Additive Manufacturing Thermal Sensor Calibration via Pattern Comparison
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Solution Overview
Problem
In additive manufacturing systems, deviations in the position of thermal sensors can lead to inaccurate temperature distribution calculations in the print region, affecting the quality of printed objects and requiring frequent recalibration, which results in material waste, increased startup times, and user support needs.
Innovation Solution
The system performs an initial calibration check during startup by forming a small number of layers and comparing thermal images with expected patterns to determine if recalibration is necessary, allowing for accurate thermal sensor positioning and reducing the need for frequent recalibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If thermal sensor position is not accurately calibrated, then temperature distribution calculations become inaccurate, but recalibration requires material waste and increased startup time
Solution Approach 1:
The system performs a quick calibration check during startup by forming only a small number of calibration layers (e.g., 3-5 layers) compared to full production layers. This preliminary action allows the system to detect thermal sensor position deviations early and determine whether recalibration is needed, avoiding the time loss of extensive recalibration when the sensor is properly positioned.
2Measurement precision
If thermal sensor position deviates from expected position, then temperature distribution calculations are inaccurate, but frequent recalibration increases material waste
Solution Approach 1:
The system performs a quick calibration check during startup by forming only a small number of calibration layers (e.g., 3-5 layers) compared to full production layers. This preliminary action allows the system to detect thermal sensor position deviations early and determine whether recalibration is needed, avoiding the material waste of extensive recalibration when the sensor is properly positioned.
Solution Approach 2:
The system captures thermal images during the calibration layers, compares them to expected thermal patterns, and uses this feedback to determine whether the thermal sensor position requires recalibration. This feedback mechanism enables the system to make informed decisions about recalibration needs, reducing unnecessary material consumption.
3Manufacturing precision
If thermal sensor position is inaccurate, then printed object quality deteriorates, but recalibration increases user support needs
Solution Approach 1:
The system captures thermal images during the calibration layers, compares them to expected thermal patterns, and uses this feedback to determine whether the thermal sensor position requires recalibration. This feedback mechanism enables the system to make informed decisions about recalibration needs, reducing unnecessary material consumption.
Solution Approach 2:
The system automatically performs calibration checks and determines its own recalibration needs without requiring user intervention or technical support. The automated calibration check during startup and the decision-making process for recalibration empower the system to self-diagnose and self-correct, reducing user support requirements.
4Measurement precision
If calibration is performed frequently to ensure accuracy, then measurement precision improves, but productivity decreases
Solution Approach 1:
The system performs a quick calibration check during startup by forming only a small number of calibration layers (e.g., 3-5 layers) compared to full production layers. This preliminary action allows the system to detect thermal sensor position deviations early and determine whether recalibration is needed, avoiding the time loss of extensive recalibration when the sensor is properly positioned.
Solution Approach 2:
The system performs a partial calibration using only a small number of calibration layers (e.g., 3-5 layers) instead of full production layers. This partial action is sufficient to detect thermal sensor position deviations and determine recalibration needs, maintaining measurement precision while minimizing impact on productivity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach ensures accurate calibration of additive manufacturing systems, reducing material waste, print agent consumption, and startup time while improving the quality of printed objects and user experience by minimizing the need for technical support.
Implementation Method 1
A thermal sensor, such as a thermal camera or a thermal image capture device... can be used to capture images indicating the temperature of the print region
Implementation Method 2
energy, for example thermal energy, is applied to the layer. This fuses particles of build material according to the agents that have been applied
Data Source
AI summary
Examples of a method of operating an additive manufacturing system, a three-dimensional (3D) printing system and a non-transitory machine-readable medium are described. In an example, a build material is supplied to a print region of an additive manufacturing system. A temperature distribution, corresponding to a pattern, of at least a surface of the build material is generated. An image of the pattern is captured using a thermal sensor. Image data representative of the image of the pattern is compared with data representative of an expected position of the pattern. On the basis of the comparing, difference data indicative of a difference between a position of the thermal sensor during capture of the image and an expected position of the thermal sensor associated with the expected position of the pattern is generated. Operation of the additive manufacturing system is controlled at least in dependence on the difference data.