In-Situ AM Monitoring With Digital Twin Parameter Qualification
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Solution Overview
Problem
Conventional additive manufacturing (AM) processes require a time-consuming and resource-intensive iterative approach to optimize build parameters, leading to prolonged development cycles and inefficient use of materials and equipment, as each parameter set is tested sequentially and often results in suboptimal part quality and production rates.
Innovation Solution
Implementing an in-situ monitoring system and predictive material modeling to collect data during the manufacturing process, allowing for real-time analysis and adjustment of build parameters, enabling parallel optimization of multiple features and reducing the need for physical testing, thereby streamlining the parameter development process and improving production efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional iterative parameter optimization is used, then build parameter development is achieved through systematic testing, but the process is very time consuming and requires considerable quantities of material, equipment time, and labor resources
Solution Approach 1:
The system performs preliminary actions by conducting virtual builds and simulations before physical manufacturing. The digital twin technology allows parameter optimization to be tested and validated in a virtual environment first, so that only optimized parameters are applied to physical builds, eliminating the need for multiple iterative physical trials.
Solution Approach 2:
The patent creates a digital copy (digital twin) of the physical additive manufacturing system. This digital twin replicates the behavior and characteristics of the physical system, allowing parameter optimization to be performed on the copy rather than requiring repeated physical experimentation. The digital twin includes virtual representations of materials, processes, and equipment that can be tested without consuming physical resources.
2Manufacturing precision
If conventional iterative parameter optimization is used, then build parameter development is achieved through systematic testing, but considerable quantities of material and equipment time are consumed
Solution Approach 1:
The system performs preliminary actions by conducting virtual builds and simulations before physical manufacturing. The digital twin technology allows parameter optimization to be tested and validated in a virtual environment first, so that only optimized parameters are applied to physical builds, eliminating the need for multiple iterative physical trials that consume material.
Solution Approach 2:
The patent creates a digital copy (digital twin) of the physical additive manufacturing system. This digital twin replicates the behavior and characteristics of the physical system, allowing parameter optimization to be performed on the copy rather than requiring repeated physical experimentation that would consume material resources.
3Manufacturing precision
If conventional iterative parameter optimization is used, then build parameter development is achieved through systematic testing, but labor resources and equipment time are significantly required
Solution Approach 1:
The system implements continuous feedback loops where monitoring data from the additive manufacturing process is collected in real-time and fed back to adjust build parameters dynamically. This automated feedback mechanism replaces manual trial-and-error processes, reducing labor requirements and accelerating parameter optimization. The system automatically analyzes monitoring data and makes parameter adjustments without human intervention.
Solution Approach 2:
The patent replaces manual mechanical processes with automated computational systems. Instead of human operators performing iterative testing and analysis, the system uses automated algorithms, machine learning models, and computational simulations to optimize parameters, thereby eliminating labor-intensive operations and improving productivity.
4Manufacturing precision
If multiple build iterations are performed to optimize parameters, then part quality requirements are approached, but additional time and resources are still required for printing, analyzing and testing
Solution Approach 1:
The system performs preliminary actions by conducting virtual builds and simulations before physical manufacturing. The digital twin technology allows parameter optimization to be tested and validated in a virtual environment first, ensuring that the first physical build uses optimized parameters and achieves success without requiring multiple iterations.
Solution Approach 2:
The system implements continuous feedback loops where monitoring data from the additive manufacturing process is collected in real-time and fed back to adjust build parameters dynamically. This automated feedback mechanism ensures that deviations from optimal parameters are corrected during the build process, guaranteeing first-build success and eliminating the need for subsequent iterations.
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 significantly reduces the build parameter development cycle from months to weeks or days, optimizing part quality and production rates while minimizing resource usage, allowing for rapid qualification of new materials and efficient use of resources.
Implementation Method 1
collecting in-situ monitoring data from one or more in-situ monitoring systems of the additive manufacturing machine for one or more parts
Implementation Method 2
The laser consolidates the powdered material by sintering or melting the powdered material
Implementation Method 3
The laser consolidates the powdered material by sintering or melting the powdered material
Implementation Method 4
The laser consolidates the powdered material by sintering or melting the powdered material
Data Source
AI summary
According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a parameter development module comprising a processor, a defined geometry for one or more parts, wherein the parts are manufactured with an additive manufacturing machine, and wherein a stack is formed from one or more parts; fabricating the one or more parts with the additive manufacturing machine based on a first parameter set; collecting in-situ monitoring data from one or more in-situ monitoring systems of the additive manufacturing machine for one or more parts; determining whether each stack should receive an additional part based on an analysis of the collected in-situ monitoring data; and fabricating each additional part based on the determination the stack should receive the additional part. Numerous other aspects are provided.