Multi-scale simulation of the nano-metric cutting process

Molecular dynamics (MD) simulation and the finite element (FE) method are two popular numerical techniques for the simulation of machining processes. The two methods have their own strengths and limitations. MD simulation can cover the phenomena occurring at nano-metric scale but is limited by the computational cost and capacity, whilst the FE method is suitable for modelling meso- to macro-scale machining and for simulating macro-parameters, such as the temperature in a cutting zone, the stress/strain distribution and cutting forces, etc. With the successful application of multi-scale simulations in many research fields, the application of simulation to the machining processes is emerging, particularly in relation to machined surface generation and integrity formation, i.e. the machined surface roughness, residual stress, micro-hardness, microstructure and fatigue. Based on the quasi-continuum (QC) method, the multi-scale simulation of nano-metric cutting has been proposed. Cutting simulations are performed on single-crystal aluminium to investigate the chip formation, generation and propagation of the material dislocation during the cutting process. In addition, the effect of the tool rake angle on the cutting force and internal stress under the workpiece surface is investigated: The cutting force and internal stress in the workpiece material decrease with the increase of the rake angle. Finally, to ease multi-scale modelling and its simulation steps and to increase their speed, a computationally efficient MATLAB-based programme has been developed, which facilitates the geometrical modelling of cutting, the simulation conditions, the implementation of simulation and the analysis of results within a unified integrated virtual-simulation environment

Optimization of pocket machining strategy in HSM

Our two major concerns, which should be taken into consideration as soon as we start the selecting the machining parameters, are the minimization of the machining time and the maintaining of the high-speed machining machine in good state. The manufacturing strategy is one of the parameters which practically influences the time of the different geometrical forms manufacturing, as well as the machine itself. In this article, we propose an optimization methodology of the machining strategy for pockets of complex forms. For doing this, we have developed analytic models expressing the feed rate of the cutting tools trajectory. Then, we have elaborated an optimization method based on the analysis of the different critical parameters so as to distinguish the most suitable strategies to calculate the cutting time and define the machine dynamics. To validate our results, we have compared them to the experimental ones and also to those found in literature

Multi-agent framework based on smart sensors/actuators for machine tools control and monitoring

Throughout the history, the evolutions of the requirements for manufacturing equipments have depended on the changes in the customers' demands. Among the present trends in the requirements for new manufacturing equipments, there are more flexible and more reactive machines. In order to satisfy those requirements, this paper proposes a control and monitoring framework for machine tools based on smart sensor, on smart actuator and on agent concepts. The proposed control and monitoring framework achieves machine monitoring, process monitoring and adapting functions that are not usually provided by machine tool control systems. The proposed control and monitoring framework has been evaluated by the means of a simulated operative part of a machine tool. The communication between the agents is achieved thanks to an Ethernet network and CORBA protocol. The experiments (with and without cooperation between agents for accommodating) give encouraging results for implementing the proposed control framework to operational machines. Also, the cooperation between the agents of control and monitoring framework contributes to the improvement of reactivity by adapting cutting parameters to the machine and process states and to increase productivity

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

Automation of finite element aided design of induction motors using multi-slice 2D models

Purpose – To develop a practical design tool employing a general purpose electromagnetic finite element (FE) software package to perform automated simulation and performance analysis of induction motors in a design and optimisation process. Design/methodology/approach – Recent publications identified a suitable approach in applying 2D finite-element analysis to 3D problems. This, together with other similar work carried out on brushless DC motors, set out a framework for program development. Performance of the program was validated against practical test data. Findings – Finite-element analysis-based design tools can be realistically employed within a design office environment and are capable of providing solutions within acceptable time scales. Such tools no longer require user expertise in the underlying FE modelling method. The multiple slice technique was employed to model skew in three-phase induction motors and it was established that a four-slice model provides a good balance between accuracy and speed of computation. Research limitations/implications – Program development was based on one commercial FE software package and comparison with practical test data was not exhaustive. However, the approach outlined confirms the practical application. Future work could consider alternative approaches to optimisation. Practical implications – Computing hardware and commercially available 2D FE software have developed sufficiently to enable multi-slice techniques and optimisation to be employed in the analysis and design of machines. Originality/value – This paper provides a practical illustration of how commercial electromagnetic software can be employed as a design tool, demonstrating to industry that such tools no longer need to be bespoke and can realistically be used within a design office

SPH method applied to high speed cutting modelling

The purpose of this study is to introduce a new approach of high speed cutting numerical modelling. A Lagrangian smoothed particle hydrodynamics (SPH)- based model is arried out using the Ls-Dyna software. SPH is a meshless method, thus large material distortions that occur in the cutting problem are easily managed and SPH contact control permits a "natural" workpiece/chip separation. The developed approach is compared to machining dedicated code results and experimental data. The SPH cutting model has proved is ability to account for continuous to shear localized chip formation and also correctly estimates the cutting forces, as illustrated in some orthogonal cutting examples. Thus, comparable results to machining dedicated codes are obtained without introducing any adjusting numerical parameters (friction coefficient, fracture control parameter)

A methodology for the lightweight design of modern transfer machine tools

This paper deals with a modern design approach via finite elements in the definition of the main structural elements (rotary table and working unit) of an innovative family of transfer machine tools. Using the concepts of green design and manufacture, as well as sustainable development thinking, the paper highlights the advantages derived from their application in this specific field (i.e., the clever use of lightweight materials to allow ruling out high-consumption hydraulic pump systems). The design is conceived in a modular way, so that the final solution can cover transfers from four to 15 working stations. Two versions of the machines are examined. The first one has a rotary table with nine divisions, which can be considered as a prototype: this machine has been studied in order to set up the numerical predictive model, then validated by experimental tests. The second one, equipped with a rotary table with 15 divisions, is the biggest of the range: this machine has been entirely designed with the aid of the previously developed numerical model. The loading input forces for the analyses have been evaluated experimentally via drilling operations carried out on a three-axis CNC unit. The definition of the design force made it possible to accurately assess both the rotary table and the working units installed in the machine

On-the-fly adaptivity for nonlinear twoscale simulations using artificial neural networks and reduced order modeling

A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. It is based on the introduction of two different surrogate models and an adaptive on-the-fly switching. The two concurrent surrogates are built incrementally starting from a moderate set of evaluations of the full order model. Therefore, a reduced order model (ROM) is generated. Using a hybrid ROM-preconditioned FE solver, additional effective stress-strain data is simulated while the number of samples is kept to a moderate level by using a dedicated and physics-guided sampling technique. Machine learning (ML) is subsequently used to build the second surrogate by means of artificial neural networks (ANN). Different ANN architectures are explored and the features used as inputs of the ANN are fine tuned in order to improve the overall quality of the ML model. Additional ANN surrogates for the stress errors are generated. Therefore, conservative design guidelines for error surrogates are presented by adapting the loss functions of the ANN training in pure regression or pure classification settings. The error surrogates can be used as quality indicators in order to adaptively select the appropriate -- i.e. efficient yet accurate -- surrogate. Two strategies for the on-the-fly switching are investigated and a practicable and robust algorithm is proposed that eliminates relevant technical difficulties attributed to model switching. The provided algorithms and ANN design guidelines can easily be adopted for different problem settings and, thereby, they enable generalization of the used machine learning techniques for a wide range of applications. The resulting hybrid surrogate is employed in challenging multilevel FE simulations for a three-phase composite with pseudo-plastic micro-constituents. Numerical examples highlight the performance of the proposed approach