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中南大学学报(自然科学版)

Journal of Central South University

第43卷    第5期    总第213期    2012年5月

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文章编号:1672-7207(2012)05-1753-11
面向多质量特征的产品质量损失成本模型及其应用
赵延明1, 2,刘德顺3,张俊3,柳乔3

(1. 中南大学 机电工程学院,湖南 长沙,410083;
2. 湖南科技大学 信息与电气工程学院,湖南 湘潭,411201;
3. 湖南科技大学 机械设备健康维护省重点实验室,湖南 湘潭,411201
)

摘 要: 针对产品多质量特征与零部件的尺寸之间不能直接利用几何原理得出显式关系表达式,很难建立产品级的质量损失模型的现状,提出一种基于神经网络法和层次分析法的质量损失模型。为了尽量减少主观随意性对权重确定的影响,采用神经网络法处理产品历史数据确定权重。考虑零件加工过程中的返修成本和报废成本,采用分段质量损失函数对田口质量损失函数进行改进,使其更加贴近工程实际,并根据零件尺寸服从不同的分布,导出相应的零件质量损失成本。研究结果表明:该质量损失模型为隐式关系建模提供了有效解决方法。

 

关键字: 多质量特征;质量损失;神经网络法;层次分析法

Quality loss cost model and its application to products with multi-quality characteristics
ZHAO Yan-ming1, 2, LIU De-shun3, ZHANG Jun3, LIU Qiao3

1. School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China;
2. School of Information and Electrical Engineering, Hunan University of Science and Technology,
Xiangtan 411201, China;
3. Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment,
Hunan University of Science and Technology, Xiangtan 411201, China

Abstract:Based on the fact that the explicit relation expression between product multi-quality characteristics and the dimensional tolerance of component is not educed directly with geometry principle and the product-level quality loss cost is difficult to establish, a quality loss cost model with neural network method and analytic hierarchy process (AHP) was processed. In order to decrease the impact of subjective randomness, the weights are determined with neural network method to product historical data process. Taking rework costs and scrap costs into account during the course of manufacturing mechanical parts, the piecewise quality loss function was used to improve Taguchi quality loss function, which is very close to engineering practice. The corresponding quality loss costs were deduced with the different distribution of part dimension. The results show that the quality loss cost model provides an effective method for the implicit relation model.

 

Key words: multi-quality characteristics; quality loss; neural network method; analytic hierarchy process

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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