• Journal of Korean Society for Quality Management
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• v.33 no.3
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• pp.149-155
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• 2005

Cusum control chart is used for the purpose of controling the process mean. We consider the problem related to cusum chart for controling process variance. Previous researches have considered the same problem. The main difficulty shown in the related researches was to derive the ARL function which characterizes the properties of the chart. Sample variance, differently with sample mean, follows chi-squared type distribution, even when the quality characteristics are assumed to be normally distributed. The ARL function of cusum is described by a type of integral equation. Since the solution of the integral equation for non-normal distribution is not known well, people used simulation method instead of solving the integral equation directly, or approximation method by taking logarithm of the sample variance. Recently a new method to solve the integral equation for Erlang distribution was published. Here we consider the steps to apply the solution to the problem of controling process variance.

• Journal of the Korea Society for Simulation
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• v.5 no.2
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• pp.59-72
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• 1996

The purpose of this study is to make an improvement to the batch-means method, which is a procedure to construct a confidence interval(c.i.) for the steady-state process mean of a stationary simulation output process. In the batch-means method, the data in the output process are grouped into batches. The sequence of means of the data included in individual batches is called a batch-menas process and can be treated as an independently and identically distributed set of variables if each batch includes sufficiently large number of observations. The traditional batch-means method, therefore, uses a batch size as large as possible in order to. destroy the autocovariance remaining in the batch-means process. The c.i. prodedure developed and empirically tested in this study uses a small batch size which can be well fitted by a simple ARMA model, and then utilizes the dependence structure in the fitted model to correct for bias in the variance estimator of the sample mean.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.175-190
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• 2001

We propose, a new process capability index $C_{psk}$(WV) applying the weighted variance control charting method for non-normally distributed. The main idea of the weighted variance method(WVM) is to divide a skewed or asymmetric distribution into two normal distributions from its mean to create two new distributions which have the same mean but different standard deviations. In this paper we propose an example, a distributions generated from the Johnson family of distributions, to demonstrate how the weighted variance-based process capability indices perform in comparison with another two non-normal methods, namely the Clements and the Wright methods. This example shows that the weighted valiance-based indices are more consistent than the other two methods in terms of sensitivity to departure to the process mean/median from the target value for non-normal processes. Second method show using the percentage nonconforming by the Pearson, Johnson and Burr systems. This example shows a little difference between the Pearson system and Burr system, but Johnson system underestimated than the two systems for process capability.

• Fibers and Polymers
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• v.2 no.1
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• pp.140-143
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• 2001

To better understand the formation of necking in drawing processes of fibers, strain distributions during drawing processes have been analyzed. For simplicity, one-dimensional incompressible steady flow at a constant temperature was assumed and quasi-static model was used. To describe mechanical properties of solid polymers, non-linear visco-plastic material properties were assumed using the power law type hardening and rate-sensitive equation. The effects of various parameters on the neck formation were matematically analyzed. As material property parameters, strain-hardening parameter, visco-elastic coefficient and strain-rate sensitivity were considered and, for process parameters, the drawing ratio and the process length were considered. It was found that rate-insensitive materials do not reach a steady flow state and the rate-sensitivity plays a key role to have a steady flow. Also, the neck formation is mainly affected by material properties, especially for the quasi-static model. If the process length changes, the strain distribution was found to be proportionally re-distributed along the process line by the factor of the total length change.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.189-199
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• 1992

Standard acceptance sampling plans models the production process as a sequence of independent identically distributed Beruoulli random variables. However, the quality of items sampled sequentially from an ongoing production process often exhibits statistical dependency that is not accounted for in standard acceptance sampling plans. In this paper, a dependent production process is modelled as an ARMA process and as a two-state Markov chain. A simulation study of each is performed. A comparison of the probability of acceptance is done for the simulation method and for the approximation method.

• Transactions of Materials Processing
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• v.20 no.8
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• pp.611-618
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• 2011

Flow forming is an incremental forming process in which rollers are used to form cylindrical parts with repeated turning of both roller and starting material. Both sheet and tube can be used as the starting material. The process is highly useful for producing hollow shaped parts from a tube, with the benefit of the average strain in the final shape being significantly lower than that from a sheet material. In the present study, the flow forming process was studied and optimized for producing a hollow shaped part from seamless steel tube by both experiment and numerical analysis. Upon considering the difficulty of forming seamless steel sheet, the thickness reduction was distributed over several tool paths. In the end, an optimum process condition was attained, and the experiment verified the simulation results.

• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.1-16
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• 2000

This paper considers the problem of determining the optimal process mean and screening specification limits of a surrogate variable associated with product quality under two-stage screening procedure. In two-stage screening, the surrogate variable is inspected first to decide whether an item should be accepted, rejected or additional observations should be taken. If additional observations are required, the performance variable of interest is then observed to classify the undecided items. Assuming that the performance variable and the surrogate variable are jointly normally distributed, the optimal process mean and the screening limits are obtained by maximizing the expected profit which includes selling price, production, reprocessing, inspection and penalty costs. A numerical example is presented and numerical studies are performed to compare the proposed two-stage screening procedure with single-stage screening procedures.

• Journal of the Korea Society for Simulation
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• v.7 no.2
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• pp.137-152
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• 1998

One of the components that constitute the simulation models is the state variables whose values are determined by the time related simulation process. Embedding rule-based expert systems into the simulation models should provide a systematic way of handling these time-dependent variables without distracting the essential problem solving capabilities of the expert systems which are well suited for expressing the decision making function of complex cases. The expert system, however, is inefficient in dealing with the time elapsing characteristics of target system compare to the simulation models. To solve the problem, this paper provides an interruptible inference engine whose inferencing process can be interrupted when the variables' value, which are used as the parameters of the rules, are not yet determined due to the time dependent nature of the state variables. The process is resumed when the variables are ready. The elapse of time is calculated by time-advance function of the simulation model to which the expert system has been embedded. The example modeling shown exploits the embedded interruptible inferencing capability for the controlling and monitoring of metal grating process.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.135-141
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• 2006

Cusum control chart is used for the purpose of controling the process mean. We consider the problem related to cusum chart for controling process variance. Previous researches have considered the same problem. The main difficulty shown in the related researches was to derive the ARL function which characterizes the properties of the chart. Sample variance, differently with sample mean, follows chi-squared type distribution, even when the quality characteristics are assumed to be normally distributed. The ARL function of cusum is described by a type of integral equation. Since the solution of the integral equation for non-normal distribution is not known well, people used simulation method instead of solving the integral equation directly, or approximation method by taking logarithm of the sample variance. Recently a new method to solve the integral equation for Erlang distribution was published. Here we consider the steps to apply the solution to the problem of controling process variance.

• Journal of the Semiconductor & Display Technology
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• v.8 no.2
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• pp.15-21
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• 2009

Atmospheric pressure plasma equipment was successfully applied to the flip chip BGA manufacturing process to improve the uniformity of flux printing process. The problem was characterized as shrinkage of the printed flux layer due to insufficient surface energy of the flip chip BGA substrate. To improve the hydrophilic characteristics of the flip chip BGA substrate, remote DBD type atmospheric pressure plasma equipment was developed and adapted to the flux print process. The equipment enhanced the surface energy of the substrate to reasonable level and made the flux be distributed over the entire flip chip BGA substrate uniformly. This research was the first adaptation of the atmospheric pressure plasma equipment to the flip chip BGA manufacturing process and a lot of possible applications are supposed to be extended to other PCB manufacturing processes such as organic cleaning, etc.