Multi-Sensor Quality Inference for Real-Time Additive Manufacturing Control
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Solution Overview
Problem
Current additive manufacturing processes face challenges in non-destructively verifying the quality of parts, as conventional quality assurance methods often require destruction of the part and cannot be applied to production parts, and there is a need for real-time monitoring and control to manage variations in the size and temperature of the weld pool during the manufacturing process.
Innovation Solution
The method involves using optical temperature sensors to monitor temperature changes and calibrate heat supply based on sensor data, allowing for real-time adjustments to maintain consistent weld pool size and temperature, and combining Lagrangian and Eulerian reference frames to predict process parameters and ensure quality control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional quality assurance testing is used to verify part quality, then thorough inspection of internal portions is achieved, but the part must be destroyed
Solution Approach 1:
The patent replaces physical contact-based destructive testing with non-contact optical sensing systems. Multiple optical sensors (pyrometers, cameras, interferometers) detect thermal radiation, light reflection, and interference patterns to infer internal part quality without mechanical contact or destruction, resolving the contradiction between thorough inspection and part preservation
Solution Approach 2:
The patent introduces optical sensors as intermediary devices that indirectly measure internal part characteristics through thermal radiation and light interactions. These sensors act as mediators between the part and the inspection system, enabling quality verification without direct physical contact that would require destruction
2Manufacturing precision
If real-time temperature monitoring is implemented with multiple sensors, then weld pool consistency is improved, but system complexity increases
Solution Approach 1:
The patent divides the monitoring system into multiple specialized optical sensors, each targeting specific parameters (temperature, weld pool geometry, thermal radiation). This segmentation allows each sensor to be optimized for its specific function while collectively providing comprehensive process control, managing complexity through functional specialization
Solution Approach 2:
The patent employs optical sensors that serve multiple functions simultaneously - measuring temperature, weld pool size, and thermal characteristics with the same hardware platform. This multi-functionality reduces overall system complexity compared to using separate specialized devices for each measurement type
3Reliability
If non-contact optical sensing is used to monitor temperature, then part integrity is maintained, but measurement precision at high temperatures becomes challenging
Solution Approach 1:
The patent utilizes the change in thermal radiation parameters with temperature to enable non-contact measurement. By detecting variations in radiation intensity, spectral distribution, and temporal patterns, the system accurately measures high temperatures without contact, maintaining both part integrity and measurement precision
Solution Approach 2:
The patent applies pyrometric principles that detect color changes in thermal radiation corresponding to temperature variations. Optical sensors measure the spectral characteristics of emitted radiation, where color temperature changes provide accurate high-temperature measurements without physical contact
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 enables non-destructive quality verification and real-time process control, improving the consistency and integrity of additive manufactured parts by adjusting heat input based on sensor data, thereby enhancing the precision and reliability of the additive manufacturing process.
Implementation Method 1
monitoring the temperature of a first portion of a build plane during an additive manufacturing operation with a first optical temperature sensor
Implementation Method 2
the heat source melts the incrementally added powder by welding regions of the powder layer creating a moving molten region
Implementation Method 3
using an energy source that takes the form of a moving region of intense thermal energy
Implementation Method 4
detecting a change in state of material within the first portion as a heat source passes through the first portion of the build plane
Data Source
AI summary
This invention teaches a multi-sensor quality inference system for additive manufacturing. This invention still further teaches a quality system that is capable of discerning and addressing three quality issues: i) process anomalies, or extreme unpredictable events uncorrelated to process inputs; ii) process variations, or difference between desired process parameters and actual operating conditions; and iii) material structure and properties, or the quality of the resultant material created by the Additive Manufacturing process. This invention further teaches experimental observations of the Additive Manufacturing process made only in a Lagrangian frame of reference. This invention even further teaches the use of the gathered sensor data to evaluate and control additive manufacturing operations in real time.