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基于6σ稳健性的运输工装轻量化设计 被引量:5

Lightweight Design for Transportation Tooling Based on Six Sigma Robustness
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摘要 为了在减轻地铁车辆拖车轮对运输工装重量的同时,提高优化设计的可靠性与稳健性,在轻量化设计中充分考虑尺寸参数的不确定性信息,通过引入6稳健设计理念,将响应面法、轻量化设计、6质量管理、可靠性设计、稳健设计、蒙特卡罗模拟技术相结合,构造了基于6稳健性的地铁车辆拖车轮对运输工装轻量化设计新方法。结果表明,优化后的工装强度和刚度满足设计要求,重量减少了112.3kg,减重率达49.3%,轻量化效果显著;且与传统的确定性轻量化设计相比,该方法不仅增强了工装的强度和刚度,而且提高了优化设计的可靠性、强度与刚度的稳健性以及重量的一致性,验证了该方法的有效性。 In order to reduce the weight of the metro vehicle trailer wheelset transportation tooling and improve the reliability and robustness of the optimization design,the uncertainty information of the dimension parameters was fully considered in the lightweight design.By introducing the six sigma robust design concept,and combined response surface method,lightweight design,six sigma quality management,reliability design,robust design and Monte Carlo simulation technique,a new method for the lightweight design of the metro vehicle trailer wheelset transportation tooling was constructed based on six sigma robustness.The results show that the strength and stiffness of the tooling meets the design requirements,the weight is reduced by 112.3kg,the weight loss rate is 49.3%,and the lightweight effect is remarkable.Compared with the traditional deterministic lightweight design,this method not only enhances the strength and stiffness of the tooling,but also improves the reliability of the design,the robustness of the strength and stiffness and the consistency of the weight.Therefore the effectiveness of the proposed method is verified.
作者 伍建军 王子宁 金渶棋 马垚 WU Jian-jun;WANG Zi-ning;JIN Ying-qi;MA Yao(School of Mechatronics Engineering,Jiangxi University of Science and Technology,Jiangxi Ganzhou341000,China;Second Operation Branch Company Affiliated with Beijing Mass Transit Railway Operation Co.,LTD.,Beijing 100044,China)
出处 《机械设计与制造》 北大核心 2020年第7期273-277,共5页 Machinery Design & Manufacture
基金 国家自然科学基金项目(51665017) 江西省重点研发计划项目(20161BBH80041)。
关键词 拖车轮对运输工装 轻量化设计 6稳健设计 蒙特卡罗模拟 Trailer Wheelset Transportation Tooling Lightweight Design Six Sigma Robust Design Monte Carlo Simulation
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