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 study analyzes contour distortions, wear mass losses and tensile properties of polypropylene (PP) composite components applied to the interior coffer of automobiles. The specimens are prepared under different injection molding conditions by changing melting temperatures, injection speeds, and injection pressures via three computer-controlled progressive strokes. The contour distortions, wear and tensile properties are selected as quality targets. The arrangement of sixteen experiments is based on an orthogonal array table. Both the Taguchi method and the design of experiments (DOE) method are applied to determine an optimal parameter setting. In addition, a side-by-side comparison of two different approaches is provided. In this study, regression models that link the controlled parameters and the targeted outputs are developed, and the mathematic models can be utilized to predict the contour distortions, wear and tensile properties at various injection molding conditions.

This paper presents an approach for analyzing the dynamics of initial impact during robotic parts mating represented by peg-in-hole assembly. Lagrange's impact model is used to derive a general form of impact equations for an industrial manipulator performing peg-in-hole assembly. Specific impact equations can then be generated for a given robot to analyze part motions and contact forces in the mating of parts. The impact equations of a SCARA robot are obtained and utilized to investigate how the system parameters affect force impulse and departure angle in the assembly of a peg with a chamfered hole. The resulting information is useful to robot manufacturers in design of robotic equipment and to robot users in determining optimal operational conditions. It is also useful for building an intelligent robot controller capable of deciding on proper values of operation parameters.

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