Measurement Controller Command Sequencing for Faster Multi-Device Execution
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Solution Overview
Problem
Complex measurement systems often require non-optimal control command sequences due to manual programming or user input, leading to inefficiencies and suboptimal execution speeds.
Innovation Solution
A method and system that automatically optimizes sequences of control commands for improved execution speed by identifying and optimizing sub-sequences, reordering commands, and enabling parallel execution across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual programming or user input is used to control measurement application devices, then the measurement system can be operated, but the control command sequences are non-optimal and execution speed is reduced
Solution Approach 1:
The measurement system automatically optimizes control command sequences without requiring manual intervention. The system analyzes and reorders commands itself, eliminating the need for users to manually craft optimal sequences while achieving both ease of operation and high execution speed
Solution Approach 2:
The system changes the parameters of control command sequences by analyzing execution times and reordering commands based on measured performance data. This dynamic parameter optimization transforms static manual programming into adaptive automated sequencing
2Adaptability or versatility
If control commands are provided sequentially to multiple measurement application devices, then all devices can be controlled, but repeated or conflicting commands reduce efficiency
Solution Approach 1:
The control command sequence is segmented into individual commands with associated execution times. By dividing the overall control sequence into discrete analyzable units, the system can identify and eliminate redundant or conflicting commands while maintaining control over multiple devices
Solution Approach 2:
The system measures actual execution times of control commands and uses this feedback to optimize future command sequences. This feedback loop enables the system to learn from performance data and automatically adjust command ordering to eliminate inefficiencies
3Reliability
If control commands are executed sequentially one after another, then all commands are processed, but the total execution time is increased
Solution Approach 1:
The system performs preliminary analysis of control command sequences to identify commands that can be executed in parallel. By pre-determining safe parallel execution opportunities before actual command execution, the system reduces total time without compromising reliability
Solution Approach 2:
The system dynamically adjusts command execution timing based on measured performance characteristics. Commands are reordered and timed dynamically rather than following a fixed sequential pattern, enabling parallel execution where possible while maintaining reliable operation
Data Source
AI summary
The present disclosure provides a method for operating a measurement system comprising at least one measurement application device, the method comprising receiving a sequence of control commands provided in the measurement system, automatically optimizing the recorded sequence of control commands for improving execution speed of the sequence of control commands in the measurement system, and controlling the measurement system based on the optimized sequence of control commands. Further, the present disclosure provides a respective measurement system controller, and a respective measurement system.