Demand-Supply Inference for Shared Container Specifications

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Solution Overview

Problem

Existing inventory management systems for products in distribution networks struggle to accurately predict consumer demand and supply for containers with identical specifications used across multiple content types, leading to unstable distribution and inefficient production planning.

Innovation Solution

An information processing device that acquires web access information from containers to determine consumer preferences and generates demand-supply information using a machine learning model, allowing for stable distribution by predicting consumer demand and supply for containers with identical specifications.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If container identification codes are used for product management in distribution networks, then inventory management and sales tracking can be performed, but consumer demand prediction and supply planning accuracy deteriorate when identical containers are used for multiple content types

Engineering Contradiction:

Improvedemand prediction accuracyVSAvoidinformation management complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the information management system into two parts: the physical container identification code (which remains simple) and the virtual content-type-specific information layer (which enables precise demand prediction). By separating container identity from content type association, the system achieves both simplicity and accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary information storage carrier (such as a database or digital tag) that links container identification codes with content type information. This intermediary enables accurate demand prediction by associating containers with specific content types without complicating the physical container structure.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If identical containers are used for multiple content types in high-mix low-volume production, then production flexibility improves, but distribution stability deteriorates due to inability to distinguish content-specific demand

Engineering Contradiction:

Improveproduction flexibilityVSAvoiddistribution stability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent segments container identification into two independent dimensions: physical container identity (for tracking) and content type association (for demand prediction). This segmentation allows the same physical container to be reliably associated with different content types, maintaining both production flexibility and distribution stability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the information parameters associated with containers from static identification codes to dynamic content-type-linked information. By adding the content type parameter, the system can distinguish demand patterns for different contents while using identical physical containers, enabling reliable distribution planning.

Inventive Principle:

Principle #35Parameter changes

3Ease of operation

If traditional barcode or IC tag systems are used for container management, then basic tracking is achieved, but consumer preference information and demand prediction capabilities are lost

Engineering Contradiction:

Improvecontainer tracking simplicityVSAvoidconsumer preference information

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The patent makes the information storage carrier universal by designing it to serve multiple functions: basic container tracking (original function) and consumer preference information storage (new function). The same information carrier that tracks container movement now also stores content type associations and consumer preference data, eliminating information loss while maintaining operational simplicity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250356382A1Information processing device, inference device, machine learning device, information processing method, inference method, and machine learning method

Publication Date: 2025.11.20 TOYO SEIKAN GRP HLDG LTD

AI summary

Provided is information processing device, which includes: an information acquisition unit that acquires acquisition information as network information related to a prediction target container based on web access information included in an information storage carrier attached to a container to be filled with a content and thus constituting a product; and a generation processing unit that generates demand-supply information corresponding to the network information of the prediction target container when the network information acquired by the information acquisition unit related to the prediction target container is input to a learning model trained by machine learning with a correlation between the network information of a training target container and demand-supply information including, for each of the types of the contents, information related to demand or supply of the product in which the different container having the specification identical to the specification of the container has been filled.