Measurement Plan Presets Using ML for Faster Setup
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Solution Overview
Problem
The complexity and time-consuming nature of creating measurement plans for dimensional measuring devices, such as coordinate measuring machines and microscopes, lead to high costs due to the need for manual selection of numerous setting parameters, which can be inefficient and result in overwriting frequently used settings.
Innovation Solution
A method and device that utilize statistical evaluation and machine-aided learning to determine user-specific default settings for setting parameters, reducing the need for manual input and allowing for adaptive presettings based on user interactions and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a user manually creates a measurement plan using existing software, then the measurement plan can be created, but the process requires significant user input and interpretation of measurement data, making it complex and time-consuming
Solution Approach 1:
The system automatically generates the measurement plan by processing measurement data and identifying relevant features without requiring manual user input. The computer executes algorithms that autonomously create the measurement plan based on the measured data and predefined criteria, making the system self-sufficient in plan generation.
Solution Approach 2:
The system performs preliminary processing of measurement data to identify relevant features and characteristics before the actual measurement plan creation. By pre-analyzing the data and preparing feature information, the system streamlines the subsequent plan generation process and reduces the time required for manual intervention.
2Loss of information
If measurement data is processed to identify features, then relevant measurement information can be extracted, but the process becomes complex requiring significant user input and interpretation
Solution Approach 1:
The system implements a feedback mechanism where measurement data is processed, features are identified, and the results are used to automatically adjust and refine the measurement plan. This closed-loop approach ensures that all relevant measurement information is captured while the system self-corrects and optimizes the plan without requiring complex manual interpretation.
Solution Approach 2:
The system introduces an intermediary processing layer that automatically interprets measurement data and translates it into structured feature information. This intermediary layer handles the complex data interpretation tasks, preventing the complexity from being transferred to the user while ensuring complete measurement information is captured.
3Adaptability or versatility
If existing measurement software is used, then measurements can be performed, but the software does not sufficiently support the user in creating a suitable measurement plan
Solution Approach 1:
The system dynamically adapts the measurement plan based on the actual measurement data obtained. As measurements are performed and data is collected, the system automatically adjusts the plan to optimize it for the specific features and characteristics identified in the data, making the plan adaptable rather than static while maintaining ease of operation through automation.
Data Source
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AI summary
A method for assisting a user in creating a measurement plan for a measurement to be performed with a measuring instrument (100) and/or in controlling the measurement to be performed with the measuring instrument (100), the method comprising the following steps: (i) receiving (S100) a plurality of setting parameters (42) selected by a user with respect to a measurement or control command (40) from a plurality of measurement or control commands for the measurement to be performed with the measuring instrument (100); (ii) evaluating (S200) the plurality of setting parameters (42) based on a statistical evaluation and/or an evaluation by machine learning; (iii) determining (S300) a preset (46) by which at least one setting parameter (48) of the evaluated plurality of setting parameters (42) is assigned to the measurement or control command (40);and (iv) output (S400) a setting parameter suggestion (50) based on the determined preset (46) when an input command for selecting the measurement or control command (40) is received.;