Numerical Control API Processing Period Estimation
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Solution Overview
Problem
Numerical control apparatuses face challenges in screen updates during heavy CPU-load operations, leading to delayed responses and timeouts, which affect operator usability and reliability, as existing solutions do not adequately address the CPU load on the data preparation side.
Innovation Solution
An API is developed that estimates process completion times based on CPU load, allowing for timely data acquisition and screen updates by defining upper-limit CPU loads for each API function and monitoring CPU usage, with error handling to prevent process execution when deadlines cannot be met, and notifying the HMI to manage display updates accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the CPU is allocated more time for motion control tasks during heavy-CPU-load operation, then motion control precision and speed are improved, but screen update frequency and HMI response time deteriorate
Solution Approach 1:
The system performs preliminary actions by predicting API processing completion times before actual execution. The prediction unit estimates how long API functions will take based on current CPU load, allowing the HMI to proactively plan display updates and avoid timeouts rather than reactively responding to delays.
Solution Approach 2:
The system dynamically adjusts HMI operations based on real-time CPU load conditions. When CPU load is high, the system modifies HMI behavior by using predicted completion times to stagger API invocations or adjust update frequencies, allowing the HMI to adapt its operation dynamically to current system conditions rather than using fixed timing.
2Reliability
If the API process execution time is extended to ensure completion of data preparation, then data accuracy is improved, but HMI operability and screen responsiveness deteriorate
Solution Approach 1:
The prediction unit performs preliminary assessment of API execution requirements by estimating completion times based on current CPU load. This allows the system to determine in advance whether an API function can complete within the HMI's timeout threshold, enabling proactive decision-making about which operations to proceed with or defer.
Solution Approach 2:
The system applies partial action by selectively executing only those API functions that are predicted to complete within acceptable time frames. When CPU load prevents full execution of all requested operations, the system performs a subset of critical operations that can complete reliably, rather than attempting all operations and risking complete failure.
3Loss of information
If the frequency of screen update is increased to improve operator awareness, then operator awareness of system status is improved, but CPU load increases causing more timeouts
Solution Approach 1:
The system dynamically adjusts screen update frequency based on predicted API completion times and current CPU load. When CPU load is high, the system reduces update frequency for non-critical displays while maintaining updates for critical operational information, optimizing the balance between information provision and system performance rather than using fixed high-frequency updates.
Solution Approach 2:
The prediction unit enables preliminary planning of screen updates by estimating when data will be ready. The HMI can schedule display updates to coincide with predicted API completion times, ensuring information is refreshed as soon as data is available without requiring continuous polling that would increase CPU load.
4Ease of operation
If the timeout threshold for API functions is reduced to improve HMI responsiveness, then HMI response time is improved, but the number of timeout errors increases during heavy load
Solution Approach 1:
The prediction unit performs preliminary estimation of API completion times before execution, allowing the system to set dynamic timeout thresholds based on current CPU load rather than using fixed thresholds. This enables the HMI to maintain responsive behavior during normal operation while anticipating longer processing times during heavy load conditions.
Solution Approach 2:
The system changes the timeout parameter dynamically based on predicted CPU load conditions. When the prediction unit estimates high CPU load, the system increases timeout thresholds for affected API functions, allowing sufficient time for completion while maintaining tight thresholds for low-load operations to preserve responsiveness.
Data Source
AI summary
A numerical control apparatus includes an API interface section that accepts invocation of an API function, an API control section that executes the process of the API function based on the invocation of the API function, and processing period estimation means for estimating if the execution of the API function is completed in a predetermined period, and the API control section does not execute but terminates the process of the API function when the processing period estimation means estimates that the execution of the API function will not be completed in the predetermined period.