Neural IoT Edge Architecture for Legacy PLC Replacement

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Solution Overview

Problem

Legacy programmable logic controllers (PLCs) in industrial environments face challenges such as spare part unavailability, proprietary programming issues, and skill loss, making replacement and maintenance costly and time-consuming, especially with the transition to Industry 4.0.

Innovation Solution

A distributed neural Internet of Things (IoT) edge architecture that integrates IoT devices as digital interfaces and neural nodes, forming an artificial neural network to learn and replicate PLC behavior, allowing for seamless replacement and integration into Industry 4.0 systems without additional wiring, enabling autonomous configuration and fail-safe operation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If legacy PLCs are replaced with new PLCs, then system reliability is improved, but replacement cost and downtime increase due to proprietary programming and lack of spare parts

Engineering Contradiction:
Improvesystem reliabilityVSAvoidreplacement downtime
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent creates a digital twin of the legacy PLC by having the new PLC learn and replicate the behavior, I/O states, and control logic of the aging PLC through monitoring and emulation, enabling replacement without proprietary programming knowledge

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The new PLC is configured and trained to replicate legacy PLC behavior before the actual replacement occurs, allowing for seamless switchover and minimizing downtime by having the replacement system ready in advance

Inventive Principle:
Principle #10Preliminary action

2Device complexity

If a single PLC is used to control all I/O, then device complexity is reduced, but processing capacity and adaptability are limited

Engineering Contradiction:
Improvecontrol system complexityVSAvoidprocessing capacity
Core Design Contradiction:
Device complexityVSAdaptability or versatility

Solution Approach 1:

The patent divides the control system into multiple distributed PLCs, each responsible for specific I/O groups or functional areas, allowing parallel processing and improved adaptability while maintaining manageable complexity through modular architecture

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

Each PLC in the distributed system is designed to be multi-functional, capable of handling various I/O types and control tasks, enabling flexible reconfiguration and scaling of the control system as needs change

Inventive Principle:
Principle #6Universality (Multi-functionality)

3Ease of operation

If additional wiring infrastructure is installed for new PLCs, then I/O connectivity is improved, but installation complexity and cost increase

Engineering Contradiction:
ImproveI/O connectivityVSAvoidwiring infrastructure
Core Design Contradiction:
Ease of operationVSDevice complexity

Solution Approach 1:

The patent introduces communication modules and protocols as intermediaries between PLCs and I/O devices, enabling digital communication over existing infrastructure and eliminating the need for additional physical wiring while maintaining connectivity

Inventive Principle:
Principle #24Intermediary (Mediator)

4Adaptability or versatility

If loT devices are integrated in series with existing ICS, then scalability is improved, but device complexity increases

Engineering Contradiction:
ImprovescalabilityVSAvoidsystem architecture
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system is segmented into independent, modular loT devices that can be individually added or removed from the control system, each handling specific sensing or actuation functions, enabling scalable expansion without increasing overall system complexity

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The loT devices are designed with autonomous configuration and self-integration capabilities, automatically registering with the control system and configuring their parameters without requiring complex manual setup, thereby reducing the complexity burden of scalability

Inventive Principle:
Principle #25Self-service

Data Source

PatentEP4312094A1Connecting system comprising a device configuration for an artificial neural network
Publication Date: 2024.01.31 GISH CHARLES
  • EP4312094A1 patent drawingFigure 1
  • EP4312094A1 patent drawingFigure 2
  • EP4312094A1 patent drawingFigure 3

AI summary

Proposed is a connecting system with a connection and configuration of a device between an industrial control system (ICS) and each sensor and actuator in a plant or a machine, in which loT devices are connected between the ICS and each sensor and actuater, at the physical locations of each sensor and actuator in the plant or machine.