Self-Learning Field Device Profiles for Faster Configuration

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Solution Overview

Problem

Current methods for managing field devices require high user familiarity and complex handheld tools, leading to a cumbersome and error-prone process, as users need to manually select device versions, traverse multiple configuration menus, and wait for failure messages to identify issues.

Innovation Solution

An interactive profile-based self-learning program module installed on a computing device automatically identifies field devices, provides management options, predicts potential failures, and corrects user inputs, reducing the need for extensive user knowledge and manual menu navigation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If a complex handheld tool is used to manage field devices, then device management functionality is comprehensive, but user operation complexity increases and requires high user familiarity

Engineering Contradiction:

Improvedevice management functionalityVSAvoiduser operation complexity

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system performs automatic device identification and self-learning by analyzing device responses to test commands, eliminating the need for users to manually configure device parameters. The system automatically builds device models and generates management strategies without requiring deep user expertise about the field device

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The computing device acts as an intermediary between the user and the field device, handling all complex communication and configuration tasks. The user interface provides simplified options while the computing device manages the complex interactions with the field device in the background

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If manual device identification and configuration menu traversal is required, then precise device management is achieved, but time consumption increases

Engineering Contradiction:

Improvedevice identification accuracyVSAvoiddevice management time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary device identification by sending test commands and analyzing device responses before actual management operations. The computing device pre-builds device models and identifies device types, versions, and capabilities automatically, so that when management operations are needed, the device is already characterized and ready for efficient management

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces manual mechanical navigation through configuration menus with automated electronic identification. The computing device uses software-based device fingerprinting and profile matching to identify devices, eliminating the need for users to manually traverse configuration menus while maintaining accurate device identification

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Manufacturing precision

If users manually select device versions and navigate configuration menus, then precise device configuration is achieved, but user error probability increases

Engineering Contradiction:

Improvedevice configuration accuracyVSAvoiduser input error rate

Core Design Contradiction:

Manufacturing precisionVSReliability

Solution Approach 1:

The system continuously monitors user inputs against the automatically generated device model and management strategy. When errors are detected in user inputs, the system provides real-time feedback and corrections, ensuring that the final device configuration is accurate even if the user makes initial mistakes. The system validates inputs against device capabilities and constraints

Inventive Principle:

Principle #23Feedback

4Adaptability or versatility

If comprehensive device management options are provided, then management capability is enhanced, but interface complexity increases

Engineering Contradiction:

Improvemanagement capabilityVSAvoidinterface complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The user interface is segmented into contextual sections based on the current device state and user needs. Instead of presenting all possible management options simultaneously, the interface divides functionality into manageable segments that are revealed progressively as the user interacts with the system, reducing cognitive load while maintaining comprehensive capability

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11853773B2Interactive profile-based self-learning application for smart field devices

Publication Date: 2023.12.26 HONEYWELL INTERNATIONAL INC

AI summary

Aspects of the disclosure relate to computer hardware and software for managing a field device (e.g., a transmitter, an actuator, a valve, a switch, a sensor, a power supply, a meter, or the like, used in one or more pieces of equipment that process one or more input chemicals to create one or more products in a chemical plant, a petrochemical plant, a refinery, or the like) by using an interactive automation/self-learning program module installed in a computing device (e.g., a mobile device). Some aspects of the disclosure provide techniques that may enable a computing device to connect to a field device; automatically identify the field device; provide guidance to manage the connected field device; receive input corresponding to the guidance; and/or manage the field device based on the input.