進階搜尋


 
系統識別號 U0026-0812200915124785
論文名稱(中文) 多維切割製程能力指標之推導與研究
論文名稱(英文) Development of New Capability Indices for the Positional Tolerance of a Multidimensional Machining Process
校院名稱 成功大學
系所名稱(中) 統計學系碩博士班
系所名稱(英) Department of Statistics
學年度 97
學期 2
出版年 98
研究生(中文) 盧彥宇
研究生(英文) Yen-Yu Lu
學號 r2696109
學位類別 碩士
語文別 中文
論文頁數 50頁
口試委員 口試委員-鄭春生
指導教授-潘浙楠
口試委員-呂金河
中文關鍵字 製程能力指標  幾何容差  位置容差 
英文關鍵字 Geometric dimensional and tolerance  Positional tolerance  Capability index 
學科別分類
中文摘要 製程能力指標(process capacity indices)在製程能力分析中扮演重要角色,因為它提供一個簡單易懂的製程整體表現量測標準。隨著產品功能的多樣化,製程的複雜度亦隨之增加,僅衡量單一品質特性已不足反映製程之能力,因此90年代以後有多位學者致力於具多重品質特性製程能力指標的研究。多重品質特性製程之規格區域是由個別品質特性規格範圍所構成的矩形區域。有別於多重品質特性之規格區域,多維切割製程之規格區域是一種稱之為位置容差(positional tolerance)的特殊規格。位置容差為幾何容差(geometric dimensioning and tolerancing, GD&T)中的一種,它是一種描述切割製程所允許的位置之規格區域,在二維度時為一圓形、三維度時為一球體。 Bothe (2006)、Karl et al. (1994)、Litting et al. (1993)、Davids et al. (1993)及Krishamoorthi (1990)等學者,提出適用於評估此特殊規格區域的多維切割製程的製程能力指標。過去的研究皆假設不同切割方向的變異是一致的,但在許多情況下此假設並不適用,故本研究制定當變異不一致時,新的多維切割製程能力指標,藉以評估多維切割製程生產時在準確度與精密度上的表現。我們在常態性的假設下推導該指標估計量之統計性質,建立其區間估計與假設檢定方法。再利用數值模擬的方式與過去學者所提出之多維切割製程能力指標作一比較。結果顯示,本研究所之新製程能力指標較能正確反映出製程實際表現。最後,利用本研究之多維切割製程能力指標對一數值實例進行分析與說明。
英文摘要 Process capability indices play the important role in the manufacturing industry to determine whether a process is capable of manufacturing good-quality items. At beginning, process capability analysis only focuses on the process with a single characteristic. With the advent of modern technology, manufacturing process become very sophisticated and merely a single quality characteristic cannot reflect the product quality. Normally, the abnormality of an industrial process is caused by the problems of several interrelated quality characteristics. In contrast with the multivariate manufacturing process, the multidimensional machining process has a special specification called the positional tolerance. Positional tolerance is a type of geometric dimensioning and tolerancing (GD&T) which describes the tolerance region between the location of machining results and the target point. Past researchers proposed the capability index for the positional tolerance of a multidimensional machining process under the assumption that two or more dimensional variances are equal. However, this assumption may not be true in the real situation. In this research, two new capability indices for measuring the precision and accuracy of the positional tolerance of a multidimensional machining process are developed under the normal assumption. The statistical properties of the point estimators for the new capability indices are proved, then their confidence intervals and hypothesis testing methods are established using the approximations. The simulation results show that the new capability indices can better reflect the true performance of a multidimensional machining process then the previous indices.
論文目次 摘要 I
Abstract II
表目錄 VI
圖目錄 VII
第一章 緒論 1
1-1 研究動機與背景 1
1-2 研究目的 3
1-3 研究架構 3
第二章 文獻探討 5
2-1 製程能力指標 5
2-2 多變量製程能力指標 7
2-3 多維切割製程能力指標 8
第三章 新的多維切割製程能力指標 11
3-1 新的多維切割製程能力指標之制定 11
3-2 多維切割製程能力指標之估計量 12
3-2-1 多維切割製程能力準確度指標估計量 12
3-2-2 多維切割製程能力精密度指標估計量 13
3-3 多維切割製程能力指標之區間估計 14
3-3-1 多維切割製程能力準確度指標區間估計 14
3-3-2 多維切割製程能力精密度指標區間估計 15
3-4 以數值分析評估多維切割製程能力指標之區間估計 16
3-4-1 準確度指標區間估計之涵蓋率 17
3-4-2 精密度指標區間估計之涵蓋率 23
3-5 多維切割製程能力指標之假設檢定 24
3-5-1 準確度指標之假設檢定 24
3-5-2 精密度指標之假設檢定 25
3-6 多維切割製程能力綜合指標 26
第四章 多維切割製程能力指標之比較與實例探討 27
4-1 各種製程能力指標在反映二維切割製程不良率之比較 29
4-2 多維切割製程評估準則之建立 32
4-3 實例分析 34
第五章 結論與未來研究方向 38
5-1 結論與貢獻 38
5-2 未來研究方向 39
參考文獻 40
附錄A 43
附錄B 44
附錄C 47
附圖 49
參考文獻 1.Bothe, D. R. (2006), “Assessing capability for hole location,” Quality Engineering, 18(3): 325-331.
2.Chan, L. K., Cheng, S. W. and Spiring, F. A. (1991), “A multivariate measure of process capability,” Journal of Modeling and Simulation, 11: 1-6.
3.Davis, R. D., Kaminsky, F. C. and Saboo, S. (1992), “Processcapability analysis for process with either a circular or a spherical tolerance zone,” Quality Engineering, 5(1): 41-54.
4.Henzold, G. (1995), Handbook of Geometrical Tolerancing, New York: John Wiley & Sons.
5.Efron, B. and Tibshirano, R. J. (1993), An Introduction to the Bootstrap, New York: Chapman and Hall.
6.English, J. R. and Taylor, G. D. (1993), “Process Capability Analysis: a robustness study”, International Journal of Production Research, 31(7): 1621-1635.
7.Hsu, Y. D. (2002), “Probability of hitting a specified target region with three-dimensional correlated random variables and aim point offset from the target,” IEEE Position Location and Navigation Symposium: 113-119.
8.Hubele, N. F., Shahriari, H., and Cheng, C. S. (1991), “A bivariate process capability vector,” in Keats, J. B., and Montgomery, D. C., (eds), Statistical Process Control in Manufacturing, Marcel-Dekker: 299-310.
9.Juran, J. M. (1974), Quality Control Handbook, New York: McGraw-Hill.
10.Kane, V. E. (1986), “Process capability indices”, Journal of Quality Technology, 18: 41-52.
11.Karl, D. P., Morisette, J. and Taam, W. (1994), “Some applications of a multivariate capability index in geometric dimensioning and tolerancing,” Quality Engineering, 6(4): 649-665.
12.Kotz, S. and Johnson, N. L. (1993), Process Capability Indices, New York : Chapman and Hall.
13.Krishnamoorthi, K. S. (1990), “Capability indices for processes subject to unilateral and positional tolerances,” Quality Engineering, 2(4): 461-471.
14.Littig, S. J., Lam, C. T. and Pollock, S. M. (1993), “Process capability measurements for a bivariate characteristic over an elliptical tolerance zone,” Department of Industrial and Operations Engineering, University of Michigan Technical Report: 92-42.
15.Liu, H., Tangb, Y. and Zhang, H. H. (2009), “A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables,” Computational Statistics and Data Analysis, 53: 853-856.
16.Mathai, A. M. and Provost S. B. (1992), Quadratic Forms in Random Variables Theory and Applications, Marcel Dekker.
17.Montgomery, D. C. (2005), Introduction to Statistical Quality Control, 5th, New York: John Wiley & Sons.
18.Pan, J. N. and Lee, J. K. (2003), “A Comparative Study of Multivariate Process Capability Indices,” Journal of Quality, 10: 149-176.
19.Pearn, M., Kots, S. and Johnson, N. L. (1992), “Distribution and Inferential Properties of Capability Indices,” Journal of Quality Technology, 24: 216-233.
20.Taam, W., Subbaiah, P. and Liddy, J. W. (1993), “A note on multivariate capability indices,” Journal of Applied Statistics, 20: 339-351.
21.Wang, C. H. (2005), “Constructing Multivariate Process Capability Indices for Short-Run Production,” The International Journal of Advanced Manufacturing, 26: 1306-1311.
22.Wang, F. K. and Chen, J. C. (1998), “Cpability index using principal component analysis,” Quality Engineering, 11(1): 21-27.
23.Weisbac, R. (2005), “Testing for multivariate equivalence with random quadratic forms,” University of Dortmund Technical Report: 4.
24.潘浙楠、李文瑞 (2003),「品質管理」,華泰書局。
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2014-07-02起公開。
  • 同意授權校外瀏覽/列印電子全文服務,於2014-07-02起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw