Container Tracking via Machine-Readable Codes
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Solution Overview
Problem
Existing container tracking systems lack the ability to effectively monitor and collect data on containers as they travel through distribution chains, limiting the usefulness of this information for manufacturers and customers.
Innovation Solution
Implementing a system that serializes containers with irremovable machine-readable codes, allowing for data storage and tracking across the distribution chain, using a central server and electronic code readers to collect and analyze data on container manufacture, filling, sale, and reuse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If containers are tracked through distribution chains using machine-readable codes, then data availability and tracking capability are improved, but system complexity and implementation cost increase
Solution Approach 1:
The tracking system is segmented into independent components: machine-readable codes on containers, electronic code readers at distribution points, and a central server for data aggregation. Each component performs a specific function, allowing the system to collect comprehensive tracking data without requiring complete system integration at every stage.
Solution Approach 2:
Containers are pre-encoded with machine-readable codes during manufacturing, establishing the tracking foundation before entering the distribution chain. This preliminary action enables automatic identification and data collection at subsequent distribution points without requiring manual intervention or system reconfiguration.
2Reliability
If machine-readable codes are made irremovable from containers, then code integrity and authentication are improved, but manufacturing complexity increases
Solution Approach 1:
Traditional removable labels or tags are replaced with machine-readable codes that are permanently integrated into the container structure through manufacturing processes. This substitution eliminates the mechanical attachment and detachment steps, making the codes irremovable while actually simplifying the overall manufacturing process by integrating identification directly into container production.
3Loss of information
If comprehensive data is collected from all distribution points, then analytical value and business insights are improved, but data management complexity increases
Solution Approach 1:
A central server acts as an intermediary that receives, standardizes, and aggregates data from multiple distribution points including manufacturers, customers, and sellers. This intermediary consolidates the data management complexity into a single location while providing simplified access to comprehensive data for all stakeholders through unified reports and analytics.
Data Source
AI summary
A method for tracking containers. The method includes manufacturing containers, including forming the containers and serializing them with machine-readable codes. The method further includes using the machine-readable codes to store data associated with the containers, and supplying the containers to a customer. The method still further comprises receiving from the customer, data obtained from customer-readings of the machine-readable codes; and receiving from one or more other locations in a distribution chain in which the containers travel, data obtained from readings of the machine-readable codes at those locations. The method still further comprises comparing the data from the customer-readings and other readings of the machine-readable codes across product brands, product distribution channels, and/or container types, and providing the data to the customer. In at least some embodiments, the method further comprises receiving from the customer a compensation for the containers, for example, a per-refill compensation.