QCS Scanner Mixed Reality Guidance for Safer Troubleshooting
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Solution Overview
Problem
The installation, maintenance, and troubleshooting of Quality Control System (QCS) scanners require skilled expertise due to handling of radioactive sources and precise procedural steps, leading to a competency gap as experienced personnel retire, and training is time-consuming and physically dependent.
Innovation Solution
Implementing a 360° assistance system using mixed reality (MR) and machine learning technology, which includes an optical sensor, display, and processor to diagnose issues, guide users to affected parts, and provide necessary steps for resolution, leveraging augmented and virtual reality for training and interactive troubleshooting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional training methods using physical scanners are used, then training effectiveness is improved, but training time and costs increase
Solution Approach 1:
The patent creates virtual copies of physical scanners and training environments using VR/AR technology. These digital twins replicate the actual scanner interfaces, components, and operational procedures, allowing trainees to practice on identical virtual representations without consuming physical resources or requiring access to actual equipment.
Solution Approach 2:
The patent transitions training from the physical three-dimensional space to a virtual/digital dimension. By immersing users in virtual environments that overlay or replace physical spaces, the system enables training in an additional dimensional realm where time and physical constraints are relaxed while maintaining procedural fidelity.
2Measurement precision
If expert troubleshooting is used, then issue identification accuracy is improved, but response time varies and expertise is scarce
Solution Approach 1:
The system enables scanners and field devices to perform self-diagnosis and self-reporting of issues. Automated monitoring mechanisms detect problems and communicate them directly to the platform, eliminating the need for manual inspection and enabling immediate, accurate issue identification without human intervention.
Solution Approach 2:
The patent implements continuous feedback loops where diagnostic data from scanners flows automatically to the AI platform, which analyzes the information and provides real-time guidance. This closed-loop system ensures accurate issue detection through automated data collection, analysis, and verification, reducing reliance on human expertise while maintaining high accuracy.
3Measurement precision
If physical presence for guidance is used, then troubleshooting accuracy is improved, but mobility and accessibility decrease
Solution Approach 1:
The patent replaces physical presence and mechanical guidance with digital communication channels and virtual reality interfaces. Instead of requiring experts to physically travel to and manually guide operators at the scanner location, the system uses augmented reality overlays, virtual walkthroughs, and digital annotation tools to provide precise guidance remotely, maintaining accuracy while eliminating mobility constraints.
4Reliability
If comprehensive training programs are implemented, then skill level is improved, but training costs and complexity increase
Solution Approach 1:
The patent implements adaptive, dynamic training programs that automatically adjust content, difficulty, and pacing based on individual learner performance and progress. The system dynamically modifies training scenarios, provides real-time feedback, and adapts the curriculum to match the user's skill level, eliminating the need for complex static program structures while maintaining comprehensive skill development.
Data Source
AI summary
An apparatus, method, and non-transitory machine-readable medium provide for 360° assistance for a QCS scanner with mixed reality (MR) and machine learning technology. The apparatus includes an optical sensor, a display, a Chatbot, cloud service, and a processor operably connected to the optical sensor and the display. The processor receives diagnostic information from a server related to a field device in an industrial process control and automation system; identifies an issue of the field device based on the diagnostic information; detects, using the optical sensor, the field device corresponding to the identified issue; guides, using the display, a user to a location and a scanner part of the field device that is related to the issue; provides, using the display, necessary steps or actions to resolve the issue; and connects, using a cloud server, a user to get modules of installation, commissioning, annual maintenance (AMC) and training for a quality control system (QCS) as per the selected persona.


