CNC Datum Selection for Accurate Group Hole Machining
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Solution Overview
Problem
Current methods for selecting a datum in group hole machining of large components, particularly in aircraft assembly, fail to minimize hole position errors due to geometric and positioning errors in multi-axis CNC machine tools, affecting machining accuracy and efficiency.
Innovation Solution
A datum selection method that determines the type of CNC machine tool using IoT sensing data, establishes a topological structure, and calculates a machining datum by creating a hole position error model and average error model to minimize positional errors through partial derivations and Lagrangian functions, tailored for skeleton and skinned group hole machining.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional manual drilling methods are used, then ease of operation is maintained, but manufacturing precision deteriorates
Solution Approach 1:
The patent replaces manual drilling operations with multi-axis CNC machine tools that utilize sensor feedback and automated control systems. IoT sensors monitor the machining process in real-time, and the control system automatically adjusts machining parameters to maintain high precision without requiring manual intervention, thus improving hole position accuracy while maintaining operational ease.
Solution Approach 2:
The patent implements feedback mechanisms through IoT sensors that continuously monitor machining parameters such as tool position, cutting forces, and vibration. This real-time feedback enables the control system to detect and correct deviations from the intended hole positions, thereby improving manufacturing precision through closed-loop control.
2Manufacturing precision
If multi-axis CNC machine tools are used, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex multi-axis CNC machine tool system into modular functional units, each equipped with dedicated IoT sensors and control modules. This segmentation allows for independent optimization and maintenance of each module, reducing overall system complexity while maintaining high machining precision through coordinated operation of the segmented components.
Solution Approach 2:
The patent implements a universal control architecture that manages multiple axes and sensing functions through a single integrated control system. This multi-functional approach reduces device complexity by eliminating the need for separate control systems for each axis, while still achieving high group hole machining accuracy through coordinated multi-axis operation.
3Manufacturing precision
If motion range is increased to cover large component contours, then adaptability is improved, but manufacturing precision deteriorates
Solution Approach 1:
The patent introduces a temporal dimension to the machining process by implementing real-time error compensation that dynamically adjusts machining parameters during operation. This allows the system to maintain high hole position accuracy across large component contours by continuously compensating for errors that accumulate over extended motion ranges, effectively adding a time-based correction layer to the spatial machining process.
Solution Approach 2:
The patent dynamically changes machining parameters such as feed rate, spindle speed, and tool path interpolation based on real-time sensor feedback and predicted error models. This parameter adaptation allows the system to maintain high manufacturing precision across varying motion ranges and component sizes by optimizing parameters for each specific machining condition.
Data Source
AI summary
Embodiments of the present disclosure provide a datum selection method for minimizing hole position errors in group hole machining of large components, comprising: 1) determining a type of a computer numerical control (CNC) machine tool and establishing a topological structure of the CNC machine tool; 2) establishing a theoretical postural model of a tool center point during a motion; 3) establishing a hole position error model; 4) establishing an average error model of hole positions in group hole machining; and 5) obtaining a machining datum for group holes of corresponding components. For the skeleton and skinned group hole machining of aircraft components, different principles of datum selection are provided respectively, which can effectively improve the positional accuracy of the skeleton or skinned group hole machining, at the same time provides a more scientific and reasonable approach for the datum selection in group hole machining of large components.