Aiming at the unmelted powders splash from collision between electron and powders, optimized process parameters is selected to pre-heat the powders to obviously reduce the splash.
针对实验中出现的电子与粉末碰撞造成的未熔粉末的飞溅，采用优化的工艺参数对粉层进行预热，从而大大减少了未熔粉末的飞溅。
Based on these parameters, optimized process parameters set with mathematical statistical full factor experiments can guarantee the quality of welded plastics parts in batch production.
以这些参数为基础，借助数理统计的全因子实验设置优化的工艺参数，可以保证批量焊接产品的质量。
In this paper, the optimized process parameters that have major influence on nanoparticle content were obtained by orthogonal test, and the result was further analyzed by BP neural network.
本文运用正交试验法优化了对复合沉积层中纳米颗粒复合量有较大影响的各工艺参数，然后用BP神经网络分析方法对其结果进行分析处理。
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