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Purpose -The objective of this study is to investigate the effect of various parameters on rapid prototyping parts for processes of sintering metallic powder by using Nd:YAG laser via the design of experiments (DOE) method. Design/methodology/approach -Experiments based on the DOE method were utilized to determine an optimal parameter setting for achieving a minimum amount of porosities in specimens during the selective laser sintering (SLS) process. Analysis of variance (ANOVA) was further conducted to identify significant factors. Findings -A regression model predicting percentages of porosities under various conditions was developed when the traditional Taguchi's approach failed to identify a feasible model due to strong interactions of controlled factors. The significant factors to the process were identified by ANOVA.Research limitations/implications -Four controlled factors including pulse frequencies and pulse durations of laser beams, times of strikes of a pulse applying on a single laser spot and particle sizes of the powder base material had significant influence on the sintering process. Future investigation planned to be carried out for achieving multiple quality targets such as the hardness and the density for 3D parts. Originality/value -The implementation of the DOE method provided a systematic approach to identify an optimal parameter setting of the SLS process; thus, the efficiency of designing optimal parameters was greatly improved. This approach could be easily extended to 3D cases by just including additional parameters into the design. Additionally, utilization of the normality analysis on the residual data ensured that the selected model was adequate and extracted all applicable information from the experimental data.

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This paper presents the use of a genetic algorithm to optimize the size and cruise speed of a solar-powered unmanned aerial vehicle named Xihe. A conceptual aerodynamic configuration design is conducted first to obtain the initial size of the aircraft and the performance parameters. The optimization process then searches for optimal solutions for minimum energy operation. To minimize the number of decision variables, the aspect ratio of the wing and the fuselage design are fixed during optimization. The mass of the Xihe aircraft is then parameterized as a function of two performance parameters: wing reference area and cruise speed. With the parameterization results, a fitness function that links the optimization problem and the genetic algorithm is then established. The genetic algorithm searches for the optimal results for minimum energy operation. This optimization process reduces the referenced wing area of the Xihe aircraft from 5:63 m 2 in the conceptual design to 4:91 m 2 , which allows the reduction of the solar cell panel by 12.79%, reducing the costs. Optimization reduces the mass of the aircraft from 24.96 to 22.47 kg: a 9.98% reduction. The cost of the complex materials used would be less than originally required, and the cruise speed would increase from 10.93 to 11:23 m=s (the cruise speed for minimum power consumption).

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