Prediction of tool tip dynamics for generalized milling cutters using the 3D model of the tool body

In general, chatter is the main limitation to proper material removal in milling operations. Stability lobes are good tools to determine chatter-free cutting conditions in terms of spindle speed and cutting depth, which require the frequency response function (FRF) at the tool tip to be known. There are experimental methods to measure the tool tip FRF but this may be time consuming or even impossible for each tool and tool holder combination. Receptance coupling substructure analysis (RCSA) is a widely used approach to predict tool tip dynamics. This paper proposes the use of the RCSA approach with a stereolithographic (STL) slicing algorithm to enable the exact calculation of cross sectional properties such as area and area moment of inertia of the cutting tool from its 3D model opposed to the approximation methods. So that, the effect of flutes on cutting tool structure introduced in an exact manner and the RCSA approach becomes feasible for more complicated tool geometries with varying cross-sectional properties, i.e., tapered ball end mills, end mills with variable flute geometries, and so on. The solid model of the tool can be available by either the tool manufacturer or 3D measurement. Although, at the presence of 3D models, finite element methods (FEM) offer accurate simulation of the dynamic response for solid bodies, they suffer from the compromise between accuracy and computation time, as high number of elements is needed for accuracy. Thus, the use of analytical methods where possible improves the simulation time significantly. The proposed STL slicing algorithm is integrated with a previously developed RCSA method. The experimental results show that the proposed algorithm works more accurate in calculation of the cross-sectional properties and hence free-free response of the tool compared to the existing arc approximation methods. It is also shown that the proposed approach performs better than FEM solutions in terms of the computation time and the compromise between accuracy and computation performance. Finally, the proposed approach in prediction of tool tip dynamics for a robotic machining platform

Effect of cutting conditions and tool geometry on process damping in machining

Process damping can be a significant source of enhanced stability in metal cutting operations especially at low cutting speeds. However, it is usually ignored in stability analysis since models and methods on prediction and identification of process damping are very limited. In this study, the effects of cutting conditions and tool geometry on process stability in turning and milling are investigated. The previously developed models by the authors are used in simulations to demonstrate conditions for increased process damping, and thus chatter stability. Some representative cases are presented and verified by experimental data and conclusions are derived

Use of inverse stability solutions for identification of uncertainties in the dynamics of machining processes

Research on dynamics and stability of machining operations has attracted considerable attention. Currently, most studies focus on the forward solution of dynamics and stability in which material properties and the frequency response function at the tool tip are known to predict stable cutting conditions. However, the forward solution may fail to perform accurately in cases wherein the aforementioned information is partially known or varies based on the process conditions, or could involve several uncertainties in the dynamics. Under these circumstances, inverse stability solutions are immensely useful to identify the amount of variation in the effective damping or stiffness acting on the machining system. In this paper, the inverse stability solutions and their use for such purposes are discussed through relevant examples and case studies. Specific areas include identification of process damping at low cutting speeds and variations in spindle dynamics at high rotational speeds

Effect of MQL conditions on tool life in milling of AISI 316L stainless steel

In large-scale part manufacturing industries such as nuclear, aerospace and power generation, robotic milling is potentially a promising portable manufacturing technology to decrease the overall costs. The lack of enclosures around the robotic milling units blocks the use of flood coolant contrary to CNC machining centres. In such cases, the minimal quantity lubrication (MQL) technique is suitable, which on the other hand, agrees with the green manufacturing theme of the industry in the 21st century. However, the effect of MQL parameters such as the air pressure, oil flow rate, oil type, and pulse rate on tool life and surface integrity in end milling have not been well studied and understood yet. In this paper, the MQL technology is studied to understand its effects on tool life and surface integrity in end milling of nuclear manufacturing grade stainless steels such as AISI316L. The milling experiments are performed using a robotic milling cell. The tool life is assessed by measuring the wear land using optical microscopy techniques, whereas the surface integrity is assessed in terms of surface residual stress (XRD) and surface roughness (optical metallography). The results show that MQL conditions and the oil type significantly affects the tool wear, tool life and surface integrity. Improve surface roughness was observed at 15 strokes/min at 75 ml/h of fluid flow rate. It was observed that high stroke rate with increased oil flow leads to decrease in the surface residual stress. It was found that use of synthetic MQL oils do not help to increase tool life compared to dry cutting. When water-based synthetic oils were used, the stable wear progress duration was found to be very short

Rapid extraction of machined surface data through inverse geometrical solution of tool path information

In the last decades, several process models have been developed for simulation of 5-axis milling cycles, where the simulation results are used for parameter selection or process improvement purposes. However, integrating the process models with milling cycles is not a trivial task especially for tool path modification purposes in 5-axis free-form milling. This is mainly due to the fact that tool path modification requires the machined surface information, i.e. surface location and surface normal vector, to be known. However, this information is not explicitly given in the tool path, i.e. cutter location source (CLS), file. In this paper, a novel and practical approach is proposed to analytically calculate the surface location and surface normal vectors directly from the already generated tool path in the form of CLS file. The proposed approach is applied on representative 5-axis milling cycles, and the results are verified through CAD model comparisons. It is shown that the proposed approach can calculate the machined surface data at a reasonable accuracy depending on the cutter location point density in the tool path file

Tool axis optimization for robotic 5-axis milling considering kinematics

Robotic milling is proposed to be one of the alternatives to respond the demand for reconfigurable and cost-effective manufacturing systems. Serial arm robots are mostly use for robotic milling purposes offering 6 degrees of freedom (DOF) motion capability. In 5-axis milling, the tool axis selection is still a challenge, where only geometrical issues are considered at the computer-aided-manufacturing (CAM) packages. In this study, an approach is proposed to select the tool axis for robotic milling along an already generated 5-axis milling tool path, where the robot kinematics are considered to eliminate or decrease excessive axis rotations. The proposed approach is demonstrated through simulations and benefits are discussed

Selection of cutting strategy and parameters in multi-axis machining operations for improved productivity

Importance and application of multi-axis machining operations has been continuing to increase in several industries such as aerospace, automotive, die and mold, where parts with complex surfaces. In such industries achieving tight tolerances is required with minimum number of setups, as well. Two and half, three and five axis milling can be considered in such a class together with parallel machining operations. The cutting tool has simultaneous translation in two axes, and the third axis is used to change the axial level. In three axis milling the cutting tool is able to have simultaneous translation in –x, –y and –z axis of Cartesian coordinates. However, in five axis milling, tool orientation changes with respect to the machined surface due to the rotary axes in addition to the linear motions in x, y, and z directions. Parallel machining, which can also be considered as a multi-axis process, consists of simultaneous machining operations on a given part. For instance, while the outer diameter of a part is machined, a drilling operation can be conducted in parallel. Increasing the productivity and part quality in such operations is important due to the high cost of machine tools, equipment and raw material involved. For this purpose, the right machining strategy and appropriate set of process parameters should be selected for a given part. Moreover, proper scheduling of parallel machining operations is also of great importance for decreased machining time on a part. This objective can be achieved using of process simulations based on process modeling. It is practically known that as the cutting speed is decreased, process stability increases with the effect of process damping. Considering this fact, high productivity conditions can be achieved by selecting low cutting speeds and high cutting depths, besides the high speed cutting conditions. Although there are several models for estimation of process stability at high cutting speeds, there has not been a practical method for estimation of stability limit considering the process damping effect for low cutting speed conditions. Therefore, current models fail to accurately estimate the stability limits, especially at low cutting speeds. In this thesis, a new and practical method is proposed for modeling of process stability at low cutting speeds. The model predictions are also verified through experiments. Thus, it is one of the major contributions of this thesis to the machining research. In this thesis, selection of cutting strategies and parameters is studied for multi axis milling and turning operations through process modeling. Process stability, spindle torque and power, quality requirements on the workpiece, form errors and tool life are considered as the constraints. The proposed model for estimation of process damping and stability limits at low cutting speed is used together with the previously developed process models. By doing so, different cutting strategies are compared for industrial parts. Considering that there is not much study dealing with such a problem, it can be said that this thesis contributes to literature in this respect. Parallel machining operations, where more than one machining units are allowed to work on the part provide several advantages, while bringing additional challenges. By the help of parallel machining physical space can be saved, tolerance integrity can be achieved easier, total machining time can be decreased and flexibility in process scheduling can be achieved. The literature on scheduling of parallel machining operations is relatively scarce. Moreover, current studies do not consider the dynamic and mechanic interaction between the processes conducted in parallel. In this thesis, such interactions are also considered in scheduling of parallel machining operations. The applicability of the method and models proposed in the thesis is shown on industrial workpiece geometries and the improvements are also presented together with the results