requiring complex human oversight systems.
4Loss of information
If comprehensive tracking of all supply chain events is implemented, then information completeness is improved, but data processing time and system complexity increase
Solution Approach 1:
The blockchain ledger is pre-configured with the structure and rules for recording supply chain events. Smart contracts are programmed in advance with the logic for automatically capturing and verifying data at each stage. This preliminary setup enables comprehensive information capture without requiring complex real-time processing decisions, thus reducing data processing time while maintaining information completeness.
Data Source
AI summary
A supply chain forecasting system with blockchain controls is discussed. The supply chain forecasting system can include a central computing system communicating with a third party computing system. The central computing system and third party computing system can initiate, adjust, and fulfill smart contracts associated with the delivery of physical objects using blockchain controls.