• 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.

• IE interfaces
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• v.7 no.3
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• pp.155-168
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• 1994

In computer integrated manufacturing environment, tool management plays an important role in controlling tool performance for machining operations. Knowledge of tool behavior during the cutting process and effective tool-behavior prediction contribute to controlling machine costs by avioding production delays and off-target parts due to tool failure. The purpose of this paper is to review and develop the tool condition monitoring scheme for drilling operation to assure a fast corrective response to minimize the damage if tool failures occur. If one desires to maximize system through-put and product quality as well as tooling resources, within an economic environment, real-time tool sensing system and information processing system can be coupled to provide the necessary information for the effective tool management. The example is demonstrated as to drilling operation when the aluminum composites are drilled with carbide-tipped HSS drill bits. The example above is limited to the situation that the tool failure mode of drill bits is wear.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.251-256
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• 1999

"Ploughing" on the flank face of the tool in the metal cutting process is due to the tool in the metal cutting process is due to the finite edge radius of the tool and due to the development of flank wear. Because of the high stresses near the cutting edge, elastic-plastic deformation would be caused between the tool and the machined surface over a small area of the tool flank. The deformation would affect the roughness of the machined surface. Recently, some attempts have been made to predict the surface roughness, but elastic-plastic effect due to ploughing in the cutting process has not been considered. The research has analyzed mechanism of the ploughing of the cutting process using contact mechanics. Tool and workpiece material properties have been taken into account in the prediction of the surface roughness. The surface roughness has been simulated by the surface-shaping system. The results between experiment and simulation have been compared and analyzed. analyzed.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.36-43
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• 1998

We experimented turning SCM440, called difficult-to-cut materials in general, using tungsten carbon tool(PIO) in order to elevate machinability by a new cutting method. The cutting tool designed and made to study was cooled to -17$0^{\circ}C$ in about 1 minute by liquid nitrogen. Then, we operated cryogenic cutting by cooling tool with liquid nitrogen and stuided the effect about cutting force, chip thickness, surface roughness, behavior of tool wear and cutting temperature. In addition, we investigated the possibility that sur face roughness of workpiece can be predicted analyzing cutting characteristics.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.4
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• pp.30-42
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• 1986

On the analysis of cutting mechanics in orthogonal cutting, each cutting force component can be predicted. By adding the flank face wear term to the prediction equation for cutting force components, complete equations are obtained. Using these equations, it is shown that cutting force components are increased linearly as flank face wear land is developed, in theory and experiment. By making non-dimensional term ie. Fv/Fc, the width of variation of output signal Fv/Fc is greately decreased compared with each cutting force component as cutting condition is varied. Among these conditions, the variation of chip width in the range of more than 1mm and that of cutting velocity have little effect on the output signal Fv/Fc, that of Flank face werr land can be detected without difficulty.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.05a
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• pp.70-73
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• 2004

The approach in this thesis is for prediction of deformed strip profile in hot rolling mill. This approach shows how to make an expression as a mathematical form in predicting strip profile. This approach is based on the velocity field, shear stress and material flow on the strip edge along width direction and lateral displacement and stress along width are analytically calculated. Roll force is calculated in each section and then combined together to show roll force distribution along width. All the assumptions to make equation form for this approach are supported by FEM simulation result and the result of model is verified by FEM result. So, this model will supply very useful tool to the researcher and engineers which takes less time and has similar accuracy in predicting roll force profile comparing to FEM simulation. This model has to be combined with deformed roll profile model, which include thermal crown prediction and wear prediction model to predict deformed strip profile.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.1
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• pp.7-14
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• 2004

Machining error is defined the normal distance between designed surface and actual tool path with tool deflection. This is inevitably caused by the tool deflection, tool wear, thermal effect and machine tool errors and so on. Among these factors, tool deflection is usually known as the most significant factor of machining error. Tool deflection problem is analyzed using Instantaneous horizontal cutting forces. The high quality and precision of machining products are required in finishing. In order to achieve these purposes, it is necessary work that decrease the machining error. This paper presents a study on the machining error caused by the tool deflection in ball end milling of 2 dimensional surface. Tool deflection model and simple machining error prediction model are described. This model is checked the validity with machining experiments of 2 dimensional surface. These results may be used to decrease machining error and tool path decision.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.114-123
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• 1998

In the end milling process, the information of the surface errors plays an important role in adaptive control systems for precision machining. As the measuring accuracy of the surface errors directly matches the control's, it is an important factor for evaluating the performance of the system. In order to obtain the surface errors, the prediction using the cutting force, torque, motor power etc. is frequently practiced owing to the easiness in measurement. In the implementation of the prediction, the information on the cutting depths make it concrete and precise. Actually the axial depth of cut limits the range of the calculation. In general, it is not easy to know the cutting depths due to irregular shape of workpieces, inaccurate positioning of them on the table of machine tool, and machining error in the previous cutting. In addition to, even if cutting depths are informed, it is difficult to match the individual position of the cutter on the varying shape of the work material. This work suggests an algorithm estimating the cutting depths based on cutting force and makes it precise to predict the surface error. The proposed algorithm can be applied in more extensive cutting situations, such as presence of the tool wear, change of the work material hardness, etc.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.553-581
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• 2022

Shortly after tunnel boring machine (TBM) was introduced in the tunneling industry, the use of TBM has surprisingly increased worldwide due to its performance together with the benefit of being safely and environmentally friendly. One of the main cost items in the TBM tunneling in rock and soil is changing damaged or worn cutters. It is because that the cutter change is a time-consuming and costly activity that can significantly reduce the TBM utilization and advance rate and has a major effect on the total time and cost of TBM tunneling projects. Therefore, the importance of accurately evaluating the cutter life can never be overemphasized. However, the prediction of cutter wear in soil, rock including mixed face is very complex and not yet fully clarified, subsequently keeping engineers busy around the world. Various prediction models for cutter wear have been developed and introduced, but these models almost usually produce highly variable results due to inherent uncertainties in the models. In this study, a case study of design and construction of disc cutter change is introduced and analyzed, rather than proposing a prediction model of cutter wear. As the disc cutter is strongly affected by the geological condition, TBM machine characteristic and operation, authors believe it is very hard to suggest a generalized prediction model given the uncertainties and limitations therefore it would be more practical to analyze a real case and provide a detailed discussion of the difference between prediction and result for the cutter change. By doing so, up-to-date idea about planning and execution of cutter change in practice can be promoted.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.6
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• pp.159-167
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• 2008

Cooling lubricants are used in machining operations in order to reduce friction at the tool-chip and tool-workpiece interfaces, cool both chip and tool, and remove chip. Furthermore, they influence a strong effect on the shearing mechanisms and, consequently, on the machined surface quality and tool wear. However, several researchers state that the costs related to cutting fluids is frequently higher than those related to cutting tools. Moreover, the cooling lubricants cause an increase in both worker's health and social problems related to their use and correct disposal. Therefore, many researchers have focused on the environmentally conscious machining technologies. One of the technologies is known as MQL(Minimum Quantity Lubrication) machining. In this paper, an experimental model to obtain the optimal cutting conditions in MQL turning was suggested, and the effects of cutting conditions on surface roughness and cutting force were analyzed. For these purposes, FFD (Fractional Factorial Design) and RSM (Response Surface Methods) were used for the experiment. Cutting force and surface roughness with different cutting conditions were measured through the external cylindrical turning of Al 6061 based on the experiment plan. The measured data were analyzed by regression analysis and verification experiments with random conditions were conducted to confirm the suggested experimental model.