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研究生:毛敬筌
研究生(外文):Ching-Chuan Mao
論文名稱:量測人員與產品有交互作用下之量測重複性與再現性研究
論文名稱(外文):The Study of Gauge Repeatability and Reproducibility with Interaction between Operators and Parts
指導教授:方正中方正中引用關係
指導教授(外文):Jeng-Jung Fang
學位類別:碩士
校院名稱:南台科技大學
系所名稱:工業管理研究所
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:125
中文關鍵詞:量測變異分析變異數分析法傳統GR&R法長表格法量測重複性與再現性
外文關鍵詞:Gauge variation analysisANOVAClassical GR&RLong Form methodRepeatabilityReproducibility
相關次數:
  • 被引用被引用:8
  • 點閱點閱:371
  • 評分評分:
  • 下載下載:93
  • 收藏至我的研究室書目清單書目收藏:0
量測變異分析包含量測重複性與再現性變異之量測能力,GR&R指標可提供客觀的決策數據,不但確保量測系統的準確度在控制範圍內能確切地加以運用於製程,也確保其精密度在控制範圍以保證產品品質在允收水準之內。因此,唯有精確之量測技術才能保證製程與產品品質在統計管制狀態下無誤。
GR&R研究之估算方法,包含變異數分析法、傳統GR&R法與長表格法。以往當量測人員與產品有交互作用存在時,皆以變異數分析法來做分析,而傳統GR&R法與長表格法則無法估算其變異。因此,本研究針對傳統GR&R法與長表格法無法適用在有交互作用的情況下提出修正,使新的量測變異估計式不但可適用在有交互作用的情形下且是不偏估計式,以改善利用傳統管制圖概念分析量測變異的缺點。
同時,以因子設計為基礎,利用模擬方法,根據量測變異的不偏性和均方誤差做為評估準則,證明出變異數分析法雖然具有不偏性,但若綜合考量量測準確度與精密度,以本研究所修正的量測變異估算法為最佳估計式。另外,探討固定參數組合數(npk)下的參 數(產品數n、量測人員數p、重複量測次數k)選取,建議多指派量測人員數為優先考量,其次是多抽產品數,最後是增加重複量測次數。
Gauge study considers both repeatability and reproducibility of the measurement system. The assessment of GR&R provides objective policy-making data not only ensuring accuracy but also ensuring precision of the measurement system within the controllable range for monitoring the manufacturing process. Therefore, only qualified measurement technology can guaranty the manufacturing process and the product quality in the state of statistical control.
Methods to estimate repeatability and reproducibility contain ANOVA method, Classical GR&R method, and Long Form method. In the past, the measurement system usually utilized the method of ANOVA to analyze the measurement system while there was interaction between operators and parts. Classical GR&R and Long Form methods can not be used to estimate the variation with interaction between operators and parts. Therefore, the research modified the two methods not only making them applicable in the case of interaction between operators and parts but also providing unbiased gauge variance estimators. This improved the shortcoming of gauge analysis using the concept of control chart.
Meanwhile, the research compared the gauge variance estimators of different estimation methods by simulating a measurement system based on the criterions of the biasness, variance, and mean squares error of the gauge variance estimates. The research showed that the ANOVA method produces unbiased gauge variance estimator. While taking accuracy and precision into consideration simultaneously, the modified gauge variance estimator of the research is the best one. In addition, the research also discussed the parameter values of the measurement system which are sample size, number of operators, and repetition number per operator. It is suggested that one must consider increasing the number of operators first, sample size the second and repeated measurements the last.
摘要 IV
ABSTRACT V
目錄 VI
表目錄 VIII
圖目錄 XI
第一章 緒論 1
1.1 研究背景 2
1.2 研究動機 2
1.3 研究目的 3
1.4 研究範圍與假設 3
1.5 研究流程 4
1.6 論文架構 5
第二章 相關文獻之回顧與探討 7
2.1 量測相關名詞 7
2.2 量測之重複性與再現性介紹 12
2.3 GR&R相關文獻之探討 14
2.4 GR&R的估算方法 27
2.4.1 變異數分析法(ANOVA) 28
2.4.2 傳統GR&R法(Classical GR&R Study) 32
2.4.3 長表格法(Long Form) 35
2.5 ISO/TS 16949中GR&R之判定準則 43
第三章 修正傳統GR&R法與長表格法的缺失 47
3.1 建立量測人員與產品有交互作用下的估算方法 47
3.2 個案數值實例之驗證 52
3.3 判別GR&R估算法之比較基準 57
第四章 六種估算量測變異的模擬與比較 60
4.1 量測人員與產品有交互作用存在 63
4.2 量測人員與產品無交互作用存在 87
第五章 結論與未來研究方向 110
5.1 結論 110
5.2 未來研究方向 111
參考文獻 112
中文部份 112
英文部份 112
附錄A 115
附錄B 119
附錄C 120
附錄D 121
附錄E 125
中文部份
1.江巧玉(2002),“量測系統重覆性與再現性的分析研究”,成功大學統計研究所,碩士論文。
2.李妤莉(2006),“量測重複性與再現性分析之研究”,南台科技大學工業管理研究所,碩士論文。
3.林郁智(2005),“產品與量測人員有交互作用存在下之量測重複性與再現性分析”,南台科技大學工業管理研究所,碩士論文。
4.周國雄(1991),計量計測管理,第7-10頁、第17-23頁,中華民國品質管制學會,台北。
5.陳盈全(2003),“離散型量測系統分析之研究”,成功大學工業管理研究所,碩士論文。
6.楊志文(2003),“多重品質特性中量測重複性與再現性之研究”,台北科技大學工業工程與管理研究所,碩士論文。
7.鄭希龍(2001),“量測系統分析(MSA)之作法與解析”,量測資訊,第77期,第54-60頁。
8.鄭春生(1995),品質管理,第213-216頁、第385-392頁,三民書局,台北。
9.鄭堯柈(1977),數理統計學,第315-317頁,台北。
英文部份
1.Adamec, Eric and Burdick, R. K. (2003), “Confidence Intervals for a Discrimination Ratio in a Gauge R&R Study with Three Random Factors”, Quality Engineering, Vol. 15, No. 3, pp. 383-389.
2.AIAG Editing Group (2002), “Measurement Systems Analysis-Reference Manual (MSA)”, 3nd ed., Automotive Industries Action Group.
3.Barraentine, L. B. (1991), “Concepts for R&R Studies”, ASQC Quality Press, Mil-waukee, Wisconsin.
4.Burdick, R. K. and Larsen, G. A. (1997), “Confidence Intervals on Measures of Vari-ability in R&R Studies”, Journal of Quality Technology, Vol. 29, No. 3, pp. 261-273.
5.Burdick, R. K., Allen, A. E. and Larsen, G. A. (2002), “Comparing Variability of Two Measurement Process Using R&R Studies”, Journal of Quality Technology, Vol. 34, No. 1, pp. 97-105.
6.Daniels, L. and Burdick, R. K. (2005), “Confidence Intervals in a Gauge R&R Study with Fixed Operators”, Journal of Quality Technology, Vol. 37, No. 3, pp. 179-185.
7.Dolezal, K. K., Burdick, R. K. and Birch, N. J. (1998), “Analysis of a Two-Factor R&R Study with Fixed Operators”, Journal of Quality Technology, Vol. 30, No. 2, pp. 163-170.
8.Duncan, A. J. (1986), “Quality Control and Industrial Statistics”, 5nd ed., Homewood, Illinois, pp. 1007.
9.Fang, Jeng-Jung and Wang,Peng-Seng(2005), “The Analysis of Gauge Repeatabil-ity and Reproducibility with Interaction between Operators and Parts”, The Pro-ceeding of the Fifth International Conference on Quality and Reliability (ICQR 2005), Bejin, pp. 209-216.
10.Hamada, M. and Weerahandi, S. (2000), “Measurement System Assessment via Generalized Inference”, Journal of Quality Technology, Vol. 32, pp. 241-253.
11.Mandel, J. (1972), “Repeatability and Reproducibility”, Journal of Quality Tech-nology, Vol. 4, No. 2, pp. 74-85.
12.Montgomery, D. C. and Runger, G. C. (1993a), “Gauge Capability Analysis and De-signed Experiments. Part I : Basic Methods”, Quality Engineering, Vol. 6, No. 1, pp. 115-135.
13.Montgomery, D. C. and Runger, G. C. (1993b), “Gauge Capability Analysis and De-signed Experiments. Part II : Experimental Design Models and Variance Component Estimation”, Quality Engineering, Vol. 6, No. 2, pp. 289-305.
14.Montgomery, D. C. (2005a), “Design and Analysis of Experiments”, 6nd ed., John Wiley & Sons, New York, pp. 66-69, pp. 531-534.
15.Montgomery, D. C. (2005b), “Introduction to Statistical Quality Control”, 5nd ed., John Wiley & Sons, New York, pp. 93-96, pp. 326-376.
16.Morchower, N.D. (1999), “Two-location Gauge Evaluation”, Quality Progress, Vol. 32, No. 4, pp. 79-86.
17.Pan, Jeh-Nan (2004), “Determination of the Optimal Allocation of Parameters for Gauge Repeatability and Reproducibility Study”, Journal of Quality Technology, Vol. 21, No. 6, pp. 672-682.
18.Vardeman, S. B. and VanValkenburg, E. S. (1999), “Two-way Random-effect Analy-ses and Gauge R&R Studies”, Technometrics, Vol. 41, No. 3, pp. 202-211.
19.Voelkel, J. O. (2003), “Gauge R&R Analysis for Two-Dimensional Data with Cir-cular Tolerances, Journal of Quality Technology, Vol. 35, No. 2, pp. 153-167.
20.Wilson, A., Hamada, M. and Xu, M. (2004), “Assessing Production Quality with Nonstandard Measurement Errors”, Journal of Quality Technology, Vol. 36, No. 2, pp. 193-206.
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