• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.8
• /
• pp.39-46
• /
• 2003

Productivity and machining performance can be improved by cutting analysis including cutting force prediction, surface error prediction and machining stability evaluation. In order to perform cutting analysis, cutting force coefficients database have to be constructed. Since cutting force coefficients are dependent on cutting condition in the existing research, a large number of calibration tests are needed to obtain cutting force coefficients, which makes it difficult to build the cutting force coefficients database. This paper proposes a generalized method for constructing the cutting force coefficients database us ins cutting-condition-independent coefficients. The tool geometry and workpiece material were considered as important components for database construction. Cutting force coefficients were calculated and analyzed for various helix and rake angles as well as for several workpiece. Furthermore, the variation of cutting force coefficients according to tool wear was analyzed. Tool wear was found to affect tool geometry, which results in the change of cutting force coefficients.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.10
• /
• pp.31-40
• /
• 2003

In this paper, optimal cutting condition to minimize the form error in side wall machining with a flat end mill is studied. Cutting forces and tool deflection are calculated considering surface shape generated by the previous cutting such as roughing. Using the form error prediction method from tool deflection, optimal cutting condition considering form accuracy is investigated. Also, the effects of tool teeth number, tool geometry and cutting conditions on form error are analyzed. The characteristics and the difference of generated surface shape in up and down milling are discussed and over-cut free condition in up milling is presented. Form error reduction method through successive up and down milling is also suggested. The effectiveness and usefulness of the presented method are verified from a series of cutting experiments under various cutting conditions. It is confirmed that form error prediction from tool deflection in side wall machining can be used in optimal cutting condition selection and real time surface error simulation for CAD/CAM systems. This study also contributes to cutting process optimization for the improvement of form accuracy especially in precision die and mold manufacturing.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1784-1788
• /
• 2003

For the improvement of geometrical accuracy in end milling, cutting method and cutting condition selection are investigated in this paper. As machining processes are composed of several steps such as roughing, semi-finishing. and finishing, cutting forces and tool deflection are calculated considering surface shape generated by the previous cutting. The effects of tool teeth numbers, tool geometry, and cutting conditions on the form error are analyzed. Using the from error prediction method from tool deflection, cutting condition for geometrical accuracy improvement is discussed. The characteristics and the difference of generated surface shape in up and down milling are dealt with and over-cut free condition in up milling is presented. The form error reduction method by alternating up and down milling is also suggested. The effectiveness of the presented method is examined from a set of cutting tests under various cutting conditions. This research contributes to cutting process optimization for the geometrical accuracy improvement in die and mold manufacture.

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

• Smart Structures and Systems
• /
• v.21 no.3
• /
• pp.305-320
• /
• 2018

The second half of the 20th century was marked with a significant raise in amount of railway bridges in Austria made of reinforced concrete. Today, many of these bridges are slowly approaching the end of their envisaged service life. Current methodology of assessment and evaluation of structural condition is based on visual inspections, which, due to its subjectivity, can lead to delayed interventions, irreparable damages and additional costs. Thus, to support engineers in the process of structural evaluation and prediction of the remaining service life, the Austrian Federal Railways (${\ddot{O}}$ BB) commissioned the formation of a concept for an anticipatory life cycle management of engineering structures. The part concerning concrete bridges consisted of forming a bridge management system (BMS) in a form of a web-based analysis tool, known as the LeCIE_tool. Contrary to most BMSs, where prediction of a condition is based on Markovian models, in the LeCIE_tool, the time-dependent deterioration mechanisms of chloride- and carbonation-induced corrosion are used as the most common deterioration processes in transportation infrastructure. Hence, the main aim of this article is to describe the background of the introduced tool, with a discussion on exposure classes and crucial parameters of chloride ingress and carbonation models. Moreover, the article presents a verification of the generated analysis tool through service life prediction on a dozen of bridges of the Austrian railway network, as well as a case study with a more detailed description and implementation of the concept applied.

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

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.10a
• /
• pp.104-110
• /
• 2002

In this study, the prediction on the quality of tools after coating process has been investigated. Under different coating conditions, cutting resistances have been obtained and analyzed with a tool dynamometer to provide optimized coating conditions. The optimized coating condition has been computed with the most effective factors found by S/N ratio of Taguchi method. To evaluate the influence of the factors on cutting efficiency through the minimum of number of experiment times, the way of neural network design using Taguchi method has been employed.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.7 s.178
• /
• pp.1681-1688
• /
• 2000

A dynamic model for the prediction of surface topography in high speed end milling process is developed. In this model the effect of tool runout, tool deflection and spindle vibration were taken in to account. An equivalent diameter of end mill is obtained by finite element method and tool deflection experiment. A modal parameter of machine tool is extracted by using frequency response function. The tool deflection, spindle vibration chip thickness and cutting force were calculated in dynamic cutting condition. The tooth pass is calculated at the current angular position for each point of contact between the tool and the workpiece. The new dynamic model for surface predition are compared with several investigated model. It is shown that new dynamic model is more effective to predict surface topography than other suggested models. In high speed end milling, the tool vibration has more effect on surface topography than the tool deflection.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.9
• /
• pp.111-117
• /
• 2002

In most machining companies, operators decide the cutting condition, a pair of spindle speed (5) and table federate (F) by experience and subjective judgment. As cutting conditions are determined by operators' experience and ability, inconsistent cutting conditions are given in same operating conditions. The objective of this study is to develop the cutting condition decision system which utilizes shop data and predicts tool life by neural network and eventually leads to the optimal cutting condition. The production time per piece is considered for an optimization object. We will discuss the process of an optimal cutting condition decision by neural network. By this process, a series of shop data is stored. And neural network is constructed for prediction of tool life and the optimal cutting condition is recommended from a cutting condition decision system using the stored shop data. The results show that the developed system is rational in searching the optimal cutting conditions on job operations.

• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.9 s.186
• /
• pp.76-83
• /
• 2006

Machining accuracy is closely related with tool deflection induced by cutting forces. In this research, cutting forces and tool deflection in end milling are expressed as a closed form of tool rotational angle and cutting conditions. The discrete cutting fores caused by periodic tool entry and exit are represented as a continuous function using the Fourier series expansion. Tool deflection is predicted by direct integration of the distributed loads on cutting edges. Cutting conditions, tool geometry, run-outs and the stiffness of tool clamping part are considered together far cutting forces and tool deflection estimation. Compared with numerical methods, the presented method has advantages in prediction time reduction and the effects of feeding and run-outs on cutting forces and tool deflection can be analyzed quantitatively. This research can be effectively used in real time machining error estimation and cutting condition selection for error minimization since the form accuracy is easily predicted from tool deflection curve.