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系統識別號 U0026-2406201915581700
論文名稱(中文) 非常態分配下多維切割製程能力指標制定之研究
論文名稱(英文) Developing Capability Indices for Measuring the Performance of a Multidimensional Machining Process under Non-normal Distributions
校院名稱 成功大學
系所名稱(中) 統計學系
系所名稱(英) Department of Statistics
學年度 107
學期 2
出版年 108
研究生(中文) 廖聆禹
研究生(英文) Ling-Yu Liao
學號 R26061087
學位類別 碩士
語文別 中文
論文頁數 37頁
口試委員 指導教授-潘浙楠
口試委員-李俊毅
口試委員-鄭春生
中文關鍵字 製程能力指標  非常態分配  位置容差 
英文關鍵字 process capability index  non-normal distribution  positional tolerance 
學科別分類
中文摘要 在生產製造的過程中,製程能力指標(Process Capability Index)通常是用來衡量產品或製程品質是否具有符合工程規格的能力。一般而言,多維切割製程之規格區域為位置容差之特殊規格。過去幾十年來已有多位學者致力於多維切割製程能力指標之研究,但彼等的研究大多假設製程服從多變量常態下制定。然而實務上,許多製造過程,如奈米切割製程產出的分佈常出現不服從常態分配的情況。因此,本研究之目的主要係希望提出能正確反映製程良率之非常態多維切割製程能力指標。
我們首先利用Scaled Weighted Variance (SWV)方法對Pan和Li (2014)之NPC_p與 NPC_pk指標進行修正,並據此推導出非常態多維切割製程能力指標RNPC_p與RNPC_pk。接著,我們以數值計算的方式比較在不同參數組合之非常態分配下,各多維切割製程能力指標之表現。結果發現本研究所提出之RNPC_p與RNPC_pk指標均能正確反映非常態多維切割製程之表現。
最後,我們以一筆奈米切割製程之實際資料進行數值實例的探討及驗證,說明本研究所提出之新指標可正確的評估非常態多維切割製程的風險。
英文摘要 Process capability index (PCI) is commonly used to measure the capability of a manufacturing process and evaluate whether it can meet the engineering specifications in industries. Generally speaking, the multidimensional machining process has a specific specification called the positional tolerance. In the past decades, many scholars including Krishamoorthi (1990), Davis et al. (1992), Pan and Li (2014), etc. have devoted themselves to developing capability indices for multidimensional machining processes based on the assumption of normality. However, in practical applications, many manufacturing processes, such as nano-cutting process may not follow normal distribution. Thus, by relieving the normality assumption, this paper aims to propose new non-normal capability indices that can correctly reflect the true nonconforming rate for multidimensional machining processes.
We first use Scaled Weighted Variance (SWV) method to revise NPC_p and NPC_pk indices proposed by Pan and Li (2014). Then, the two new indices RNPC_p and RNPC_pk can be derived accordingly. In the numerical calculation studies, we compare the performance among various multidimensional machining process capability indices under different parameter combinations for non-normal distributions. The numerical calculation results show that our proposed indices can properly reflect the actual performance for non-normal multidimensional machining processes.
Finally, a nano-cutting example is used to demonstrate that the proposed indices are suitable to assess the risk of non-normal multidimensional machining processes.
論文目次 第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究架構 3
第二章 文獻回顧與探討 5
2.1 單變量製程能力指標 5
2.2 多變量製程能力指標 6
2.3 常態多維切割製程能力指標 7
2.4 Scaled Weighted Variance方法 9
2.5 非常態製程能力指標C_p^SWV和C_pk^SWV 12
第三章 非常態多維切割製程能力指標 13
3.1 非常態多維切割製程能力指標之制定 13
3.2 驗證當製程呈對稱分配時之指標 19
3.3 比較各多維切割製程能力指標在不同非常態分配下之表現 20
3.3.1 分配之設定 20
3.3.2 比較準則與待評估之指標 23
3.3.3 指標值之計算結果 24
第四章 數值實例分析與探討 30
第五章 結論與未來方向 34
5.1 結論 34
5.2 未來研究方向 35
參考文獻 36
參考文獻 1.Borrini, C. G., Cazzaro, M., & Chiodini, P. M. (2010). “Measuring Process Capability under non classical assumptions: a purposive review of the relevant literature”, Statistica Applicanta-Italian Journal of Applied Statistics, 22(3), 279-306.
2.Castagliola, P. (2000). “ ar{X} Control Chart for Skewed Populations Using a Scaled Weighted Variance Method”, International Journal of Reliability, Quality and Safety Engineering, 7(3), 237-252.
3.Chan, L. K., Cheng, S. W., & Spiring, F. A. (1988). “A new measure of process capability: Cpm”, Journal of Quality Technology, 20(3), 162-175.
4.Chan, L. K., Cheng, S. W., & Spiring, F. A. (1991). “A multivariate measure of process capability”, International Journal of Modeling and Simulation, 11(1), 1-6.
5.Chang, Y.S., & Bai, D.S. (2004). “A multivariate T^2control chart for skewed populations using weighted standard deviations”, Quality and Reliability Engineering International, 20(1), 31-46.
6.Chang, Y. (2013). “Heuristic Process Capability Indices Using Distribution-decomposition Methods”, Journal of the Korean Society for Quality Management, 41(2), 233.
7.Choobineh, F., & Branting, D. (1986). “A simple approximation for semivariance”, European Journal of Operational Research, 27(3), 364-370.
8.Davis, R. D., Kaminsky, F. C., & Saboo, S. (1992). “Process capability analysis for process with either a circular or a spherical tolerance zone”, Quality Engineering, 5(1), 41-54.
9.Juran, J. M. (1974). Quality Control Handbook, McGraw-Hill, New York.
10.Kane, V. E. (1986). “Process Capability Indices”, Journal of Quality Technology, 18(1), 41-52.
11.Karl, D. P., Morisette, J., & Taam, W. (1994). “Some applications of a multivariate capability index in geometric dimensioning and tolerancing”, Quality Engineering, 6(4), 649-665.
12.Krishnamoorthi, K. S. (1990). “Capability indices for processes subject to unilateral and positional tolerances”, Quality Engineering, 2(4), 461-471.
13.Pan, J. N., & Li, C. I. (2014). “New capability indices for measuring the performance of a multidimensional machining process”, Expert Systems with Applications, 41(5), 2409-2414.
14.Pearn, W. L., Kotz, S., & Johnson, N. L. (1992). “Distributional and inferential properties of process capability indices”, Journal of Quality Technology, 24(4), 216-231.
15.Taam, W., Subbaiah, P., & Liddy, J. W. (1993). “A note on multivariate capability indices”, Journal of Applied Statistics, 20(3), 339-351.
16.Wang, F. K. & Chen, J. C. (1998). “Cpability index using principal component analysis”, Quality Engineering, 11(1), 21-27.
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