Browsing by Author "Wu, Chien-Wei"

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A comparison of methods for estimating loss-based capability index
(2009)
Wu, Chien-Wei
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Shu, Ming-Hung
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Pearn, W. L.
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Cheng, Feng-Tsung
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工業工程與管理學系
The process capability index Cpm, sometimes called the loss-based index, has been proposed to the manufacturing industry for measuring process reproduction capability. This index incorporates the variation of production items with respect to the target value and the specification limits preset in the factory. To estimate the loss-based index properly and accurately, certain frequentist and Bayesian perspectives have been proposed to obtain lower confidence bounds (LCBs) for providing minimum process capability. The LCBs not only provide critical information regarding process performance but are also used to determine whether an improvement was made in a capability index and by extension in reducing the fraction of non-conforming items. In this paper, under the assumption of normality, based on frequentist and Bayesian senses, several existing approaches for constructing LCBs of Cpm are presented. Depending on the statistical methods used, we then classify these existing approaches into three categories and compared them in terms of the coverage rates and the mean values of the LCBs via simulations. The relative advantages and disadvantages of these approaches are summarized with some highlights of the relevant findings.
A variables sampling plan based on C-pmk for product acceptance determination
(2008-01-16)
Wu, Chien-Wei
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Pearn, W. L.
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工業工程與管理學系
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Department of Industrial Engineering and Management
Process capability indices are useful management tools, particularly in the manufacturing industry, which provide common quantitative measures on manufacturing capability and production quality. Most supplier certification manuals include a discussion of process capability analysis and describe the recommended procedure for computing a process capability index. Acceptance sampling plans have been one of the most practical tools used in classical quality control applications. It provides both vendors and buyers to reserve their own rights by compromising on a rule to judge a batch of products. Both sides may set their own safeguard line to protect their benefits. Two kinds of risks are balanced using a well-designed sampling plan. In this paper, we introduce a new variables sampling plan based on process capability index C-pmk to deal with product sentencing (acceptance determination). The proposed new sampling plan is developed based on the exact sampling distribution hence the decisions made are more accurate and reliable. For practical purpose, tables for the required sample sizes and the corresponding critical acceptance values for various producer's risk, the consumer's risk and the capability requirements acceptance quality level (AQL), and the lot tolerance percent defective (LTPD) are provided. A case study is also presented to illustrate how the proposed procedure can be constructed and applied to the real applications. (C) 2006 Elsevier B.V. All rights reserved.
Accuracy analysis of the percentile method for estimating non normal manufacturing quality
(2007)
Wu, Chien-Wei
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Pearn, W. L.
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Chang, C. S.
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Chen, H. C.
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工業工程與管理學系
Vannman ( 1995) proposed a superstructure C-p(u, v) of capability indices for processes with normal distributions, which include C-p, C-pk, C-pm, and C-pmk as special cases. Pearn and Chen (1997) considered a generalization of C-p(u, v), called C-Np(u, v), to cover processes with non normal distributions. Pearn and Chen ( 1997) also proposed a sample percentile estimator for the generalization C-Np(u , v). In this article, we investigate the performance of the sample percentile estimator. We perform some simulation study, which covers the normal distribution and various non normal distributions including the uniform distribution, chi-square distribution, student's t distributions, F distribution, beta distribution, gamma distribution, Weibull distribution, lognormal distribution, triangular distribution, and Laplace distribution, with selected parameter values. Extensive simulation results, comparisons, and analysis are provided.
An effective decision making method for product acceptance
(2007-02-01)
Pearn, W. L.
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Wu, Chien-Wei
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工業工程與管理學系
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Department of Industrial Engineering and Management
Acceptance sampling plans are practical tools for quality assurance applications involving quality contract on product orders. The sampling plans provide the vendor and buyer decision rules for product acceptance to meet the preset product quality requirement. As the rapid advancement of manufacturing technology, suppliers require their products to be of high quality with very low fraction of defectives often measured in parts per million. Unfortunately, traditional methods for calculating fraction of defectives no longer work since any sample of reasonable size probably contains no defective product items. In this paper, we introduce an effective sampling plan based on process capability index C-pk to deal with product acceptance determination for low fraction of defectives. The proposed new sampling plan is developed based on the exact sampling distribution rather than approximation. Practitioners can use the proposed method to determine the number of required inspection units, the critical acceptance value, and make reliable decisions in product acceptance. (c) 2005 Elsevier Ltd. All rights reserved.
An overview of theory and practice on process capability indices for quality assurance
(2009-02-01)
Wu, Chien-Wei
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Pearn, W. L.
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Kotz, Samuel
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工業工程與管理學系
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Department of Industrial Engineering and Management
Process capability indices (PCIS), C(p), C(a), C(pk), C(pm), and C(pmk) have been developed in certain manufacturing industry as capability measures based on various criteria, including process consistency, process departure from a target, process yield, and process loss. It is noted in certain recent quality assurance and capability analysis works that the three indices, C(pk), C(pm), and C(pmk) provide the same lower bounds on the process yield. In this paper, we investigate the behavior of the actual process yield, in terms of the number of non-conformities (in ppm), for processes with fixed index values of C(pk) = C(pm) = C(pmk), possessing different degrees of process centering. We also extend Johnson's [1992. The relationship of C(pm) to squared error loss. journal of Quality Technology 24, 211-215] result formulating the relationship between the expected relative squared loss and PCIs. Also a comparison analysis among PCIs is carried out based on various criteria. The result illustrates some advantages of using the index C(pmk) over the indices C(pk) and C(pm) in measuring process capability (yield and loss), since C(pmk) always provides a better protection for the customers. Additionally, several extensions and applications to real world problem are also discussed. The paper contains some material presented in the Kotz and Johnson [2002. Process capability indices-a review, 1992-2000. journal of Quality Technology 34(1),1-19] survey but from a different perspective. It also discusses the more recent developments during the years 2002-2006. (C) 2009 Elsevier B.V. All rights reserved.
Balanced carrier transport in organic solar cells employing embedded indium-tin-oxide nanoelectrodes
(2011-02-14)
Hsu, Min-Hsiang
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Yu, Peichen
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Huang, Jen-Hsien
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Chang, Chia-Hua
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Wu, Chien-Wei
In this paper, we present evidence of balanced electron and hole transport in polymer-fullerene based solar cells by means of embedded indium-tin-oxide nanoelectrodes. Enabled by a controllable electrochemical deposition, the individual nanoelectrodes are uniformly enclosed by a poly (3,4-ethylenedioxythiophene) hole-conducting layer, allowing a relatively short route for holes to reach the anode and hence increasing the effective hole mobility. Consequently, the power conversion efficiency and photogenerated current are maximized with a deposition condition of 50 mu C, where the ratio of the electron to hole mobility is nearly unity. (C) 2011 American Institute of Physics. [doi:10.1063/1.3556565]
Balanced carrier transport in organic solar cells employing embedded indium-tin-oxide nanoelectrodes (vol 98, 073308, 2011)
(2011-03-14)
Hsu, Min-Hsiang
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Yu, Peichen
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Huang, Jen-Hsien
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Chang, Chia-Hua
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Wu, Chien-Wei
Bayesian approach for measuring EEPROM process capability based on the one-sided indices C-PU and C-PL
(2006-11-01)
Wu, Chien-Wei
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Pearn, W. L.
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工業工程與管理學系
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Department of Industrial Engineering and Management
The purpose of process capability analysis is to provide numerical measures on whether a process is capable of reproducing items meeting the manufacturing specifications. Capability analyses have received considerable recent research attention and increased usage in process assessments and purchasing decisions. Most existing research works on capability analysis focus on estimating and testing process capability based on the traditional distribution frequency approach. In this paper, we propose a Bayesian approach based on the indices C-PU and C-PL to measure EEPROM process capability, in which the specifications are one-sided rather than two-sided. We obtain the credible intervals of C-PU and C-PL and develop a Bayesian procedure for capability testing. The posterior probability p, for which the process under investigation is capable, is derived. The credible interval is a Bayesian analog of the classical lower confidence interval. A process satisfies the manufacturing capability requirements if all the points in the credible interval are greater than the pre-specified capability level w. To make this Bayesian procedure practical for in-plant applications, a real example of an EEPROM manufacturing process is investigated, demonstrating how the Bayesian procedure can be applied to actual data collected in the factories.
Estimating and testing process accuracy with extension to asymmetric tolerances
(2010-08-01)
Wu, Chien-Wei
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Shu, Ming-Hung
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Pearn, W. L.
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Tai, Yi-Chang
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工業工程與管理學系
Pearn et al. (Commun. Stat. Theory Methods, 27(4):985-1000, 1998) introduced the process accuracy index C(a) to measure the degree of process centering, the ability to cluster around the center. In this paper, we derive an explicit form of the cumulative distribution function for the estimator (C) over cap (a) with the case of symmetric tolerances. Subsequently, the distributional and inferential properties of the estimated process accuracy index C(a) are provided. Calculations of the critical values, P-values, and lower confidence bounds are developed for testing process accuracy. Further, a generalization of C(a) for the case with asymmetric tolerances is proposed to measure the process accuracy. Based on the results practitioners can easily perform the testing of the process accuracy, and make reliable decisions on whether actions should be taken to improve the process quality. An application is given to illustrate how we test the process accuracy using the actual data collected from the factory.
High Q/V-m hybrid photonic-plasmonic crystal nanowire cavity at telecommunication wavelengths
(2015-01-01)
Chiang, Chih-Kai
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Chung, Yi-Cheng
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Cheng, Pi-Ju
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Wu, Chien-Wei
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Chang, Shu-Wei
We haw analyzed a hybrid photonic-plasmonic crystal nanocavity consisting of a silicon grating nanowire adjacent to a metal surface with a gain gap between. The hybrid plasmonic cavity modes are highly confined in the gap due to the coupling of photonic crystal cavity modes and surface plasmonic gap modes. Using the finite-element method, we numerically solve guided modes of the hybrid plasmonic waveguide at a wavelength of 1.55 jim. The modal characteristics such as wave guide confinement factors and modal losses of the fundamental hybrid plasmonic modes are explored as a function of the groove depth at various gap heights. After that, we show the band structure of the hybrid crystal modes, corresponding to a wide band gap of 17.8 THz. To effectively trap the optical modes, we introduce a single defect into the hybrid crystal. At a deep sub-wavelength defect length as small as 180 nm, the resonant mode exhibits a high quality factor of 566.5 and an ultrasmall mode volume of 0.00186 (ln)3 at the resonance wavelength of 1.55 gm. In comparison to the conventional photonic crystal nanowire cavity in the absence of metal surface, the figure of merit QIVm is enormously enhanced around 15 times. The proposed nanocavities open up the opportunities for various applications with strong light-matter interaction such as nanolasers and bio sensors.
Measuring process performance based on expected loss with asymmetric tolerances
(2006-12-01)
Pearn, W. L.
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Chang, Y. C.
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Wu, Chien-Wei
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工業工程與管理學系
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Department of Industrial Engineering and Management
By approaching capability from the point of view of process loss similar to C-pm, Johnson (1992) provided the expected relative loss Le to consider the proximity of the target value. Putting the loss in relative terms, a user needs only to specify the target and the distance from the target at which the product would have zero worth to quantify the process loss. Tsui (1997) expressed the index L-e as Le = L-ot + L-pe, which provides an uncontaminated separation between information concerning the process relative off-target loss (L-ot) and the process relative inconsistency loss (L-ot). Unfortunately, the index L-e inconsistently measures process capability in many cases, particularly for processes with asymmetric tolerances, and thus reflects process potential and performance inaccurately. In this paper, we consider a generalization, which we refer to as L-e", to deal with processes with asymmetric tolerances. The generalization is shown to be superior to the original index L-e. In the cases of symmetric tolerances, the new generalization of process loss indices L-e", L-ot" and L-pe" reduces to the original index L-e, L-ot, and L-pe, respectively. We investigate the statistical Properties of a natural estimator of L-e" L-ot" and L-pe" when the underlying process is normally distributed. We obtained the rth moment, expected value, and the variance of the natural estimator (L) over cap (e)", (L) over cap (ot)", and (L) over cap (pe)". We also analyzed the bias and the mean squared error in each case. The new generalization V measures process loss more accurately than the original index L-e.
Multiple-process performance analysis chart based on process loss indices
(2006-06-10)
Pearn, W. L.
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Chang, Y. C.
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Wu, Chien-Wei
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工業工程與管理學系
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Department of Industrial Engineering and Management
Control chart techniques have been widely used in the manufacturing industry for controlling and monitoring process performance and are practical tools for quality improvement. When dealing with variable data, one usually employs the (X) over bar chart and R chart ( or S chart) to detect the process mean and process variance change. These charts are easy to understand and effectively communicate critical process information without using words and formulae. In this paper, we develop a new multiple-process performance analysis chart (MPPAC), using the process loss index L-e to control the product quality and/or reliability for multiple manufacturing processes. Upper confidence bounds are applied to the L-e MPPAC to ensure the capability groupings are accurate, which is essential to product quality assurance. The L-e MPPAC displays the multiple-process relative inconsistency and process relative off-target degree on one single chart in order to provide simultaneous capability control for multiple processes. We demonstrate the applicability of the proposed L-e MPPAC incorporating the upper confidence bounds by presenting a case study on some liquid-crystal display module manufacturing processes, to evaluate the factory performance.
On the sampling distributions of the estimated process loss indices with asymmetric tolerances
(2007)
Chang, Y. C.
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Pearn, W. L.
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Wu, Chien-Wei
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工業工程與管理學系
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Department of Industrial Engineering and Management
Pearn et al. (2006a) proposed a new generalization of expected loss index L-e '' to handle processes with both symmetric and asymmetric tolerances. Putting the loss in relative terms, a user needs only to specify the target and the distance from the target at which the product would have zero worth to quantify the performance of a process. The expected loss index L-e '' may be expressed as L-e '' = L-ot '' + L-pe '' which provides an uncontaminated separation between information concerning the process accuracy and the process precision. In order to apply the theory of testing statistical hypothesis to test whether a process is capable or not under normality assumption, in this paper we first derive explicit form for the cumulative distribution function and the probability density function of the natural estimator of the three indices L-ot '', L-pe '', and L-e ''. We have proved that the sampling distributions of (L) over cap (pe)'' and (L) over cap (ot)'' may And the distribution of (L) over cap (e)'' can be described in terms of a mixture of the chi-square distribution and the normal distribution. Then, we develop a decision-making rule based on the estimated index (L) over cap (e)''. Finally, an example of testing L-e '' is also presented for illustrative purpose.
Two Tests for Supplier Selection Based on Process Yield
(2011-03-01)
Pearn, W. L.
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Liao, Mou-Yuan
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Wu, Chien-Wei
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Chu, Yao-Tsung
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工業工程與管理學系
Market share is highly corrected with customer satisfaction and business success; many companies increase their outsourcing level to keep their core competition. Supplier selection problems have become an important issue of production management. Process yield is a standard criterion in the manufacturing industry as a common measure on process performance. The index S(PK) provides an exact measure on the process yield for normal processes. However, most studies considered the assessment of index S(PK) for just one single supplier; the testing procedure for suppliers selection has not been done at present. Hence, the principal purpose of this research is to determine the more capable process between two competing suppliers. Two tests are presented based on S(PK), and four bootstrap methods are used for obtaining the test statistics. By Monte Carlo simulations, performance comparisons of these methods are performed in terms of empirical size and selection power. Finally, a case on the color filter manufacturing process is investigated to demonstrate the applicability of the proposed method.