Tool Shape Parameters Research Articles

Aiding of Micro End-Milling Condition Decision Using Data-Mining from Tool Catalog Data

When the minor diameter of an end-mill is 1.0 mm or less, handling of tools becomes difficult because of the influence of the characteristic size effect and bending of the cutting edge. Furthermore, it is hard for engineers to derive the cutting conditions that can serve as indexes in the early stage of micro end-milling. In this study, a system that can make instantaneous decisions was developed, on the basis of workpiece material-characteristics and tool shape parameters, by applying data mining techniques together with non-hierarchical and hierarchical clustering methods on micro end-mill catalog data. Slotting experiments using cemented carbide square micro end-mill were carried out to investigate the practicability of derived mining conditions under slotting of A7075 (JIS). We found that catalog mining can be used to derive the guidelines for deciding the micro end-milling conditions.

티타늄 합금의 밀링가공에서 평 엔드밀의 헬릭스각과 경사각의 영향 분석

Article history: In this study, the effect of the helix angle and rake angle of a flat end-mill in the milling of titanium alloy was investigated. Tool shape parameters such as helix angle and rake angle affect the cutting force, cutting zone temperature, vibration, and chip flow mechanism, which in turn determine tool life, surface integrity, and dimensional accuracy of the milling process. To investigate the effect of the helix and rake angles, a certain range of parameters was selected, and three-dimensional tool models were generated for finite element analysis (FEA) for each case. The cutting force and pressure on the tool flank face and rake face were investigated by FEA. Further, several tool models were proposed for machining tests. The cutting force characteristics were investigated by the machining tests.

Investigation of Drilling Conditions of Printed Circuit Board Based on Data Mining Method from Tool Catalog Data-Base

Data-mining methods using hierarchical and non-hierarchical clustering are proposed that will help engineers determine appropriate drilling conditions. We have constructed a system that uses clustering techniques and tool catalog data to support the determination of drilling conditions for printed wiring boards (PWBs). Variable cluster analysis and the K-means method were used together to identify tool shape parameters that have a linear relationship with the drilling conditions listed in the catalogs. The response surface method and significant tool shape parameters obtained by clustering were used to derive drilling condition decision equations, which were used to determine the indicative drilling conditions for PWBs. Comparison of the conditions recommended by toolmakers demonstrated that our proposed system can be used to determine the drilling condition for PWBs. We carried out the drilling experiments in accordance with the catalog conditions and mining conditions, and estimated the board temperature around a drilled hole, the drilling forces, and the roughness of the drilled hole wall.

An Indicative End-Milling Condition Decision Support System Using Data-Mining for Difficult-to-Cut Materials Based on Comparison with Irregular Pitch and Lead End-Mill and General Purpose End-Mill

Data-mining methods using hierarchical and non-hierarchical clustering are proposed that will help engineers determine appropriate end-milling conditions. We have constructed a system that uses clustering techniques and tool catalog data to support the determination of end-milling conditions for different types of difficult-to-cut materials such as austenitic stainless steel, Ni-base superalloy, and titanium alloy. Variable cluster analysis and the K-means method were used together to identify tool shape parameters that have a linear relationship with the end-milling conditions listed in the catalogs. The response surface method and significant tool shape parameters obtained by clustering were used to derive end-milling condition decision equations, which were used to determine the indicative end-milling conditions for each material. Comparison with the conditions recommended by toolmakers demonstrated that our proposed system can be used to determine the cutting speeds for various difficult-to-cut materials.

An End-Milling Condition Decision Support System Using Data-Mining for Difficult-to-Cut Materials

We proposed the data-mining methods using hierarchical and non-hierarchical clustering methods to help engineers decide appropriate end-milling conditions. The aim of our research is to construct a system that uses clustering techniques and tool catalog data to support the decision of end-milling conditions for difficult-to-cut materials. We used variable cluster analysis and the K-means method to find tool shape parameters that had a linear relationship with the end-milling conditions listed in the catalog. We used the response surface method and significant tool shape parameters obtained by clustering to derive end-milling condition. Milling experiments using a square end mill under two sets of end-milling conditions (conditions derived from the end-milling condition decision support system and conditions suggested by expert engineers) for difficult-to-cut materials (austenite stainless steel) showed that catalog mining can be used to derive guidelines for deciding end-milling conditions.

高速ミーリング用ボールエンドミルの創成とその切削特性−ソリッドボールエンドミルの刃先ランド処理による工具寿命向上と加工安定化−

High speed milling has been realized owing to a number of component technologies. The advancement of these technologies plays a pivotal role in practical application of high speed milling. Cutting tool is one of the most important component technologies among them. Especially, ball end mills, which are the central tools for die and mould machining, have wide usage. Therefore, ball end mills with long tool life and high machining performance are strongly demanded. However, the relationship between tool shapes of ball end mill and high speed milling has not been made clear since it is hard to analyze some complex tool shape parameters. The study focuses on the cutting edge shapes of ball end mills, and allows the creation of micro-lands on rake face and flank face in order to make tool lives longer and keep machining more stable. They are named Neg-land (land between cutting edge and rake face) and Pos-land (land between cutting edge and flank face). High speed cutting experiments enable us to recognize some specific cutting characteristics of created ball end mills. Based on the obtained characteristics, ball end mills with an original cutting edge shape (Opt-tool) are again proposed and produced. As a result, it is experimentally found that the Opt-tool shows the longest tool life and the highest machining performance in high speed milling.

Sensitivity based optimization of sheet metal forming tools

The shape of the first of two contacting bodies is optimized on the basis of sensitivities calculated for the second body, i.e. workpiece. The finite element simulation of sheet metal forming process and direct differentiation method of sensitivity analysis are used. Some energy measures of deforming sheet metal treated as a cost functional and its gradients with respect to the tool (punch) shape parameters is evaluated. Tool shape optimization based on “exact” sensitivity results is performed. Calculated sensitivities with respect to the tool shape parameters are the input for each iteration of the optimization algorithm (treated here as a “black box”) from which new values of the design variables are obtained until the cost functional is minimized, yielding the optimal shape for the considered functional. As an example the axisymmetrical part of the compressor cover produced in one of sheet stamping factories is considered. It was impossible to produce it without shape modifications. Energy consumption measure is minimized here but other objective functions can easily be included in the algorithm.