雷射粉床熔融是近年來逐漸興起的一種製造方法，該製程方法能夠在短時間內製造出獨特的零件，且幾乎沒有幾何形狀的限制。但是雷射熔融過程中的高溫度梯度及高冷卻速率會導致殘餘應力。然而殘餘應力會導致製造零件翹曲、產生裂痕甚至在製造過程中就與加工基板分離。
有鑑於此，本篇論文針對雷射粉床熔融工件切斷支撐材後的翹曲及加工參數的關係進行一系列的研究。在本篇文章中探討移除支撐材後懸臂樑的曲率而並非以翹曲量，這是由於翹曲量的量測誤差較大的原因。在本研究中建立了修正固有收縮法的多尺度模型，並以此模型預測在不同加工參數的懸臂樑曲率。接著利用一組實驗參數的結果對模擬模型進行修正，並找出修正因子。然後將相同的修正因子值應用於其他不同的加工參數模擬懸臂樑曲率。懸臂樑曲率實驗結果與模擬結果達到驗證。緊接著提出了一種模擬參數設計方法，並沿用經驗證之多尺度模型模擬懸臂樑曲率及單道掃描的固體冷卻速率。再利用人工神經網絡（ANN）用於快速預測模擬結果。最後，根據曲率、固體冷卻速率和密度決定最佳參數區域。結果最佳參數區域中的雙懸臂樑變形與其他區域相比，最大降低幅度達到17.9%，且密度可高達99.97%。
總結來說，本篇論文的主要貢獻為下列三點：
(1) 透過雷射單道掃描模型中的溫度歷史成功地修改固有收縮法，且使用多尺度模型預測雷射粉床熔融加工件在不同加工參數(雷射功率與掃描速度)下的變形；
(2) 成功地利用多尺度模擬模型以人工神經網絡找出優化的加工參數，此優化參數能製造較少的變形及較高密度的試件；
(3) 本篇論文建立了一套優化參數的方法，與一般在產業中常使用的試誤法及實驗設計法相比，得以解決大筆時間及金錢成本的問題。

Laser powder bed fusion (LPBF) is one potential manufacture process in recent year. This process is able to produce unique component in short time and has nearly no restriction on geometry. However, the high temperature gradient and high cooling rate during laser fusion process result in residual stress. The residual stress leads to LPBF part warpage, crack or even baseplate separation.
In view of this, this research focuses on the correlation between the process parameters and distortion of LPFB part (or the curvature of the cantilever beam in this study) after the supporter was removed.
The multiscale model with modified inherent shrinkage method is developed to predict the curvature of cantilever beam. Then, one parameter of experimental results was taken to calibrate the simulation model and find the calibration factor. Subsequently, the same calibration factor was applied to other different sets of laser power and scanning speed in simulation. It is found that the simulation has a good agreement with experimental results.
Subsequently, a sphere packing design method was proposed to design the parameters for simulating the curvature of LPBF and the solid cooling rate of a single scanning track for studying the minimum distortion of LPBF. Artificial neural networks (ANN) were then used to predict simulation results fast. Finally, the optimal parameters were determined based on curvature, solid cooling rate, and density. As a result, the curvature of a cantilever beam based upon the parameters in an optimal region is reduced 17.9% as compared to those of LPBF part with parameters in other regions. Also, the density of 3D part is much improved up to 99.97% based upon the parameters in an optimal region.
It is concluded that several main contributions in this study are:
(1) The original inherent shrinkage method is successfully modified by additionally adding the temperature history of a single scanning track model in order to predict the deformation of LPBF part with different sets of laser power and scanning speed.
(2) The methodology in finding the optimal region is first successfully developed for fabricating a 3D LPBF part with less distortion and high-density.
(3) Usually, companies conduct the ways of trial-and-error and design of experiments in finding the proper parameters, and it is time-consuming and resource-wasting. The methodology developed in this study supplies an efficient way to find the optimal parameters.

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