Industrial Machine Data Collection Using Sharable Public Variables

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Solution Overview

Problem

Current data collection systems for industrial machines lack the ability to distinguish between shared and unshared variables, leading to unnecessary data collection and potential exposure of proprietary information.

Innovation Solution

A data collection system that sets sharable public variables from among the industrial machine's variables, allowing only these selected variables to be collected and recorded, thereby preventing the collection of non-public data and reducing data volume and processing load.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If all variables of the industrial machine are collected, then complete data is obtained for analysis, but memory consumption and processing load increase unnecessarily

Engineering Contradiction:

Improvedata completenessVSAvoiddata volume

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The system extracts only the necessary public variables from the complete set of machine variables for data collection. By identifying and separating public variables (those needed for analysis) from non-public variables (proprietary or unnecessary data), the system collects only the required portion of data, reducing data volume while maintaining analysis capability.

Inventive Principle:

Principle #2Taking out (Extraction)

2Reliability

If all variables are collected and transmitted, then comprehensive monitoring is achieved, but communication load increases

Engineering Contradiction:

Improvemonitoring coverageVSAvoidcommunication load

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system extracts and transmits only public variables over the communication network. By filtering out non-public variables at the source, the communication load is reduced significantly while the monitoring coverage for essential parameters remains intact.

Inventive Principle:

Principle #2Taking out (Extraction)

3Adaptability or versatility

If no variable filtering is applied, then all data is available for analysis, but proprietary information may be exposed

Engineering Contradiction:

Improvedata availabilityVSAvoidinformation security risk

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The system extracts and identifies public variables that are safe to share, separating them from non-public variables that contain proprietary or sensitive information. This extraction process enables data availability for analysis while preventing exposure of confidential machine details.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Different variables are assigned different security qualities - public variables are made available for external access and analysis, while non-public variables remain protected within the machine's control system. This local differentiation of data accessibility maintains security while enabling necessary analysis.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11340590B2Data collection system, data collection method, and information storage medium

Publication Date: 2022.05.24 YASKAWA DENKI KK

AI summary

A data collection system, comprising circuitry configured to: set a sharable public variable from among a plurality of variables of an industrial machine controlled by a control device; collect data on the industrial machine based on the public variable; and record the data in a first storage.