AI Hardware Configuration for Adaptive Manufacturing Planning

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Solution Overview

Problem

Current manufacturing systems lack an efficient method to determine optimal hardware configurations for manufacturing processes, leading to inefficiencies and increased operational costs due to the need for manual selection and re-training of AI systems with hardware changes.

Innovation Solution

A manufacturing support system utilizing an AI engine that obtains object data to determine hardware configurations and manufacturing process steps, incorporating a machine learning device and hardware information processing unit to identify required hardware elements, allowing for efficient updates without re-training the AI.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual selection and configuration of manufacturing hardware is performed based on operator experience, then flexibility in handling diverse manufacturing needs is maintained, but time consumption and operational costs increase

Engineering Contradiction:

Improvemanufacturing process efficiencyVSAvoidtime for hardware configuration

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual operator-based hardware configuration with an automated AI engine that processes manufacturing data and determines optimal hardware configurations. The system substitutes human decision-making with machine learning algorithms that analyze manufacturing requirements and automatically select appropriate hardware, thereby eliminating time loss associated with manual configuration while maintaining or improving manufacturing efficiency

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The AI engine performs self-learning and self-adjustment by automatically adapting to hardware changes without requiring external re-training. The system serves itself by autonomously updating its hardware configuration recommendations based on new hardware information, eliminating the need for manual intervention or external expertise when hardware inventory changes

Inventive Principle:

Principle #25Self-service

2Reliability

If AI systems are re-trained whenever hardware changes occur, then accuracy of hardware configuration recommendations is maintained, but operational costs and time consumption increase

Engineering Contradiction:

Improveaccuracy of hardware configuration determinationVSAvoidcost and complexity of system maintenance

Core Design Contradiction:

ReliabilityVSEase of manufacture

Solution Approach 1:

The patent implements a dynamic system where the AI engine automatically adapts to hardware changes through real-time information processing rather than periodic re-training. The system dynamically updates its hardware configuration recommendations based on current hardware availability information, maintaining reliability without requiring costly and time-consuming re-training cycles. This dynamic adaptation mechanism allows the system to remain accurate while being easy to maintain

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent introduces a hardware information database as an intermediary layer between the physical hardware inventory and the AI engine. This database stores hardware information and serves as a mediator that automatically updates the AI engine when hardware changes occur, eliminating the need for direct re-training of the AI system. The intermediary database maintains data accuracy while simplifying system maintenance and reducing operational costs

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If comprehensive hardware information is stored and processed, then accuracy of hardware configuration determination is improved, but system complexity increases

Engineering Contradiction:

Improveprecision of hardware configuration determinationVSAvoidcomplexity of hardware information management

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the hardware information management system into distinct functional modules: a hardware information database for storage, an AI engine for processing, and separate input/output interfaces. This segmentation allows comprehensive hardware information to be managed systematically without overwhelming system complexity. Each module handles specific aspects of hardware information, making the overall system manageable while maintaining high precision in hardware configuration determination

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11454956B2Manufacturing support system and method

Publication Date: 2022.09.27 OMRON CORP

AI summary

A manufacturing support system may be provided. The manufacturing support system may comprise: an obtaining unit (IO) configured to obtain object data of an object to be manufactured; an artificial intelligence, Al, engine (20) configured to receive the object data as an input and to determine a hardware configuration of a manufacturing system for manufacturing the object with reference to information relating to available hardware for the manufacturing system; and an output unit (60) configured to output the determined hardware configuration.