Numerical Controller Resource Scaling for Machining Accuracy
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Solution Overview
Problem
Manufacturers of production machines are limited by the performance capabilities of their numerical controllers, making it costly and impractical to upgrade for increased machining accuracy or performance, as replacing controllers with more powerful ones is expensive and using less powerful ones restricts machining time.
Innovation Solution
An operating method that dynamically enables or disables resources such as processor cores, threads, cache, memory, and external computing power within the numerical controller, allowing manufacturers to scale performance based on unlock codes and usage requirements, enabling more powerful controllers to be used efficiently and cost-effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a more powerful numerical controller is used to achieve higher machining accuracy and performance, then machining accuracy and performance are improved, but acquisition costs and commissioning outlay increase considerably
Solution Approach 1:
The patent implements dynamic resource allocation by enabling or disabling processor cores, threads, cache, and memory based on operational requirements. This allows the controller to adapt its performance characteristics in real-time, providing high performance when needed while maintaining lower operational states during routine tasks, thereby resolving the contradiction between achieving high machining accuracy and avoiding excessive device complexity costs
Solution Approach 2:
The system changes operational parameters by modifying which hardware resources are active (processor cores, memory allocation, cache size) based on the specific machining task requirements. This parameter adjustment allows the same physical hardware to deliver varying levels of performance, enabling high machining accuracy when required without permanently requiring a high-performance configuration that would increase acquisition costs
2Productivity
If a more powerful numerical controller is used to reduce interpolation time and increase productivity, then productivity is improved, but acquisition costs and commissioning outlay increase considerably
Solution Approach 1:
The controller dynamically adjusts its operational capacity by activating additional processor cores, increasing memory allocation, or expanding cache resources when high-speed machining is required. This dynamic scaling allows the system to achieve high productivity temporarily without requiring permanent investment in a high-performance controller configuration
Solution Approach 2:
The patent makes a single controller configuration serve multiple performance levels by enabling it to operate in different modes (standard performance, high performance, maximum performance) depending on the machining task. This multi-functionality allows the same hardware to deliver both cost-effective routine operation and high-productivity performance when needed
3Device complexity
If a less powerful numerical controller is used to reduce acquisition costs, then acquisition costs are reduced, but machining time increases and performance is restricted
Solution Approach 1:
The system performs preliminary assessment of the machining task requirements and pre-configures the appropriate hardware resources before execution. By anticipating when high-performance capabilities will be needed and preparing the controller configuration in advance, the system可以避免 delays while still using a cost-effective base configuration for routine operations
4Productivity
If numerical controller resources are always fully enabled to provide maximum performance, then productivity and machining accuracy are improved, but acquisition costs and energy consumption increase
Solution Approach 1:
The controller implements dynamic resource management by activating only the necessary processor cores, memory segments, and cache resources required for the current machining task. This dynamic allocation ensures that energy-consuming components are active only when needed, reducing overall energy consumption while maintaining high productivity when required
Solution Approach 2:
The system applies partial resource allocation by enabling only the specific subset of hardware resources needed for each task rather than all available resources. This partial action approach provides sufficient performance for each specific operation while avoiding the energy consumption and costs associated with having all resources permanently active
Data Source
AI summary
A system program monitors a numerical controller executing a useful program controlling a machine. The numerical controller determines target values for position-controlled axes and controls the position-controlled axes in accordance with the target values. The numerical controller stores resources and determines whether, and optionally to which extent, the resources are enabled or disabled. Enabling or disabling the resources specifies how many processor cores are enabled for use, or how many processor threads are enabled for use, or to what extent a processor cache or a processor main memory are enabled for use, or which hardware components of the numerical controller are enabled for use, or to what extent use of external computing power is permitted. The numerical controller determines the target values for the position-controlled axes using only the enabled resources.