Industrial Machine Data Collection via Public Variable Filtering
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Solution Overview
Problem
Current data collection systems for industrial machines lack the ability to distinguish between shared and unshared variables, making it difficult to collect and record data based on sharable public variables, which can lead to unnecessary data collection and potential misuse of sensitive information.
Innovation Solution
A data collection system that allows users to set sharable public variables from a plurality of variables on an industrial machine, enabling selective data collection and recording based on these public variables, while preventing access to non-public variables to maintain confidentiality and reduce unnecessary data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all variables on the industrial machine are collected without distinction, then complete data coverage is achieved, but memory and communication loads increase unnecessarily
Solution Approach 1:
The patent segments variables into public variables (shareable) and non-public variables (confidential). The data collection system selectively collects only public variables that are designated for sharing, rather than collecting all variables. This segmentation resolves the contradiction by reducing the quantity of collected data (lowering memory and communication loads) while still achieving sufficient data coverage for external analysis purposes.
Solution Approach 2:
The patent extracts and isolates only the necessary public variables from the complete set of machine variables for external data collection. By extracting only the shareable subset of variables, the system reduces unnecessary data transmission and storage while maintaining the ability to provide external users with the data they need for analysis.
2Ease of operation
If all variables are made accessible for data collection, then data collection convenience is improved, but sensitive information may be exposed
Solution Approach 1:
The patent divides variables into public and non-public categories, allowing external users to access and collect data from public variables conveniently while automatically preventing access to non-public variables. This segmentation enables ease of operation for legitimate data collection purposes while inherently protecting sensitive information through the public/non-public distinction.
Solution Approach 2:
The patent introduces a public variable list as an intermediary mechanism between the industrial machine and external data collection systems. This intermediary structure allows external users to selectively access only authorized public variables through a controlled interface, maintaining convenience while preventing unauthorized access to sensitive non-public variables.
3Loss of energy
If public variables are designated and selectively collected, then unnecessary data transmission is reduced, but system complexity increases
Solution Approach 1:
The patent implements a universal public variable list structure that can be applied across different industrial machines and data collection scenarios. This standardized approach allows the same public variable designation mechanism to work universally, reducing the need for custom solutions and actually simplifying implementation despite the added functionality of selective variable collection.
Data Source
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AI summary
A public variable setting module (101) of a data collection system (1) is configured to set a sharable public variable from among a plurality of variables of an industrial machine (30) controlled by a control device (20). A collection module (204) is configured to collect data on the industrial machine (30) based on the public variable. A recording module (501) is configured to record the data in a storage.