• Transactions of Materials Processing
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• v.24 no.4
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• pp.264-271
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• 2015

In the current study, a method was proposed to quantitatively predict the wear and fatigue life of a shearing die in order to determine an effective replacement period for the die. The shearing die model of a retainer manufacturing process was used for the proposed method of quantitative life prediction. The retainer is produced through shearing steps, such as piercing and notching. The shearing die of the retainer is carefully controlled because the dimensional accuracy of the retainer is critical. The fatigue life for the shearing die was predicted using ANSYS considering S-N curves of STD11 and Gerber’s equation. The wear life for the shearing die was predicted using DEFORM-3D considering the Archard’s wear model. Experimental shearing of the retainer was conducted to verify the effectiveness of the proposed method for predicting die life. The fatigue failure of the shearing die was macroscopically measured. The wear depth was measured using a 3D coordinate measuring machine. The results showed that the wear and fatigue life in the FE analysis agree well with the experimental results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1587-1590
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• 2005

A rigid-plastic finite element analysis for the die forging process of a socket ball joint, which is used in the transportation system, was carried out. And also with the results, the elastic stress analysis for the forging die was performed in order to get basic data for the die life prediction. The die fatigue life prediction was simulated using Goodman's and Gerber's equation. The prediction technique for the fatigue life of a forged product, the socket ball joint, using DEFORM-3D is presented and the results are commented upon. Archard's wear model was used for the wear simulation and then the wear simulation and then the wear quantity was quantity was evaluated using volume. In order to prove the wear simulation results to be reliable, wear quantity of the real forging die set in used a forging factory was measured using a 3-dimensional measurement apparatus. The simulation results were relatively in good agreement with the experimental measurements.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.03a
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• pp.94-99
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• 1998

In bulk metal forming processes prediction of tool life is very important for saving production cost and achieving good material properties. Generally the service life of tools in metal forming process is limited to a large extent by wear, fracture and plastic deformation of tools. In case of hot and warm forging processes, tool life depends on wear over 70%. In this study finite element analyses are applied to warm forging and hot forging by adopting suggested wear model. By comparision of simulation and real profile of die, suggested model is verified

• Geomechanics and Engineering
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• v.29 no.3
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• pp.249-258
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• 2022

A disc cutter is an excavation tool on a tunnel boring machine (TBM) cutterhead; it crushes and cuts rock mass while the machine excavates using the cutterhead's rotational movement. Disc cutter wear occurs naturally. Thus, along with the management of downtime and excavation efficiency, abrasioned disc cutters need to be replaced at the proper time; otherwise, the construction period could be delayed and the cost could increase. The most common prediction models for TBM performance and for the disc cutter lifetime have been proposed by the Colorado School of Mines and Norwegian University of Science and Technology. However, design parameters of existing models do not well correspond to the field values when a TBM encounters complex and difficult ground conditions in the field. Thus, this study proposes a series of machine learning models to predict the disc cutter lifetime of a shield TBM using the excavation (machine) data during operation which is response to the rock mass. This study utilizes five different machine learning techniques: four types of classification models (i.e., K-Nearest Neighbors (KNN), Support Vector Machine, Decision Tree, and Staking Ensemble Model) and one artificial neural network (ANN) model. The KNN model was found to be the best model among the four classification models, affording the highest recall of 81%. The ANN model also predicted the wear rate of disc cutters reasonably well.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.143-153
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• 2024

Tunnel Boring Machine (TBM) method is a tunnel excavation method that produces lower levels of noise and vibration during excavation compared to drilling and blasting methods, and it offers higher stability. It is increasingly being applied to tunnel projects worldwide. The disc cutter is an excavation tool mounted on the cutterhead of a TBM, which constantly interacts with the ground at the tunnel face, inevitably leading to wear. In this study quantitatively predicted disc cutter wear using geological conditions, TBM operational parameters, and machine learning algorithms. Among the input variables for predicting disc cutter wear, the Uniaxial Compressive Strength (UCS) is considerably limited compared to machine and wear data, so the UCS estimation for the entire section was first conducted using TBM machine data, and then the prediction of the Coefficient of Wearing rate(CW) was performed with the completed data. Comparing the performance of CW prediction models, the XGBoost model showed the highest performance, and SHapley Additive exPlanation (SHAP) analysis was conducted to interpret the complex prediction model.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.1
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• pp.116-122
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• 1996

In forming processes, die failure must be considered before die design. One of the main reasons of die failure in industrial application of metal forming technologies is wear. The die wear affects the tolerances of formed parts, metal flow and costs of processes etc. The only way to control these failures is to develop methods which allow prediction of the die wear and which are suited to be used in the design state in order to optimize the process. In this paper, wire drawing processes were simulated using the rigid-plastic finite element method and its results were used for predicting the die wear by Archard's wear model. The effects of the temperature rising on the wear profiles of die were also investigated. The simulation results were compared with the measured die profiles.

• Nuclear Engineering and Technology
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• v.31 no.4
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• pp.375-384
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• 1999

The credibility of CHECWORKS FAC model analysis was evaluated for plant application in a model plant chosen for demonstration. The operation condition at each pipe component was defined before the wear rate analysis by plant data base, water chemistry analysis, and network flow analysis. The predicted wear was compared with the measured wear for 57 sample components selected from 43 susceptible line groups analysed. The inspected 57 locations represent components of highest predicted wear in each line group. Both absolute value and relative ranking comparisons indicated reasonable correlations between the predicted and the measured values. Four components showed much higher measured wear rates than the predicted ones in the feed water train from main feed water pump discharge to steam generator, probably due to high hydrazine concentration operation the effect of which had not been incorporated into the CHECWORKS model. The measured wear was higher than the predicted one consistently for components with least susceptibility to FAC. It is believed that the conservatism maintained during UT data analysis dominated the measurement accuracy. A great deal of enhancement is anticipated over the current plant pipe management program when a comprehensive plant pipe management program is implemented based on the model analysis.

• Transactions of Materials Processing
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• v.33 no.2
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• pp.112-117
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• 2024

In this study, the friction and wear characteristics of Inconel 600 in the superplastic forming process of Ti6Al4V were evaluated through pin-on-disc tests. To achieve an efficient and systematic experimental design, the Taguchi method was employed. The wear track of the Inconel 600 pin showed scratches in the sliding contact direction, confirming that the wear mechanism is abrasive wear. Through sensitivity analysis such as ANOVA and Main effects, it was confirmed that both normal force and sliding distance have a significant impact on the wear. Changes in sliding velocity and distance did not affect the friction coefficient, which remained relatively constant at approximately 0.380. The wear prediction model for Inconel 600 in the superplastic forming of Ti6Al4V was constructed, which can be utilized as a guideline for the prediction and management of tool wear.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.1051-1055
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• 1997

Hot forging is widely used in the manufacturing of automotive component. The mechanical, thermal load and thermal softening which is happened by the high temperature die in hot forging. Tool life of hot forging decreases considerably due to the softening of the surface layer of a tool caused by a high thermal load and long contact time between the tool and workpieces. The service life of tools in hot forging process is to a large extent limited by wear, heat crack, plastic deformation. These are one of the main factors affecting die accuracy and tool life. It is desired to predict tool life by developing life prediction method by FE-simulation. Lots of researches have been done into the life prediction of cold forming die, and the results of those researches were trustworthy, but there have been little applications of hot forming die. That is because hot forming process has many factors influencing tool life, and there was not accurate in-process data. In this research, life prediction of hot forming die by wear analysis and plastic deformation has been carried out. To predict tool life, by experiment of tempering of die, tempering curve was obtained and hardness express a function of main tempering curve.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.63-73
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• 1995

A mechanistic force system model considering the flank wear for the face milling process has been developed. The model predicts variation of the cutting forces according to flank wear in face milling over a range of cutting conditions, cutter geometries and cutting process geometries including relative positions of cutter to workpiece and rounouts. Flycutting and multitoth cutting teste were conducted on SS41 mild steel with sintered carbide tool. In order to verify the mechanistic force model considering the flank wear of cutting tools, a series of experiments was performed with single and multitooth cutters in various cutting conditions. The results show good agreement between the predicted and measured cutting force profiles and magnitudes in time and frequency domains.