:::

詳目顯示

回上一頁
題名:基於製程良率探討情境化抽樣策略之研究
作者:劉時玟
作者(外文):Shih-Wen Liu
校院名稱:國立臺灣科技大學
系所名稱:工業管理系
指導教授:林希偉
吳建瑋
學位類別:博士
出版日期:2016
主題關鍵詞:製程能力指標製程良率允收抽樣作業特性曲線鑑別力Process capability indexprocess yieldacceptance samplinglot sentencingOC curve
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:1
由於科技日新月異的進步與發展,許多電子產品或其他元件必須在嚴格的品質要求下進行生產。因此,為了應付多元且嚴格的市場需求,產品則必須在合乎要求的品質規格下透過穩定的製程進行生產。考慮一個在買賣雙方的交易行為中,一旦生產者將產品送達時,顧客或消費者則必須針對送達的批貨進行品質檢驗以決定是否該接受或拒絕該批產品。
允收抽樣在典型的品質管理和品質保證的相關領域中為一個相當實用的方法。允收抽樣透過生產者與顧客的品質共識,提供一個的決策規則以利貨批判決。因此,本文利用製程良率指標 建立一新型之計量型單次抽樣,更進一步地將其運用在三種不同抽樣策略(重複遞交抽樣、重複群集抽樣和多重相依狀態抽樣)下,使得貨批判決方法更加合適的應用在現今多元化的商業環境。文中不僅探討了三種抽樣策略的使用方法及特性,並比較各抽樣策略的所需樣本及作業特性曲線。最後,更進一步的透過三個實例來說明業者如何使用以 為基準的允收抽樣計畫來達到有效且可靠的貨批判決。
Following by the advance of technology and the innovation, the modern electronic appliances or products are designed with rigorous prerequisites to suffice for various market demands. Consequently, these products should be manufactured under the tolerable specifications and the process of producing goods should substance the consistent quality level (i.e. a stable process). Taking into consideration of a producer-consumer business occasion, once the products are delivered, the buyer should contemplate the quality of submission before accepting or rejecting the entire lot.
Acceptance sampling, one of the most practical tools in classical quality control and assurance applications, which deal with a quality contracting of product orders between the producers and their consumers. Acceptance sampling plans provide decision rules for lot sentencing to meet product quality needs required by producer and consumer. Hence, in the dissertation, a single sampling plan is developed and extensively applied as a reference plan for constructing other three situational sampling plans (resubmitted sampling plan, repetitive group sampling plan and multiple dependent states sampling plan), which can be adequately implemented for various producer-consumer occasions. The properties of each proposed sampling plan are investigated and the comparisons are provided. Finally, implementing with a business contract agreement using the proposed situational sampling plans, three case studies are demonstrated the applicability of our proposed methodologies.
1.Aslam, M., Jun, C. H., Lio, Y.L., Ahmad, M. and Rasool, M. (2011). Group acceptance sampling plans for resubmitted lots under Burr-type XII distributions. Journal of the Chinese Institute of Industrial Engineers, 28(8), 606-615.
2.Aslam, M., Azam, M. and Jun, C.H. (2013(a)). Multiple dependent states sampling plan based on process capability index, Journal of Testing and Evaluating, 41(2), 1-7.
3.Aslam, M., Wu, C.W., Azam, M. and Jun, C.H. (2013(b)). Variables sampling inspection for resubmitted lots based on process capability index for normal distribution items. Applied Mathematical Modelling, 37(3), 667-675.
4.Aslam, M., Wu, C. W, Jun, C. H., Azam, M. and Negrin, I. (2013(c)). Developing a variables repetitive sampling plan based on Cpk with unknown mean and variance. Journal of Statistical Computation and Simulation, 83(8), 1507-1517.
5.Boyles, R. A. (1994). Process capability with asymmetric tolerance. Communication in Statistics: Simulation and Computation, 23(3), 615-643.
6.Balamurali, S., Park, H., Jun, C. H., Kim, K. J. and Lee, J. (2005). Designing of variables repetitive group sampling plan involving minimum average sample number. Communications in Statistics: Simulation and Computation, 34, 799-809.
7.Balamurali, S. and Jun, C. H. (2006). Repetitive group sampling procedure for variables inspection. Journal of Applied Statistics, 33(3), 327-338.
8.Balamurali, S. and Jun, C.H. (2007). Multiple dependent state sampling plans for lot acceptance based on measurement data, European Journal of Operational Research, 180(3), 1221–1230.
9.Balamurali, S. and Jun, C. H. (2009). Designing of a variables two-plan system by minimizing the average sample number. Journal of Applied Statistics, 36(10), 1159-1172.
10.Collani, E. V. (1990). A Note on Acceptance Sampling for Variables, Metrika, 38, 19–36.
11.Chen, K. S., Pearn, W. L. and Lin, P. C. (2003). Capability measures for processes with multiple characteristics, Quality and Reliability Engineering International, 19(2), 101-110.
12.Conn, N. R., Gould, N. I. M. and Toint, Ph. L. (2000). Trust-Region Methods, Baker & Taylor Books, Charlotte, North Carolina.
13.Chapra, S. C. (2012) Applied mathematical methods (3rd ed.), The McGraw Hill companies, New York.
14.Dodge, H. F. and Romig, H. G. (1941). Single sampling and double sampling inspection tables, The Bell System Technical Journal, 20(1), 1–61.
15.Das, N. G. and Mitra, S. K. (1964). The effect of non-normality on sampling inspection. Sankhya, Series A, 26(2-3), 169-176.
16.Duncan, A. J. (1986). Quality Control and Industrial Statistics (5th ed.). Illinois: Richard D. Irwin.
17.Dodge, H.F. (1955). Chain sampling inspection plan, Industrial Quality Control, 11(4), 10–13.
18.Govindaraju, K. and Soundararajan, V. (1986). Selection of single sampling plans for variables matching the MIL-STD-105 scheme, Journal of Quality Technology, 18(4), 234-238.
19.Govindaraju, K. and Ganesalingam, S. (1997). Sampling inspection for resubmitted lots. Communication in Statistic: Simulation and Computation, 26(3), 1163-1176.
20.International Organization for Standardization (ISO). (2006) Statistic-Vocabulary and Symbols-Part 2, Applied Statistics, (ISO 3534-2). Geneva, Switzerland.
21.Jacobson, L. J. (1949). Nomograph for determination of variables inspection plan for fraction defective, Industrial Quality Control, 6(3): 23–25.
22.Jennett, W. J. and Welch, B. L. (1939). The control of proportion defective as judged by a single quality characteristic varying on a continuous scale. Journal of the Royal Statistical Society, 6(1), 80-88.
23.Kane, V. E. (1986). Process capability indices. Journal of Quality Technology 18(1), 41-52.
24.Kotz, S. and Johnson, N. L. (2002). Process capability indices - A review, 1992-2000. Journal of Quality Technology, 34(1), 1-19.
25.Lee, J. C., Hung, H. N., Pearn, W. L. and Kueng, T. L. (2002). On the distribution of the estimated process yield index . Quality and Reliability Engineering International, 18, 111-116.
26.Lieberman, G. J. and Resnikoff, G. J. (1955). Sampling plans for inspection by variables, Journal of the American Statistical Association, 50(270), 457-516.
27.Lin, C. J. and Pearn, W. L. (2009) Process selection for higher production yield based on capability index. Quality and Reliability Engineering International, 26, 247-258.
28.Lin, C. J. and Kuo, H. H. (2014). Multiple comparisons with the best for supplier selection. Quality and Reliability Engineering International, 30(7), 1083-1092.
29.Liu, S. W. and Wu, C. W. (2014). Design and construction of a variables repetitive group sampling plan for unilateral specification limit. Communications in Statistics: Simulation and Computation, 43(8), 1866-1878.
30.Liu, S. W., Lin, S. W. and Wu, C. W. (2014). A resubmitted sampling scheme by variables inspection for controlling lot fraction nonconforming. International Journal of Production Research, 52(12), 3744-3754.
31.Marucheck, A., Greis, N., Mena, C. and Cai, L. (2011). Product safety and security in the global supply chain: Issues, challenges and research opportunities. Journal of Operations Management, 29(7-8), 707-720.
32.Montgomery, D. C. (2009). Introduction to Statistics Quality Control (6th ed.). Wiley, New York.
33.Mogg, J.M. and Wortham, A.W. (1970) Dependent stage sampling inspection, International Journal of Production Research, 8(4), 385–395.
34.Negrin, I., Parmet, Y. and Schechtman, E. (2009). Developing a sampling plan based on . Quality Engineering, 21, 306-318.
35.Negrin, I., Parmet, Y. and Schechtman, E. (2010). Developing a Sampling Plan Based on - Unknown Variance. Quality and Reliability Engineering International, 27(1), 3-14.
36.Nocedal, J. and Wright, S. J. (1991). Numerical Optimization, Springer-Verlag, New York.
37.Nocedal, J. and Wright, S. J. (2006). Numerical Optimization (2nd ed.). Springer Series in Operations Research, Springer Verlag, New York.
38.Owen, D. B. (1967). Variables sampling plans based on the normal distribution, Technometrics, 9, 417-423.
39.Pearn, W. L. and Wu, C. W. (2006). Critical acceptance values and sample sizes of a variables sampling plan for very low fraction of defectives. Omega – The International Journal of Management Science, 34(1), 90-101.
40.Pearn, W. L. and Wu, C. W. (2007). An effective decision making method for product acceptance. Omega – The International Journal of Management Science, 35(1), 12-21.
41.Pearn, W.L., Lin, G.H. and Wang, K.H. (2004). Normal approximation to the distribution of the estimated yield index , Quality and Quantity, 38(1), 95-111.
42.Pearn, W. L. and Chuang, C. C. (2004). Accuracy analysis of the estimated process yield based on . Quality and Reliability Engineering International, 20, 305-316.
43.Pearn, W. L. and Cheng, Y. C. (2010). Measuring production yield for processes with multiple characteristics, International Journal of Production Research, 48(15), 4519-4536.
44.Dodge, H. F. and Romig, H. G. (1959). Sampling Inspection Tables, Single and Double Sampling (2nd ed.), John Wiley & Sons, New York.
45.Shmueli, G. (2011). Practical Acceptance Sampling: A Hands-On Guide. (2nd ed.). Createspace, Amazon Company, Seattle, Washington.
46.Schiling, E.G. and Neubauer, D.V. (2009). Acceptance Sampling in Quality Control (2nd ed.), Taylor & Francis Group, Boca Raton, Florida.
47.Seidel, W. (1997). Is sampling by variables worse than sampling by attribute? A decision theoretic analysis and a new strategy for inspecting individual lots. The Indian Journal of Statistics, 59, 96-107.
48.Suresh, R. P. and Ramanathan, T. V. (1997). Acceptance sampling plans by variables for a class of symmetric distributions. Communications in Statistics: Simulation and Computation, 1126(4), 1379-1391.
49.Sherman, R. E. (1965). Design and evaluation of repetitive group sampling plan. Technometrics, 7, 11-21.
50.The ANSI/ASQC Standard A2. (1987). Terms symbols and the definitions for acceptance sampling, American Society for Quality control, Milwaukee, Wisconsin.
51.United States Department of Defense. (1989). Military Standard, Sampling Procedures and Tables for Inspection by Attributes (MIL-STD-105E), U.S. Government Printing Office, Washington, D. C.
52.Vardeman, S. B. and Jobe, J. M. (1999). Statistical quality assurance methods for engineerings, Wiley, NewYork, New York.
53.Wan, X., Xu, X. and Ni, T. (2013). The incentive effect of acceptance sampling plans in a supply chain with endogenous product quality. Naval Research Logistic, 60, 111-124.
54.Wang, F. K. (2008). Process yield with measurement errors in semiconductor manufacturing, IEEE Transactions on Semiconductor Manufacturing, 21(2), 279-284.
55.Wortham, A. W. and Baker, R. C. (1976). Multiple deferred state sampling inspection, International Journal of Production Research, 14(6), 719–731.
56.Wu, C. W. (2012). An efficient inspection scheme for variables based on Taguchi capability index. European Journal of Operational Research, 223(1), 116-122.
57.Wu, C. W., Aslam, M. and Jun, C. H. (2012). Variables sampling inspection scheme for resubmitted lots based on the process capability index , European Journal of Operation Research, 217(3), 560-566.
58.Wu, C. W., Liao, M. Y. and Chen, J. C. (2012). An improved approach for constructing lower confidence bound on process yield. European Journal of Industrial Engineering, 6(3), 369-390.
59.Wu, C. W. and Liu, S. W. (2014). Developing a sampling plan by variables inspection for controlling lot fraction of defectives. Applied Mathematical Modelling, 38(9), 2303-2310.
60.Wu, C. W., Liu, S. W. and Lee, A. H. I. (2015). Design and construction of a variables multiple dependent state sampling plan based on process yield. European Journal of Industrial Engineering, 9(6), 819-838.
61.Wu, C. W., Pearn, W. L. and Kotz, S. (2009). An overview of theory and practice on process capability indices for quality assurance. International Journal of Production Economics, 117(2), 338-359.
62.Wu, C. W. and Pearn, W. L. (2008). A variables sampling plan based on Cpmk for product acceptance determination. European Journal of Operation Research, 184 (2), 549-560.
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
QR Code
QRCODE