Carrier Identification System for Supply Chain Optimization
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Solution Overview
Problem
Modern supply chain systems face inefficiencies due to multiple carriers using different tracking and monitoring systems, leading to slow and inefficient transportation processes.
Innovation Solution
A system and method for carrier identification and optimization, utilizing a computing device to receive, verify, and update carrier data based on a transport plan, and arrange carriers into optimized groups using a carrier group optimization model that includes machine learning and ranking systems to compare and score carrier groups for optimal performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple carriers use different tracking and monitoring systems, then each carrier can independently manage its transportation, but the overall supply chain efficiency decreases and transportation processes become slow
Solution Approach 1:
The patent combines multiple independent carrier tracking systems into a single unified tracking and monitoring platform. This allows data from different carriers to be aggregated and processed centrally, improving overall supply chain efficiency while maintaining the ability to track and manage individual carrier operations through the integrated system.
Solution Approach 2:
The unified tracking system serves multiple carriers simultaneously with a single platform, providing universal functionality across different transportation providers. The system can identify, track, and monitor multiple carriers using different identification methods (OCR, manual entry, barcode scanning) within one integrated infrastructure, eliminating the need for separate systems for each carrier.
2Productivity
If a unified tracking system is implemented across multiple carriers, then supply chain efficiency improves, but the system complexity increases
Solution Approach 1:
The system introduces a central computing device as an intermediary that handles the complexity of unified tracking. This computing device receives identification data from various sources (OCR scans, manual entries, barcodes), processes the information, and manages carrier groupings. By concentrating the complex processing logic in a single intermediary system, individual carriers can participate with simpler local devices while still benefiting from unified tracking capabilities.
Solution Approach 2:
The system uses optical character recognition (OCR) to create digital copies of carrier identification information from physical documents or labels. This copying mechanism allows the system to capture and process carrier data automatically without requiring complex physical interaction with carriers, simplifying the tracking process while maintaining accuracy.
3Loss of time
If carriers are arranged into optimized groups using machine learning, then transportation time and cost reduce, but the computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary carrier identification and data collection using OCR and other methods before optimization is needed. By having carrier information pre-captured and stored in the database, the machine learning optimization process can quickly retrieve and process this pre-prepared data when grouping carriers, reducing the overall computational burden and processing time required for optimization decisions.
Data Source
AI summary
In an aspect, a system for transport verification is disclosed. A system includes a computing device. A computing device is configured to receive at least a carrier datum from a carrier device. A computing device is configured to verify at least a carrier datum as a function of a transport plan. A computing device is configured to update at least a carrier datum as a function of a verification of a transport plan. A computing device is configured to display an updated at least a carrier datum through a carrier device.