| Summary: | 碩士 === 中正理工學院 === 兵器系統工程研究所 === 87 === In order to obtain a better performance in weapon components, their design parameters and operating variables usually were determined by means of trial and error method in traditional weapon component research and development stage. The effective factors for bad quality in manufacture process can be found by the technique of the Statistical Process Control（SPC）, such as Control-charts and Herringbone diagram analysis, etc. However, these traditional methods or techniques usually can not obtain the best results exactly.
The problems in design process come from the cause that the interaction between the effective factors of the experiment are still unknown by trial and error method. Besides the unknown interaction, the SPC skills are also lack of general performance rating method to evaluate the compromise condition of the multi-objectives in weapon components. Therefore, the reasonable compromise in multi-objective performances is also difficult to approach in manufacture process.
In this investigation, the integrate model of Experimental Design Methodology（EDM）which was incorporated with the Response Surface Methodology（RSM） optimization analysis was proposed to improve the design and manufacture process in the weapon components. This integrated model can solve the above problems. In order to explain the method, a typical procedure that representing the design and manufacture stages was illustrated by two different needle-roller bearing retainer C-I & C-II punch forming process, one for design and the other for manufacture. The results reveal that the optimized response data were better than any results which from the original experimental design data. The performance rating percentage of compromise setting was validated within satisfactory range. These results provide evidence that for this integrated methodology is effective in the design and manufacture process. This study can improve the quality, reduce the research and development time, and save the production cost of weapon components.
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