Industrial Tool Maintenance Using Torque Signatures and AR Guidance
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Solution Overview
Problem
Existing screwdriving and drilling tools in industrial settings suffer from noise in torque measurements due to transmission elements, leading to inaccurate screw fastening and potential tool failure, necessitating inefficient and costly maintenance processes that can disrupt production.
Innovation Solution
A method and system for tool maintenance using a digital twin and augmented reality, where a tool's signature is generated from torque and angle measurements, stored in an RFID chip, and analyzed to identify defects, with augmented reality guidance for maintenance operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional maintenance methods are used (manual inspection, empirical approach), then maintenance can be performed, but it is time-consuming, costly, and prone to unnecessary or delayed interventions
Solution Approach 1:
The system performs preliminary analysis by continuously monitoring tool operation data and comparing it against reference profiles to predict wear and defects before they cause failures. This allows maintenance to be scheduled proactively rather than reactively, improving reliability while optimizing maintenance timing to avoid unnecessary downtime.
Solution Approach 2:
The system creates a digital twin or virtual model of the physical tool that replicates its operational characteristics and wear patterns. By analyzing this digital copy, the system can predict maintenance needs without physically disassembling or testing the actual tool, significantly reducing maintenance time while improving prediction accuracy.
2Measurement precision
If comprehensive tool inspections are performed to accurately identify defects, then maintenance quality improves, but production downtime increases
Solution Approach 1:
The system replaces manual physical inspection with automated sensor-based monitoring and data analysis. Sensors continuously collect operational data (torque, speed, current) and algorithms automatically compare this data against reference profiles to detect defects, eliminating the need for production-stopping manual inspections while maintaining high detection accuracy.
Solution Approach 2:
The monitoring system operates continuously during normal production without interrupting tool operation. Data collection and preliminary analysis occur in real-time alongside manufacturing activities, allowing defect detection to proceed continuously rather than requiring periodic production stoppages for inspection.
3Ease of repair
If manual maintenance procedures are used, then operators can perform maintenance tasks, but the process is lengthy and expensive
Solution Approach 1:
The system provides real-time feedback to operators through mobile devices or control interfaces, displaying diagnostic results, identified defects, and step-by-step maintenance instructions. This feedback loop guides operators through the maintenance process systematically, reducing errors and completing tasks faster while maintaining ease of repair for complex components.
Solution Approach 2:
The system enables a degree of self-service by automatically diagnosing tool conditions and generating maintenance recommendations. Operators receive pre-analyzed diagnostic information and targeted maintenance instructions, allowing them to perform repairs more efficiently without requiring extensive training or prolonged engagement with complex diagnostic procedures.
Data Source
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AI summary
The invention relates to a method for assisting in the maintenance of an industrial tool such as a screwdriver or drill, employing several rotating moving components, comprising the following steps: - obtaining measurement data representative of an angle and/or a torque during use of said tool; - analyzing said measurement data, so as to determine at least one quality data point representative of possible disturbances induced for each of the components of a set of controlled components, delivering a signature of said tool comprising said quality data; - storing said signature in a memory associated with said tool, and readable without contact at short distance; - remotely reading said signature from said memory, using a maintenance assistance terminal; - identifying a component requiring intervention, based on said signature;- obtaining by said terminal assistance information on said intervention to be carried out, including three-dimensional information on said tool; - taking at least one image of said tool, using a camera mounted on said terminal; - displaying an augmented reality representation, using said image(s) and said three-dimensional information, identifying said defective component and/or maintenance operations to be carried out.