Automated Drill Bit Grading via 3D Model Comparison
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Solution Overview
Problem
Conventional grading techniques for drill bits in the petroleum industry are inefficient and subjective, particularly for new oil field personnel, as they rely on manual, visual methods that can lead to inconsistent results and difficulty in understanding grading codes for worn or damaged bits.
Innovation Solution
An automated system using 3D feature recognition and computer-implemented methods to scan drill bits from multiple angles, generate 3D numerical models, and compare them to product specification models, determining product type, condition, and generating inspection reports that classify bits as re-runnable, repairable, or junk, thereby reducing subjectivity and improving compliance and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual visual inspection methods are used for bit grading, then personnel can physically examine the bits, but the process is subjective and produces inconsistent results
Solution Approach 1:
The patent replaces manual visual inspection with an automated 3D scanning system that uses optical sensors to capture geometric data. The mechanical and human-based grading process is substituted with an automated computational system that objectively measures bit wear and generates consistent grading results without human subjectivity.
Solution Approach 2:
The patent creates a digital 3D copy of the bit through scanning, storing geometric data in a database. This digital replica allows for objective comparison against specification models, eliminating the need for personnel to physically handle and interpret complex grading codes while maintaining consistent, repeatable measurements.
2Measurement precision
If automated 3D scanning is used for product inspection, then inspection objectivity and precision are improved, but device complexity and initial costs increase
Solution Approach 1:
The patent divides the inspection process into discrete functional modules: scanning module, data processing module, comparison module, and reporting module. Each module performs a specific function, making the overall complex system more manageable and easier to implement incrementally while maintaining high measurement precision through standardized 3D geometric analysis.
3Productivity
If manual inspection processes are used, then personnel can perform inspections, but time and labor costs increase
Solution Approach 1:
The system performs self-service inspection by automatically scanning bits, comparing them against stored specification models, and generating inspection reports without requiring skilled personnel intervention. The automated system independently completes the entire inspection workflow, dramatically increasing productivity while eliminating time-consuming manual grading processes.
Data Source
AI summary
Systems and methods include a computer-implemented method for automating product inspection processes. A product is scanned using multiple scans obtained from different angles. A 3D numerical model of the product is generated. The 3D numerical model is compared to 3D product specification models, each numerically defining specifications for a given product in new condition. The 3D numerical model is matched to a matched 3D product specification model. A product type of the product is determined. A report is generated based on comparisons of the 3D numerical model and the matched 3D product specification model. For a new product, the report includes an indication of whether the new product matches design specifications for new products of the product type. For a used product, the report includes an indication of a used condition of the used product relative to a new condition of new products of the product type.