XR Machine Guidance Using Context-Aware Industrial Data
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Solution Overview
Problem
Existing systems fail to effectively present data to users in industrial environments, often overwhelming or hindering them due to inappropriate amounts or formats of data, which can obstruct task performance and reduce efficiency.
Innovation Solution
A system and method that utilize processing circuitry to receive sensory datasets from industrial automation systems, determine context information, and instruct extended reality devices to present output data in a manner optimized based on the user's context, position, and task requirements, including visual, audio, and haptic feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is presented to assist user task performance, then task guidance is improved, but user overload increases and task performance is hindered
Solution Approach 1:
The system segments data presentation by spatial location, dividing the industrial environment into multiple zones with different data presentation strategies. Each zone presents only the data relevant to tasks performed in that specific location, preventing user overload while maintaining comprehensive task guidance across the entire environment.
Solution Approach 2:
The system applies local quality by tailoring data presentation to specific locations within the industrial environment. Different data types, formats, and densities are presented depending on the user's current location and the tasks being performed in that area, ensuring optimal information delivery without overwhelming the user.
2Ease of operation
If multiple data formats are presented, then user comprehension is improved, but system complexity increases
Solution Approach 1:
The system changes data presentation parameters such as format, density, and modality based on user context and task requirements. By dynamically adjusting these parameters rather than maintaining fixed complex systems for each data type, the system achieves improved user comprehension while managing overall system complexity.
Data Source
AI summary
A non-transitory computer-readable medium includes instructions that, when executed by processing circuitry, are configured to cause the processing circuitry to receive, from first sensors, first sensory datasets associated with an industrial automation system, receive, from second sensors, second sensory datasets associated with a machine configured to perform mechanical operations, determine a position of the machine relative to the industrial automation system based on the first sensory datasets and the second sensory datasets, determine output representative data associated with the industrial automation system based on the first sensory datasets and the second sensory datasets and in accordance with the position of the machine relative to the industrial automation system, instruct an extended reality device to present the output representative data, determine movement of components of the machine, and instruct the extended reality device to present feedback based on the movement of the components.