Machining strategy development in 5-axis milling operations using process models

Increased productivity and part quality can be achieved by selecting machining strategies and conditions properly. At one extreme very high speed and feed rate with small depth of cut can be used for high productivity whereas deep cuts accompanied with slow speeds and feeds may also provide increased material removal rates in some cases. In this study, it is shown that process models are useful tools to simulate and compare alternative strategies for machining of a part. 5-axis milling of turbine engine compressors made out of titanium alloys is used as the case study where strategies such as flank milling (deep cuts), point milling (light cuts) and stripe milling (medium depths) are compared in terms of process time by considering chatter stability, surface finish and tool deflections

Optimum selection of variable pitch for chatter suppression in face milling operations

Cutting capacity can be seriously limited in heavy duty face milling processes due to self-excited structural vibrations. Special geometry tools and, specifically, variable pitch milling tools have been extensively used in aeronautic applications with the purpose of removing these detrimental chatter vibrations, where high frequency chatter related to slender tools or thin walls limits productivity. However, the application of this technique in heavy duty face milling operations has not been thoroughly explored. In this paper, a method for the definition of the optimum angles between inserts is presented, based on the optimum pitch angle and the stabilizability diagrams. These diagrams are obtained through the brute force (BF) iterative method, which basically consists of an iterative maximization of the stability by using the semidiscretization method. From the observed results, hints for the selection of the optimum pitch pattern and the optimum values of the angles between inserts are presented. A practical application is implemented and the cutting performance when using an optimized variable pitch tool is assessed. It is concluded that with an optimum selection of the pitch, the material removal rate can be improved up to three times. Finally, the existence of two more different stability lobe families related to the saddle-node and flip type stability losses is demonstrated

Multi-criteria optimization in end milling of AISI D2 hardened steel using coated carbide inserts

This paper proposes a multi-criteria optimization technique using the mathematical models developed by the response surface methodology (RSM) for the target responses combined with desirability indices for the determining the optimum cutting parameters in end milling of AISI D2 hardened steels. Different responses may require different targets either being maximized or minimized. Simultaneous achievement of the optimized (maximum or minimum) values of all the responses is very unlikely. In machining operations tool life and volume metal removed are targeted to be maximized whereas the machined surface roughness need to be at minimum level. Models showing the combined effect of the three control factors such as cutting speed, feed, and depth of cut are developed. However, a particular combination of parameter levels appears to be optimum for a particular response but not for all. Thus adoption of the method of consecutive searches with higher desirability values is found to be appropriate. In this study the desirability index reaches to a maximum value of 0.889 after five consecutive solution searching. At this stage, the optimum values of machining parameters - cutting speed, depth of cut and feed were determined as 44.27 m/min, 0.61 mm, 0.065 mm/tooth respectively. Under this set condition of machining operations a surface roughness of 0.348 μm and volume material removal of 7.45 cm3 were the best results compared to the rest four set conditions. However, the tool life would be required to compromise slightly from the optimum value

Simulation of broaching operations for tool design optimization

In this study, an approach for simulation of broaching operations is presented. The proposed approach calculates the cutting forces, power, maximum stress at the tooth root, chip thickness and rake angle distribution on all teeth, and the workpiece geometry evolution during the process. The developed algorithms are integrated in a computer software that can simulate a whole broaching process to predict various physical parameters and generate some performance measures. The model which is used to optimize the broaching process is briefly presented here together with the industrial applications

A novel haptic model and environment for maxillofacial surgical operation planning and manipulation

This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is important to have all the operation related information of the patient available beforehand in order to plan the operation and avoid any complications. A haptic interface with a virtual and accurate patient model to support the planning of bone cuts is therefore critical, useful and necessary for the surgeons. The system proposed uses DICOM images taken from a digital tomography scanner and creates a mesh model of the filtered skull, from which the jaw bone can be isolated for further use. A novel solution for cutting the bones has been developed and it uses the haptic tool to determine and define the bone-cutting plane in the bone, and this new approach creates three new meshes of the original model. Using this approach the computational power is optimized and a real time feedback can be achieved during all bone manipulations. During the movement of the mesh cutting, a novel friction profile is predefined in the haptical system to simulate the force feedback feel of different densities in the bone

Optimization and analysis of surface roughness, flank wear and 5 different sensorial data via Tool Condition Monitoring System in turning of AISI 5140

Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L9 orthogonal design principle, the basic machining parameters cutting speed (vc), feed rate (f) and depth of cut (ap) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, VB, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at vc = 150 m/min, f = 0.09 mm/rev, ap = 1 mm) to obtain the best results for VB, Ra and the sensorial data, with a high success rate (82.5%)

A Survey of Automated Process Planning Approaches in Machining

Global industrial trend is shifting towards next industrial revolution Industry 4.0. It is becoming increasingly important for modern manufacturing industries to develop a Computer Integrated Manufacturing (CIM) system by integrating the various operational and information processing functions in design and manufacturing. In spite of being active in research for almost four decades, it is clear that new functionalities are needed to integrate and realize a completely optimal process planning which can be fully compliant towards Smart Factory. In order to develop a CIM system, Computer Aided Process Planning (CAPP) plays a key role and therefore it has been the focus of many researchers. In order to gain insight into the current state-of-the-art of CAPP methodologies, 96 research papers have been reviewed. Subsequent sections discuss the different CAPP approaches adopted by researchers to automate different process planning tasks. This paper aims at addressing the key approaches involved and future directions towards Smart Manufacturing