Industrial Data Contextualization Using Structured Asset Data Types
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Solution Overview
Problem
Industrial automation systems face challenges in collecting and formatting unstructured data from distributed industrial devices for meaningful presentation, requiring developers to define the meaning of each data item, which is burdensome and inefficient.
Innovation Solution
Implementing structured data types, referred to as basic information data types (BIDTs), including state, rate, odometer, and event types, with user-configurable metadata to define and present industrial data in a standardized manner, facilitating integration with automation and non-automation models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If unstructured data from distributed industrial devices is collected and formatted manually by developers, then data can be presented meaningfully, but the process becomes burdensome and inefficient
Solution Approach 1:
The patent applies parameter changes by transforming unstructured industrial data into structured data with standardized parameters and metadata. Each data item is assigned predefined parameters (e.g., state, rate, odometer, event types) that automatically structure the data, eliminating manual formatting efforts and improving data collection efficiency while reducing integration complexity.
Solution Approach 2:
The patent implements universality through a unified data structure and metadata framework that can handle multiple types of industrial data (state, rate, odometer, event) in a consistent manner. This universal approach allows the same data collection and presentation mechanisms to work across diverse industrial devices and data types, significantly reducing the burden on developers and improving overall productivity.
2Adaptability or versatility
If developers define the meaning of each data item manually, then data can be integrated across systems, but the process is time-consuming and inefficient
Solution Approach 1:
The patent applies preliminary action by pre-defining standardized parameters, data types, and metadata structures that can be automatically applied to industrial data. Instead of manually defining each data item's meaning during integration, the system has already prepared the structural framework in advance, allowing rapid data integration while maintaining adaptability across different systems and devices.
Solution Approach 2:
The patent uses parameter changes to transform undefined or loosely-defined data into structured data with explicit meanings. By assigning predefined parameters (state, rate, odometer, event) and metadata to data items, the system automatically defines data meanings without requiring manual intervention, thus reducing time loss while preserving integration versatility.
3Productivity
If industrial data is presented without standardized formatting, then data can be collected quickly, but meaningful presentation and visualization become difficult
Solution Approach 1:
The patent applies parameter changes by automatically assigning standardized parameters and metadata to collected data in real-time. This transformation occurs during the data collection process itself, so data is both collected quickly and simultaneously structured with meaningful context. The parameter assignment happens as part of the collection workflow, preventing information loss while maintaining high collection speed.
Solution Approach 2:
The patent introduces an intermediary layer of standardized parameters and metadata that bridges raw industrial data and meaningful presentation. This intermediary structure is automatically applied during data collection, serving as a mediator that preserves data context and meaning without slowing down the collection process. The standardized parameters act as a universal language that enables both rapid collection and meaningful visualization.
Data Source
AI summary
An industrial data presentation system leverages structured data types defined on industrial devices to generate and deliver meaningful presentations of industrial data. Industrial devices are configured to support structured data types referred to as basic information data types (BIDTs) comprising a finite set of structured information data types, including a rate data type, a state data type, an odometer data type, and an event data type. The BIDTs can be referenced by both automation models of an industrial asset and non-automation models of the asset, allowing data points of both types of models to be easily linked using a common data source nomenclature.