Test Control Device Using Prediction Model for Predictable Test Times
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Solution Overview
Problem
The unpredictability of test time when using random numbers as manipulated variables in device testing leads to prolonged test durations, as the time required for the controlled variable to reach the target value is not predictable.
Innovation Solution
A test control device and method that utilizes a test prediction model to generate manipulated variables, allowing for the prediction of controlled variable values and thereby shortening the test time by adjusting the manipulated variables based on the difference between the target and current controlled variable values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If random numbers are used as manipulated variables in device testing, then the testing process is simple to implement, but the test time becomes unpredictable and excessively long
Solution Approach 1:
The test control device implements feedback by continuously monitoring the controlled variable values from device testing and using this information to dynamically adjust subsequent manipulated variables. The determination unit compares the current controlled variable with the target value and modifies the next manipulated variable accordingly, creating a closed-loop system that accelerates convergence to the target value while maintaining systematic control.
Solution Approach 2:
The system changes the parameters of manipulated variables based on test progress. Instead of using fixed random numbers, the determination unit adjusts manipulated variable parameters dynamically according to the difference between current and target controlled variable values. This parameter adaptation enables the system to optimize test efficiency while reducing test time.
2Device complexity
If random numbers are used as manipulated variables, then no complex control mechanism is needed, but the time until the controlled variable reaches the target value is not predictable
Solution Approach 1:
The test control device implements feedback by continuously monitoring the controlled variable values from device testing and using this information to dynamically adjust subsequent manipulated variables. The determination unit compares the current controlled variable with the target value and modifies the next manipulated variable accordingly, creating a closed-loop system that accelerates convergence to the target value while maintaining systematic control.
Solution Approach 2:
The system performs preliminary analysis of the relationship between manipulated variables and controlled variables to establish optimal adjustment strategies. By pre-determining the control logic and adjustment rules based on expected test scenarios, the system prepares advance guidance for manipulating variables, enabling predictable test time without excessive complexity.
3Ease of manufacture
If random manipulated variables are used for testing, then the test setup is straightforward, but the test duration becomes excessively long and unpredictable
Solution Approach 1:
The test control device implements feedback by continuously monitoring the controlled variable values from device testing and using this information to dynamically adjust subsequent manipulated variables. The determination unit compares the current controlled variable with the target value and modifies the next manipulated variable accordingly, creating a closed-loop system that accelerates convergence to the target value while maintaining systematic control.
Solution Approach 2:
The system transitions from static random manipulated variables to dynamic adjusted manipulated variables. The determination unit enables the test system to adapt its behavior in real-time based on test progress, making the testing process dynamic and responsive to actual device performance, thereby significantly improving testing efficiency.
Data Source
AI summary
A test control device includes a test variable generation device and a test processing device. The test variable generation device uses a test prediction model to generate a first manipulated variable based on a difference between a target value and a first controlled variable value from a device under test. The test processing device acquires a second controlled variable value from the device under based on use of the first manipulated variable value. The test variable generation device notifies the device under test of end of a test if the second controlled variable value is equal to or greater than the target value or uses the test prediction model to generate a second manipulated variable based on a difference between the target value and the second controlled variable value when the second controlled variable value is less than the target value.


