双侧公差限产品的合格概率计算方法

doi:10.3969/j.issn.1000-1158.2018.04.03

Abstract
Figure/Table
References (18)
Related Citation (15)

Download: PDF (588 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract A calculation model of products’ qualified probability is established to quantitatively analyze products qualification, considering the influence of uncertainty of parameter measurement and based on the assumption of normal distribution. The design requirement of products is bilateral tolerance limit. The model provides a theoretical basis for the quantitative calculation of batch products’ and single product’ qualified probability, and gives a calculation example of measurement and analysis. The results show that the quantitative calculation results of products’ qualified probability has an important guiding significance for the analysis of product quality problems and improving the quality of products. The given method also has referenced value for the calculation of product qualified probability, which design requirement of products is unilateral tolerance limit.

Key words： metrology bilateral tolerance limit product inspection qualified probability uncertainty of measurement

Received: 08 June 2017 Published: 06 July 2018

PACS:

TB92

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	HUANG Fu-gui
	LIU Zhi-sen
	ZHAO Bao-sheng

Cite this article:

HUANG Fu-gui,LIU Zhi-sen,ZHAO Bao-sheng. A Calculation Method of Products’ Qualified Probability of Bilateral Tolerance Limit[J]. Acta Metrologica Sinica, 2018, 39(4): 461-464.

URL:

http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2018.04.03 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2018/V39/I4/461

［1］邓军,余忠华,吴昭同. 产品质量与过程质量的映射研究［J］.中国机械工程,2010,21(17):2070-2074.
［2］毕军贤,赵定涛. 抽样产品检验的质量检验博弈与诚信机制设计［J］.管理科学学报,2011,14(5):43-50.
［3］段赛赛,樊树海,黄婷华,等. 基于信息熵的二次抽样特性曲线性能评价［J］.现代制造工程,2013,(10):6-10.
［4］罗明,尹雪艳. 平衡单因素模型下两过程能力指数的比较［J］.山东理工大学学报,2015,29(3):76-78.
［5］张根保,庞继红,任显林,等. 机械产品多元质量特性重要度排序方法［J］.计算机集成制造系统,2011,17(1):151-157.
［6］王汉斌,陈晓怀,程真英,等. 融合生产信息的产品检验不确定度评定［J］. 计量学报,2017, 38(2): 164-167.
［7］彭和平,将向前,徐振高,等. 基于现值质量损失的相关特征产品的公差设计［J］.华中科技大学学报,2009,37(2):71-74.
［8］赵延明,刘德顺,徐小艳,等. 面向零件公差设计的产品质量损失成本模型［J］.中国机械工程,2011,22(11):1347-1351.
［9］费威. 制造商检验的最优质量水平及其影响因素研究［J］.经济数学,2013,30(2):1-6.
［10］王宏涛,王汉斌,陈晓怀,等. 测量不确定度引起的批量产品检验误判风险评估［J］. 计量学报,2017, 38(5):559-562.
［11］周小喜. 两种基于过程能力指数的抽样方案研究［J］.苏州市职业大学学报,2010,21(1):65-68.
［12］魏冠军,党亚民,章传银. 测量数据不确定性度量的最小模糊熵算法［J］.武汉大学学报,2016,41(12):1677-1682.
［13］蒋薇, 张玘,Alessandro Ferrero,等. 随机模糊变量表示测量及测量不确定度［J］.仪器仪表学报,2016,37(5):1065-1078.
［14］梁淑明,张根保. 质量成本与西格玛能力之间关系模型探讨［J］.制造技术与机床,2006,(5):103-105.
［15］施浒立, 赵彦. 误差设计新理念与方法［M］.北京:科学出版社,2009.
［16］王海宇. SPC/EPC整合控制下的过程能力指数研究［J］.中原工学院学报,2016,27(2):47-51.
［17］沙定国. 误差分析与测量不确定度评定［M］.北京:中国计量出版社,2003.
［18］GB/T 4882—2001 数据的统计处理和解释—正态样本离群值的判断和处理［S］. 2001.