Machine Tool Numeric Control for Adaptive Safety Distance
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Solution Overview
Problem
Current methods for selecting a safety distance in numerical control of machine tools are inefficient, leading to potential losses in cycle time and throughput due to either excessive safety distances or risks of tool damage from insufficient distances.
Innovation Solution
A method utilizing a trained neural network to determine the optimal minimum distance between the tool and the workpiece by analyzing numerical tool information, including spindle torque and axis positions, to improve cycle time and prevent tool damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large safety distance is selected, then tool damage is prevented, but cycle time increases and throughput decreases
Solution Approach 1:
The patent implements dynamic adjustment of the safety distance based on real-time machining conditions, workpiece geometry, and tool position. Instead of using a fixed conservative safety distance throughout the entire machining process, the system continuously adapts the safety margin to match the actual requirements at each moment, allowing minimal safe distances during critical phases and larger distances only when necessary, thereby optimizing both tool protection and cycle time
Solution Approach 2:
The system employs feedback mechanisms by monitoring machining progress, tool position, and workpiece characteristics to continuously adjust the safety distance. The control system receives information about the current machining state and modifies the safety margin accordingly, ensuring tool safety while minimizing unnecessary idle time during non-critical phases of the machining cycle
2Productivity
If a small safety distance is selected, then cycle time is reduced and throughput increases, but tool damage risk increases
Solution Approach 1:
The system dynamically adjusts safety distance based on real-time machining conditions, using minimal distances during phases where collision risk is low and increasing distances only when geometric conditions or tool positions indicate potential risks, thereby optimizing cycle time without compromising tool safety
Solution Approach 2:
The system performs preliminary analysis of the workpiece geometry and machining path before execution to pre-determine optimal safety distances for different phases of the machining process. This advance planning allows the system to minimize safety margins during safe phases while preparing appropriate buffers for potentially critical sections, reducing overall cycle time while maintaining tool protection
3Ease of operation
If fixed safety distance is used, then programming is simplified, but machining efficiency is reduced due to excessive idle time
Solution Approach 1:
The patent implements dynamic safety distance adjustment that automatically adapts to different machining phases and geometric conditions. The system transitions from static, manually-programmed fixed distances to dynamically calculated variable distances based on real-time parameters such as tool position, workpiece geometry, and machining phase, thereby eliminating excessive idle time while maintaining operational simplicity through automated control
Solution Approach 2:
The system performs self-adjustment of safety distances by automatically analyzing machining conditions and modifying parameters without requiring manual intervention or complex programming. The control system serves itself by continuously optimizing safety margins based on embedded geometric models and real-time feedback, freeing operators from complex programming tasks while maximizing machining efficiency
Data Source
AI summary
A computer-implemented method for optimizing a numerical control of a machine tool having a tool for machining a workpiece may include obtaining numerical tool information with respect to a machining. The method may further include acquiring, by a trained neural network, timing information based on the obtained tool information and generating a set of path information for machining from the timing information and the tool information. The set of path information may include a travel path of the tool, which may include an approach, tool entry, working, and tool exit phase, and a distance between the tool and the workpiece before the approach phase. The method may include determining a minimum distance between the tool and the workpiece before the approach phase from a plurality of sets of path information of a plurality of previous machinings for a next machining.