• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.102-111
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• 2021

Maintainability is a major design parameter that includes availability as well as reliability in a RAM (reliability, availability, maintainability) analysis, and is an index that must be considered when developing a system. There is a lack of awareness of the importance of predicting and analyzing maintainability; therefore, it is dependent on past-experience data. To improve the utilization rate, maintainability must be managed as a key indicator to meet the user's requirements for failure maintenance time and to reduce life-cycle costs. To improve the maintainability-prediction accuracy in the detailed design stage, we present a maintainability-prediction method that applies Method B of the Military Standardization Handbook (MIL-HDBK-472) Procedure V, as well as a Korean maintainability-prediction software package that reflects the system complexity.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.163-166
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• 2005

A hole expansion process is an important process in producing a hub-hole in a wheel disc of a vehicle. In this process, the main parameter is the formability of a material that is expressed as the hole expansion ratio. The hub-hole expansion process is different from conventional forming processes or hole flanging processes from the view-point of its deformation mode and forming of a thick plate. In the process, a crack is occurred in the upper edge of a hole as the hole is expanded. Since prediction of the forming limit by hole expansion experiment needs tremendous time and effort, an appropriate fracture criterion has to be developed fur finite element analysis to define forming limit of the material. In this paper, the hole expansion process of a hub-hole is studied by finite element analysis with ABAQUS/standard considering several ductile fracture criteria. The fracture mode and hole expansion ratio is compared with respect to the various fracture criteria. These criteria do not predict its fracture mode or hole expansion ratio adequately and show deviation from experimental results of hole expansion. A modified ductile fracture criterion is newly proposed to consider the deformation characteristics of a material accurately in a hole expansion process. A fracture propagation analysis at the hub-hole edge is also performed for high accuracy of prediction using the new fracture criterion proposed.

• Design & Manufacturing
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• v.17 no.4
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• pp.72-78
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• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.203-209
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• 1999

In this paper, we present the methods to predict the milled surface shapes in profile milling process. In the cutting process, tools are deflected due to the cutting forces varying with the imposed depth of cut and feedrate. Thus, the final shapes of the milled surface, generated by the nominal tool trajectory, are different from the required profile. In order to predict the milled surface shapes, we present two methods based on: (1) the deflected tool profile and (2) the trace of contact point between the tool and the workpiece. In the first method, we make an assumption that the milled surface corresponds to the deflected tool profile. In another method, we make we make an assumption that the milled surface is generated by the trace of the contact point between the cutting edge of the tool and workpiece. We present the surface generation process by calculating the trajectory of the contact points on the workpiece. Several simulations and experiments are performed to verify the proposed milled surface prediction methods.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.932-941
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• 1993

High moisture content of barley seeds, which were carried to the laboratory within 10 minutes after harvest, were stored in air tight bottle at constant temperature, and the individual moisture contents the grains were measured at predecided tim intervals. The theory of predicting the moisture movement between two kinds of different moisture content grains was tried to apply to the prediction of the moisture distribution and tried to apply to the prediction of the moisture distribution and the comparison of the predicted values with the observed dta showed the good suitability of the theory. The shape of the moisture distribution predicted form the theory were similar to the observed ones for the temperature range of 10 to $50^{\circ}C$. This study will be useful in designing the mix-storage facility or dryer.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.2
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• pp.213-218
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• 2008

Prediction models for post-chlorination require complicated information of reaction time, chlorine dosage considering flow rate as well as environmental conditions such as turbidity, temperature and pH. In order to operate post-chlorination process effectively, the correlations between inlet and outlet of clear well were investigated to develop prediction models of chlorine dosages in post-chlorination process. Correlations of environmental conditions including turbidity and chlorine dosage were investigated to predict residual chlorine at the outlet of clear well. A linear regression model and autoregressive model were developed to apply for the post-chlorination which take place time delay due to detention in clear well tank. The results from autoregressive model show the correlationship of 0.915~0.995. Consequently, the autoregressive model developed in this study would be applicable for real time control for post chlorination process. As a result, the autoregressive model for post chlorination which take place time delay and have multi parameters to control system would contribute to water treatment automation system by applying the process control algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.266-266
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• 2019

Marine accidents are increasing year by year, and various accidents occur such as engine failure, collision, stranding, and fire. These marine accidents present a risk of large casualties. It is important to prevent accidents beforehand. In this study, we propose a modeling to predict the occurrence of marine accidents by applying the Markov Chain Process that can predict the future based on past data. Applying the proposed modeling, the probability of future marine accidents was calculated and compared with the actual frequency. Through this, a probabilistic model was proposed to prepare a prediction system for marine accidents, and it is expected to contribute to predicting various marine accidents.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2642-2649
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• 2023

A real-time unmeasured dynamic response prediction process for the nuclear power plant pressure pipeline is proposed and its performance is tested in the test-loop system (KAERI). The aim of the process is to predict unmeasurable or unreachable dynamic responses such as acceleration, velocity, and displacement by using a limited amount of directly measured physical responses. It is achieved by combining a well-constructed finite element model and robust inverse force identification algorithm. The pressure pipeline system is described by using the displacement-pressure vibro-acoustic formulation to consider fully filled liquid effect inside the pipeline structure. A robust multiphysics modal projection technique is employed for the real-time sensor synchronized prediction. The inverse force identification method is also derived and employed by using Bathe's time integration method to identify the full-field responses of the target system from the modal domain computation. To validate the performance of the proposed process, an experimental test is extensively performed on the nuclear power plant pressure pipeline test-loop under operation conditions. The results show that the proposed identification process could well estimate the unmeasured acceleration in both frequency and time domain faster than 32,768 samples per sec.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1243-1250
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• 2003

In the present study, hot forging process for a lower arm connector of an automobile was investigated. An FEM code, DEFORM-3D, was used to analyze the process and the process parameters, such as temperature, strain and strain rate, were obtained. The microstructure of the connector was predicted by applying the Sellars and Yada microstructure evolution models to the process parameters. The method of microstructure prediction used in the present study seems to be effective for the quality assurance of a forged automotive product.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.86-89
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• 2002

In NC machining, the ability to automatically generate an optimal process plan is an essential step toward achieving automation, higher productivity, and better accuracy. For this ability, a system that is capable of simulating the actual machining process has to be designed. In this paper, a milling process simulation system for the general NC machining was presented. The system needs first to accurately compute the cutting configuration. ME Z-map(Moving Edge node Z-map) was developed to reduce the entry/exit angle calculation error in cutting force prediction. It was shorn to drastically improve the conventional Z-map model. Experimental results applied to the pocket machining show the accuracy of the milling process simulation system.