Supplier Factory Location Estimation Using Transaction Relationship Scores

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Solution Overview

Problem

Existing methods require significant manual effort and resources to determine the location of component manufacturing factories by suppliers, hindering effective supply chain risk assessment.

Innovation Solution

An information processing apparatus and method that calculates inter-industry transaction relationship scores to estimate the industry type of a supplier's factory candidates, using component names and model numbers, and selects the most likely factory location based on these scores.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual information collection methods are used to determine factory locations, then information accuracy can be maintained through human verification, but enormous man-hours and resources are required

Engineering Contradiction:

Improvefactory location identification accuracyVSAvoidinformation collection time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical information collection with an automated information processing system that uses transaction relationship scores and industry type estimation algorithms to automatically identify factory locations, eliminating the need for human-wave information collection while maintaining accuracy through systematic data analysis

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces transaction relationship scores as an intermediary metric that connects component information to factory location data. This intermediary enables automated matching between suppliers and their manufacturing facilities without requiring direct manual verification, bridging the information gap efficiently

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If automated estimation methods are implemented, then information collection efficiency is improved, but the complexity of the system increases

Engineering Contradiction:

Improveinformation collection efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the information collection process into distinct functional modules: transaction relationship score calculation, industry type estimation, and factory location selection. This segmentation manages system complexity by organizing automated processes into manageable, independent computational steps that can be executed systematically

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent transforms the information collection approach by changing key parameters from manual verification metrics to automated calculation parameters such as transaction relationship scores and industry type probabilities. This parameter transformation enables automated processing while controlling system complexity through mathematical models rather than complex procedural logic

Inventive Principle:

Principle #35Parameter changes

3Reliability

If comprehensive supplier information is collected, then supply chain risk assessment accuracy is improved, but the resources required for information collection increase significantly

Engineering Contradiction:

Improvesupply chain risk assessment reliabilityVSAvoidinformation resources required

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent extracts only the essential information elements needed for factory location identification (component information, transaction relationships, industry types) from the broader supplier information set. This extraction approach maintains supply chain risk assessment reliability by focusing on critical data points while reducing overall resource requirements

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent creates a multi-functional information processing system that uses the same automated estimation framework for multiple purposes: identifying factory locations, assessing supplier reliability, and evaluating supply chain risks. This universality improves risk assessment reliability through comprehensive analysis while avoiding the need for separate resource-intensive collection processes

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20260065212A1Information processing apparatus and information processing method

Publication Date: 2026.03.05 HITACHI LTD

AI summary

An information processing apparatus includes: a transaction relationship score calculation unit that calculates an inter-industry transaction relationship score indicating a relevance of a transaction relationship among a plurality of industry types; a component supplier industry-type estimation unit that estimates an industry type of a factory candidate of a supplier on a basis of identification information of a component for a factory candidate of a supplier; an industry type similarity calculation unit that calculates an inter-industry transaction relationship score between an industry type of a factory candidate of a supplier and an industry type of a factory candidate of a supplier estimated by the component supplier industry-type estimation unit; and a component manufacturing factory estimation unit that selects a factory candidate of a supplier on a basis of an inter-industry transaction relationship score calculated by the industry type.