• International Journal of Quality Innovation
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• v.8 no.1
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• pp.137-153
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• 2007

Failure mode and effects analysis (FMEA) is a preventive technique in reliability management field. The successful implementation of FMEA technique can avoid or reduce the probability of system failure and achieve good product quality. The FMEA technique had applied in vest scopes which include aerospace, automatic, electronic, mechanic and service industry. The marking process is one of the back ends testing process that is the final process in semiconductor process. The marking process failure can cause bad final product quality and return although is not a primary process. So, how to improve the quality of marking process is one of important production job for semiconductor testing factory. This research firstly implements FMEA technique in laser marking process improvement on semiconductor testing factory and finds out which subsystem has priority failure risk. Secondly, a CCD position solution for priority failure risk subsystem is provided and evaluated. According analysis result, FMEA and CCD position implementation solution for laser marking process improvement can increase yield rate and reduce production cost. Implementation method of this research can provide semiconductor testing factory for reference in laser marking process improvement.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.41-47
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• 2006

The Renewal process and the Non-homogeneous Poisson process (NHPP) process are probably the most popular models for describing the failure pattern of repairable systems. But both these models are based on too restrictive assumptions on the effect of the repair action. For these reasons, several authors have recently proposed point process models which incorporate both renewal type behavior and time trend. One of these models is the Modulated Power Law Process (MPLP). The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose Bayes estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model. Numerical examples illustrate the estimation procedure.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.11a
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• pp.120-126
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• 2004

The failure modes analysis by the real process method at the head section of rubble mound breakwaters is more important than other failure modes analysis. because this initial failure modes and failure process will lead to the destruction of the structure. The three-dimensional failure modes are discussed using the experimental data with directional waves considering the failure modes. It was processed step by step failure around the head of rubble mound breakwaters. The spacial characteristics of failure mode by real process analysis was well descript at the rubble mound structures.

• Journal of Applied Reliability
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• v.8 no.3
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• pp.113-124
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• 2008

In reliability engineering, failure reporting, analysis, and corrective action system (FRACAS) is an useful tool for effective failure reporting and related operations. FRACAS is generally mainly focused on implementation of its closed-loop process, but also includes various related information which has to be effectively managed such as failure types, failure modes, failure mechanisms, and corrective actions. In this study, we adopt and utilize the concept of process knowledge, and create it through abstraction of FRACAS information. At each step of closed-loop process, the necessary type of knowledge, priority and usability are clearly defined. This study also suggests corresponding management tools such as business process management system, knowledge management system, and their key elements and functions to deal with process knowledge. A prototype system using simple closed-loop process with its process knowledge is presented to demonstrate the feasibility of the proposed work.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.37-41
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• 2018

Process safety technology has developed from qualitative methods such as HAZOP (hazard and operability study) to semi-quantitative methods such as LOPA (layer of protection analysis), and quantitative methods are actively studied these days. Quantitative risk assessment (QRA) is often based on fault tree analysis (FTA). FTA is efficient, but difficult to apply when failure events are not independent of each other. This problem can be avoided using a Markov process (MP). MP requires definition of all possible states, and thus, generally, is more complicated than FTA. A method is proposed in this work that uses an MP model and a Weibull distribution model in order to construct a reliability model for multiple dependent failures. As a case study, a pressure safety valve (PSV) is considered, for which there are three kinds of failure, i.e. open failure, close failure, and gas tight failure. According to recently reported inspection results, open failure and close failure are dependent on each other. A reliability model for a PSV group is proposed in this work that is to reproduce these results. It is expected that the application of the proposed method can be expanded to QRA of various systems that have partially dependent multiple failure states.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.859-870
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• 2011

The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.51-59
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• 2006

The purpose of this paper is to present reliability analysis procedures for repairable systems and apply the procedures for assessing the reliabilities of two subsystems of a specific group of military equipment based on field failure data. The mean cumulative function, M(t), the average repair rate, ARR(t), and analytic test methods are used to determine whether a failure process follows a renewal or non-renewal process. For subsystem A, the failure process turns out to follow a homogeneous Poisson process, and subsequently, its mean time between failures, availability, and the necessary number of spares are estimated. For subsystem B, the corresponding M(t) plot shows an increasing trend, indicating that its failure process follows a non-renewal process. Therefore, its M(t) is modeled as a power function of t, and a preventive maintenance policy is proposed based on the annual mean repair cost.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.122-129
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• 2004

There is an increasing need for large flat panel display devices. PDP (Plasma Display Panel) is one of the most promising candidates for this need. Thermal shock failure of PDP glass during manufacturing process is a critical issue in PDP industry since it is closely related to the product yield and the production speed. In this study, thermal shock resistance of PDP glass is measured by water quenching test and an analysis scheme is described for estimating transient temperature and stress distributions during thermal shock. Based on the experimental data and the analysis results, a simple procedure for predicting the thermal shock failure of PDP glass is proposed. The fast cooling process for heated glass plates can accelerate the speed of PDP production, but often leads to thermal shock failure of the glass plates. Therefore, a design guideline for preventing the failure is presented from a viewpoint of high speed PDP manufacturing process. This design guideline can be used for PDP process design and thermal -shock failure prevention.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.98-103
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• 2016

Purpose: The purpose of this paper is to get a meaningful information for improving manufacturing quality of the products before they are produced in client's manufacturing process. Methods: A variety of data mining techniques have been being used for wide range of industries from process data in manufacturing factories for quality improvement. One application of those is to get meaningful information from process data in manufacturing factories for quality improvement. In this paper, the failure rate at client's manufacturing process is predicted by using the parameters of the characteristics of the product based on PCA (Principle Component Analysis) and regression analysis. Results: Through a case study, we proposed the predicting methodology and regression model. The proposed model is verified through comparing the failure rates of actual data and the estimated value. Conclusion: This study can provide the guidance for predicting the failure rate on the manufacturing process. And the manufacturers can prevent the defects by confirming the factor which affects the failure rate.

• Journal of Information Technology Services
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• v.6 no.3
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• pp.251-272
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• 2007

Although Enterprise Systems (ES) have promised major strategic benefits and process improvements from business and technology integration, their implementation has been plagued by a high failure rate and difficulty in realizing the promised benefits. For the purpose of understanding implementation failures, previous studies have focused on identifying critical success factors (CSFs) for information systems implementation. However, there has been little research on how these CSFs actually lead to successful results. In this study, based on process theory, we examined the process of ES implementation by explaining how the factors of ES implementation influence each other and how interaction among them produces results. Based on a failure case, we then developed a process model of ES implementation thus allowing us to explain the process of ES implementation. The proposed model facilitated an understanding of how repeating patterns of ES failure can be reversed. This model can be used for guiding new ES implementation projects.