• Journal of Digital Convergence
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• v.11 no.7
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• pp.83-95
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• 2013

Supply chain management for engineering project focuses on planning acquisitions, identifying and choosing the right suppliers and subcontractors, planning and negotiating appropriate contracts, and administering the collaboration with the suppliers and subcontractors. This paper aims to identify the determinants of SCM performance of the suppliers and subcontractors participating in the project-based supply chain. This study proposes the absorptive capacity, fairness of suppliers' evaluation, the quality of collaboration and incentives as major research variables, and collected the survey responses from the suppliers and subcontractors having experiences with major engineering projects. The statistical results indicate that the incentives, absorptive capacity and the quality of collaboration influence SCM performance of suppliers, and that the fairness of suppliers' evaluation has some impact on the incentives and the absorptive capacity. But on the contrary to our expectation, the incentives have no significant impact on the level of absorptive capacity.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.327-330
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• 2007

This paper verifies that the normality assumption that the simulation output data, Project Completion Times (PCTs), follow normal distribution is not always acceptable and the existing belief may lead to misleading results. A risk quantification method, which measures the effect caused by the assumption, relative to the probability distribution of PCTs is implemented as an algorithm in MATLAB. To validate the reliability of the quantification, several series of simulation experiments have been carried out to analyze a set of simulation output data which are obtained from different type of Probability Distribution Function (PDF) assigned to activities'duration in a network. The method facilitates to find the effect of PDF type and its parameters. The procedure necessary for performing the risk quantification method is described in detail along with the findings. This paper contributes to improving the reliability of simulation based scheduling method, as well as increasing the accuracy of analysis results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.345-353
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• 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 the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.19-23
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• 2021

A statistical approach to inspection of the 3-D shape of micro solder balls is proposed, where an optical method with spatially arranged LED and specular reflection is used. The reflected image captured by a vision system was analyzed to calculate the relative displacements of LED's in the image. Also, the statistics of displacements for the solder balls contained in a captured image are used to detect existing defects, and the usefulness of the proposed method is shown via experiments.

• Korean Journal of Construction Engineering and Management
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• v.8 no.2
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• pp.155-163
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• 2007

Multiple parties-owners, engineering and construction contractors, and suppliers involve the delivery process of capital facility projects in the construction industry, and each party obtains or provides their workforce, material, equipment, or service tied into specific contracts. Considering that construction projects are based on the contracted relationship between the parties and that contract types are one of the significant factors determining project success. it is critical for project stakeholder to select appropriate contract types for successful deliveries of projects. With these considerations, this paper assesses impacts of different contract types on project cost, schedule, safety, change, or rework. Analyzing data from real construction projects, the differences in project performance between two contract types, Cost Reimbursable and Lump Sum are measured and statistically tested to investigate if the differences are significant. For this analysis, performance metrics developed by Benchmarking and Metrics program, the Construction Industry Institute are used.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.50-60
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• 1998

This paper is concerned with the design of two residual control charts for real-time monitoring of the continuous flow processes. Two different control charts are designed under the situation that observations are correlated each other. Kalman-Filter based model estimation is employed when the process model is known. A black-box approach, based on Back-Propagation Neural Network, is also applied for the design of control chart when there is no prior information of process model. Performance of the designed control charts and traditional control charts is evaluated. Average run length(ARL) is adopted as a criterion for comparison. Experimental results show that the designed control chart using the Neural Network's modeling has shorter ARL than that of the other control charts when process mean is shifted. This means that the designed control chart detects the out-of-control state of the process faster than the others. The designed control chart using the Kalman-Filter based model estimation also has better performance than traditional control chart when process is out-of-control state.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.177-189
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• 2024

The run length is defined as the number of samples or subgroups taken before the control chart statistic exceeds the control limits. Because the distribution of run length is typically asymmetric and has a large variability, it may not be appropriate to use ARL (average run length) alone to design control charts and evaluate performance. In this paper, we introduce the concept of percentile (PL)-based design of control charts, and propose the procedure for PL-based design of EWMA (exponentially weighted moving average) charts. For the PL-based design of EWMA, we present a fitted function for the control chart coefficient, given specific percentile parameters. Additionally, we perform simulations to compare the proposed design with the ARL-based design. The simulation results show that the proposed design yields improvements in monitoring in-control processes while maintaining the ability to detect out-of-control performance.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.339-348
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• 2017

One of the major issues of statistical process control for variables data is monitoring both the mean and the standard deviation. The traditional approach to monitor these parameters is to simultaneously use two seperate control charts. However there have been some works on developing a single chart using a single plotting statistic for joint monitoring, and it is claimed that they are simpler and may be more appealing than the traditonal one from a practical point of view. When using these control charts for variables data, estimating in-control parameters and checking the normality assumption are the very important step. Nonparametric Shewhart-Lepage chart, proposed by Mukherjee and Chakraborti (2012), is an attractive option, because this chart uses only a single control statistic, and does not require the in-control parameters and the underlying continuous distribution. In this paper, we introduce the Shewhart-Lepage chart, and propose the design procedure to find the optimal diagnosis limits when the location and the scale parameters change simultaneously. We also compare the efficiency of the proposed method with that of Mukherjee and Chakraborti (2012).

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.156-168
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• 2004

This research investigates the statistical efficiency of variable sampling size & sampling interval(VSSI) $\bar{X}$ charts under two assignable causes. Algorithms for calculating the average run length(ARL) and average time to signal(ATS) of the VSSI $\bar{X}$ chart are proposed by employing Markov chain method. States of the process are defined according to the process characteristics after the occurrence of an assignable cause. Transition probabilities are carefully derived from the state definition. Statistical properties of the proposed chart are also investigated. A simple procedure for designing the proposed chart is presented based on the properties. Extensive sensitivity analyses show that the VSSI $\bar{X}$ chart is superior to the VSS or VSI $\bar{X}$ chart as well as to the Shewhart $\bar{X}$ chart in statistical sense, even tinder two assignable causes.