• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.549-555
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• 2009

The research proposes two calculation methods for estimating the overall, within and between standard deviation of population. These standard deviations can be used to evaluate the process capability and performance indexes. The guidelines for using $C_{PK}$ and $P_{PK}$ according to the pattern of common and assignable causes are presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.67
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• pp.11-18
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• 2001

The efficiency and robustness of the scale estimator based on the Gini's mean difference are well known in Nam et al.(2000). In this paper we propose use of robust control limits based on the Gini's mean difference for the control of the process deviation. To compare the performances of the proposed control chart with the existing R-chart or S-chart, some Monte Carlo simulations are performed. The simulation results show that the use of the Gini's mean difference in construction of the control limits has good performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.41-49
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• 2017

Process quality control, which prevents problems and risks that may occur in products and processes, has been recognized as an important issue, and SPC techniques have been used for this purpose. Process Capability Index (PCI) is useful Statistical Process Control (SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. $C_p$ and $C_{pk}$ are traditional PCIs. These traditional $C_p$ and $C_{pk}$ were used only as a measure of process capability, taking into account the quality variance or the bias of the process mean. These are not given information about the characteristic value does not match the target value of the process and this has the disadvantage that it is difficult to assess the economic losses that may arise in the enterprise. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. $C_{pm}$ is considers both the process variation and the process deviation from target value. And $C_{pm}{^+}$ is considers economic loss for the process deviation from target value. In this paper we developed an improved Expected Loss Capability Index using Reflected Normal Loss Function of Spring. This has the advantage that it is easy to realistically reflect the loss when the specification is asymmetric around the target value. And check the correlation between existing traditional process capability index ($C_{pk}$) and new one. Finally, we propose the criteria for classification about developed process capability index.

• Journal of the Korean Mathematical Society
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• v.42 no.6
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• pp.1215-1230
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• 2005

In this paper we establish some results on the increments of a d-dimensional Gaussian process with the usual Euclidean norm. In particular we obtain the law of iterated logarithm and the Book-Shore type theorem for the increments of ad-dimensional Gaussian process, via estimating upper bounds and lower bounds of large deviation probabilities on the suprema of the d-dimensional Gaussian process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.20-21
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• 2002

Recently, Lee[European J. Operational Research 129(2001) 682-688] calculated standard deviation of fuzzy numbers in order to obtain the membership function of the process capacity index (PCI) $C^{pk}$. In this note, we show that his result is not valid.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.117-124
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• 2017

In this study, we investigated the optimization of process conditions by using the Six Sigma process, design of experiment (DOE) method and response surface method (RSM) to resolve dimensional deviation and appearance problems arising from the shortened process time of the mobile phone rear cover. The analysis of the trivial many was performed by 2-sample T-test and cooling time, and mold temperature and packing pressure were selected as the vital fews affecting the overall width of the product. The optimal conditions of the process were then studied using the DOE and the RSM. We analyzed the improvement effects by applying the selected optimal conditions to the production process and the results showed that the difference between the mean value and target value of the overall width stood at 0.01 mm, an improvement of 88.89% compared to current process that fell within the range of standard dimension. The short-term process capability stood at $4.77{\sigma}$, which implied an excellent technology level despite a decrease by $0.22{\sigma}$ compared to the current process. The difference in process capability decreased by $2.44{\sigma}$ to $0.41{\sigma}$, showing a significant improvement in management capability. Ultimately, the process time of the product was shortened from 18.3 seconds in the current process to 13.65 seconds, resulting in a 34.07% improvement in production yield.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.2
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• pp.51-58
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• 2015

In this study, we developed an automated non-contact thickness measurement machine that continuously and precisely measures the thickness and warp of a PCB product using a laser sensor. The system contains a measurement part to measure the thickness in real time automatically according to the set conditions with an alignment supply unit and unloading unit to separate OK and NG products. The measurement machine was utilized to evaluate the performance at each step to minimize measurement error. At the zero setting for the initial setup, the standard deviation of the 216 samples was determined to be $5.52{\mu}m$. A measurement error of 0.5mm and 1.0mm as a standard sample in the measurement accuracy assessment was found to be 2.48% and 2.28%, respectively. In the factory acceptance test, the standard deviation of 1.461mm PCB was measured as $28.99{\mu}m$, with a $C_{pk}$ of 1.2. The automatic thickness measurement machine developed in this study can contribute to productivity and quality improvement in the mass production process.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1062-1070
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• 2009

The strip shape for the stainless steel process has made an issue of the strip quality, and hence the shape control method is developed at the Sendzimir rolling mill (ZRM). ZRM is a stainless cold rolling mill and has actuators for the shape control. They are first intermediate rolls and top crown rolls, which are controlled horizontally and vertically, respectively. The shape control of the stainless steel rolling process has difficulty in obtaining the symmetrical shape. The objective of the shape control is to minimize the shape deviation and to maintain stable state, which keeps symmetrical shape pattern in the lateral direction. The method of the shape recognition employs a least squares method and neural network. The shape deviation is the difference between the target shape and actual shape and is controlled by the fuzzy shape control. The fuzzy shape control using operator's informative knowledge is proposed in this paper. The experiments are carried out online for various stainless materials and sizes. The productivity of the rolling process has increased from 9.0 to 9.4 tons per hour.

• Journal of the Korean Ceramic Society
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• v.44 no.4 s.299
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• pp.235-239
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• 2007

For the pressure compaction process of the ceramic powder, the density distribution is very important for the uniform shrinkages at the sintered body. In this paper, we fabricated alumina green body using compaction process and simulated about same condition. Then comparison of simulation and experimental result confirmed that accuracy of simulation. On the average density of top and lower part was each $2.41g/cm^3,\;2.27g/cm^3$ and deviation at final step was calculated with 0.06 in simulation. Also, experiments show that total density of top and lower part was each $2.59g/cm^3,\;2.36g/cm^3$, and deviation was 0.09. Conclusion, that was not a difference to the simulation and experimental result. The application using the finite element simulation method is possible optimization of the compressing process, predict generated part of cracks and there is a possibility of getting result of more fast, more accurate then existing experience method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.1006-1012
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• 2010

The hot rolling process ranks the highest position for production in steel making process. The hot strip manufacturing processes consist of the reheating furnace, roughing and finishing mill and coiler. The reheating furnace heats the slab. The roughing and finishing mill produce the hot strip from slab. The hot strip quality mainly depends on finishing mill, which consists of 4-high 7 stands. The looper is installed between stands and is used for controlling the strip tension by the looper angle for better material flow. It is difficult to control the strip tension with the coupled looper system from interaction between the looper angle and strip tension. Too much deviation of strip tension severely affects the poor width quality of the hot strip. It is important to control simultaneously both the looper angle and strip tension with each of their target values. This paper proposes the fuzzy tension control, which is developed to minimize the width deviation of the hot strip by maintaining the proper strip tension between stands and to achieve the stable operation of the coupled looper system. The fuzzy tension control performance is compared with the conventional PID control by experimental results.