scholarly journals A 6-Components Mechanistic Model of Cutting Actions in Milling

2021 ◽  
Author(s):  
Maël Jeulin ◽  
Olivier Cahuc ◽  
Philippe Darnis ◽  
Raynald Laheurte
Keyword(s):  
Energy Balance ◽  
Experimental Model ◽  
Cutting Forces ◽  
Mechanistic Model ◽  
Cutting Parameters ◽  
Point Of View ◽  
Stress Fields ◽  
Mechanistic Modelling ◽  
Cutting Zone ◽  
Energetic Point

Abstract Most of the cutting models developed in the literature attest only to the presence of cutting forces in the balance of mechanical actions resulting from cutting. However, several studies have highlighted the presence of cutting moments during machining, and particularly 3D cutting in milling. The objective of this paper is to characterise phenomena associated with cutting moments by performing experimental mechanistic modelling in 3D cutting. For this purpose, several modelling factors will be investigated, such as the 3D cutting reference frame, the undeformed chip section, the cutting parameters, the cutting zone, etc. The predictive model of this study proves to be relatively efficient for an experimental model and allows a global prediction of cutting moments in milling. Furthermore, beyond the aspect of stress fields in the workpiece caused by cutting moments, this paper gives perspectives from an energetic point of view for which the share of moments in the energy balance could be substantial for monobloc tools.

Research on the Machining Behaviors in High Speed Milling Cellular Aluminium Alloy

2012 ◽  
Vol 472-475 ◽  
pp. 1087-1090
Author(s):  
Fa Zhan Yang ◽  
Xin Zhuang ◽  
Wan Hua Zhao ◽  
Yong Yang
Keyword(s):  
Aluminium Alloy ◽  
Cutting Forces ◽  
High Speed ◽  
Cutting Parameters ◽  
Point Of View ◽  
Element Analysis ◽  
Measuring Device ◽  
Tool Wear Mechanisms ◽  
Experimental Cutting ◽  
Cemented Carbide Tools

The purpose of this investigation is to examine the machining behavior of cemented carbide tools in dry hard milling of cellular aluminium alloy (6N01) by experiments and finite-element analysis. From the machining point of view, Cellular aluminium alloy are often considered as poor machinability materials. Milling tests were carried out by using a three-head milling machine and a milling force measuring device. For this purpose, both microscopic and microstructural aspects of the tools were taken into consideration. Meanwhile, the cutting forces and the noise intensity are also considered in the experiment. Results show that cutting forces vary greatly with the experimental cutting parameters. Additionally, the noise field intensity increased greatly as the feed rate increased. Analysis indicated that the major tool wear mechanisms observed in the machining tests involve adhesive wear and abrasion wear.

Cutting Process Simulation in Micro Dimple Machining

2019 ◽  
Author(s):  
Takashi Matsumura ◽  
Yuji Musha
Keyword(s):  
Cutting Forces ◽  
Rotation Axis ◽  
Flow Direction ◽  
Mechanistic Model ◽  
Cutting Parameters ◽  
Process Models ◽  
Cutting Process ◽  
High Rate ◽  
Force Model ◽  
Micro Dimple

Abstract The paper discusses micro dimple millings with inclined ball end mills. Cutting process models are presented to control the dimple shapes and predict the cutting forces. In micro dimple milling, the cutter rotation axis is inclined to have the non-cutting time, during which the cutting edges don’t remove the material in a rotation of cutter. The end mill is fed at a high rate so that the machining areas removed by the cutting edges are not overlapped each other. The shapes and the alignment of the dimples are simulated for the cutting parameters in the mechanistic model. Then, the cutting forces are predicted for high machining accuracies. The cutting experiments were conducted to verify the micro dimple machining. The dimple shape model is validated in comparison between the simulated and the actual dimple shapes. The cutting forces are simulated to compare the measured ones. The force model works well to predict the cutting forces with the chip flow direction during a rotation of the cutter.

Uncertainty Management of Cutting Forces Parameters and its Effects on Machining Stability

2015 ◽  
Vol 651-653 ◽  
pp. 1165-1170 ◽  
Author(s):  
Edouard Rivière Lorphèvre ◽  
Christophe Letot ◽  
François Ducobu ◽  
Enrico Filippi
Keyword(s):  
Cutting Forces ◽  
Mechanistic Model ◽  
Model Identification ◽  
Cutting Parameters ◽  
Virtual Manufacturing ◽  
Production Costs ◽  
Machining Process ◽  
Macroscopic Models ◽  
Force Signal ◽  
Machining Operations

Virtual manufacturing is a field of research which numerically simulate all the manufacturing processes seen by a mechanical part during its production (for example casting, forging, machining, heat treatment,…). Its use is rising on various industries to reduce production costs and improve quality of manufactured parts. One of the most challenging component of the whole simulation chain is the simulation of machining operations due to some of its specificities (need of material law at high strain, strain rates and temperature, heterogeneities of machined material, influence of residual stresses,…).In order to circumvent these difficulties, macroscopic models of machining process have been developed in order to compute more global information (cutting forces, stability of the process, tolerance or roughness for example). For this approach, the cutting forces computation is done by using simple analytical law based on mechanistic approach. The parameters of the models have no clear physical meaning (or at least cannot be linked to intrinsic properties of the material to be machined) and are therefore considered constants for a given set of simulations.The aim of this paper is to take into account the uncertainty on the variability of the cutting force signal during machining operation used as input for mechanistic model identification. The variability of the response during a test on fixed conditions (cutting tool, machined material and cutting parameters) is taken into account to develop a model where parameters of the model can evolve during a given operation.The proposed model is then used as an input of a milling operation simulation in order to study its influence on machining stability as compared to a classical approach.

scholarly journals Energetic analysis of landrace varieties and hybrids of corn produced in different technological levels of management

2013 ◽  
Vol 33 (4) ◽  
pp. 625-635 ◽  
Author(s):  
Alisson V. de Araujo ◽  
Delacyr da S. Brandão Junior ◽  
Fernando Colen
Keyword(s):  
Energy Efficiency ◽  
Energy Balance ◽  
Point Of View ◽  
High Tech ◽  
Family Farming ◽  
Technological Level ◽  
Energetic Analysis ◽  
Energetic Point ◽  
Social Importance ◽  
Hybrid Cultivar

The aim of this study was to analyze, under the energetic point of view, the cultivation of corn in three management systems (low, medium and high-tech), using two landrace varieties ('Argentino' and 'BR da Várzea'), a double hybrid cultivar (SHS 4080) and a simple hybrid (IAC 8333). Five performance indicators were used: energy efficiency, liquid cultural energy, cultural efficiency, energy balance and productive energy efficiency. From the perspective of family farming, it was verified the largest social importance of the systems under low and medium levels of technology, due to the increase employment capacity of rural labor. The liquid cultural energy and energy balance were more favorable for the system under high technological level, unlike cultural efficiency and productive energy efficiency, which were significantly higher for medium and low technological levels. The variety 'Argentino' showed lower productive energy efficiency. The variety 'BR da Várzea', on the other hand, presented the potential to generate energy as much as the hybrids. In general, the biggest sustainability in the corn crop was achieved when the management system under medium and lower levels of technology were used.

scholarly journals Temperature monitoring in the subsurface during single lip deep hole drilling

2020 ◽  
Vol 87 (12) ◽  
pp. 757-767
Author(s):  
Robert Wegert ◽  
Vinzenz Guski ◽  
Hans-Christian Möhring ◽  
Siegfried Schmauder
Keyword(s):  
Cutting Parameters ◽  
Drill Hole ◽  
Machining Process ◽  
Hole Drilling ◽  
Drilling Process ◽  
Deep Hole ◽  
Machining Processes ◽  
Deep Hole Drilling ◽  
Feed Force ◽  
Cutting Zone

AbstractThe surface quality and the subsurface properties such as hardness, residual stresses and grain size of a drill hole are dependent on the cutting parameters of the single lip deep hole drilling process and therefore on the thermomechanical as-is state in the cutting zone and in the contact zone between the guide pads and the drill hole surface. In this contribution, the main objectives are the in-process measurement of the thermal as-is state in the subsurface of a drilling hole by means of thermocouples as well as the feed force and drilling torque evaluation. FE simulation results to verify the investigations and to predict the thermomechanical conditions in the cutting zone are presented as well. The work is part of an interdisciplinary research project in the framework of the priority program “Surface Conditioning in Machining Processes” (SPP 2086) of the German Research Foundation (DFG).This contribution provides an overview of the effects of cutting parameters, cooling lubrication and including wear on the thermal conditions in the subsurface and mechanical loads during this machining process. At first, a test set up for the in-process temperature measurement will be presented with the execution as well as the analysis of the resulting temperature, feed force and drilling torque during drilling a 42CrMo4 steel. Furthermore, the results of process simulations and the validation of this applied FE approach with measured quantities are presented.

scholarly journals From Black Box to Machine Learning: A Journey through Membrane Process Modelling

Membranes ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 574
Author(s):  
Claudia F. Galinha ◽  
João G. Crespo
Keyword(s):  
Machine Learning ◽  
Process Modelling ◽  
Model Membrane ◽  
Point Of View ◽  
Personal Perspective ◽  
Process Conditions ◽  
Monitoring And Control ◽  
Membrane Processes ◽  
Mechanistic Modelling ◽  
Process Monitoring And Control

Membrane processes are complex systems, often comprising several physicochemical phenomena, as well as biological reactions, depending on the systems studied. Therefore, process modelling is a requirement to simulate (and predict) process and membrane performance, to infer about optimal process conditions, to assess fouling development, and ultimately, for process monitoring and control. Despite the actual dissemination of terms such as Machine Learning, the use of such computational tools to model membrane processes was regarded by many in the past as not useful from a scientific point-of-view, not contributing to the understanding of the phenomena involved. Despite the controversy, in the last 25 years, data driven, non-mechanistic modelling is being applied to describe different membrane processes and in the development of new modelling and monitoring approaches. Thus, this work aims at providing a personal perspective of the use of non-mechanistic modelling in membrane processes, reviewing the evolution supported in our own experience, gained as research group working in the field of membrane processes. Additionally, some guidelines are provided for the application of advanced mathematical tools to model membrane processes.

scholarly journals Photochemistry of 1-Phenyl-4-Allyl-Tetrazol-5-One: A Theoretical Study Contribution towards Mechanism Elucidation

2021 ◽  
Vol 11 (9) ◽  
pp. 4045
Author(s):  
Amilcar Duque-Prata ◽  
Carlos Serpa ◽  
Pedro J. S. B. Caridade
Keyword(s):  
Density Functional ◽  
Reaction Pathway ◽  
Intramolecular Proton Transfer ◽  
Polarizable Continuum Model ◽  
Uv Spectra ◽  
Point Of View ◽  
Basis Set ◽  
Pathway Evolution ◽  
Photodegradation Mechanism ◽  
Energetic Point

The photodegradation mechanism of 1-phenyl-4-allyl-tetrazol-5-one has been studied using (time-dependent) density functional theory with the M06-HF, B3LYP, and PBE0 functionals and the VDZ basis set. All calculations have been carried out using the polarizable continuum model to simulate the solvent effects of methanol. The reaction pathway evolution on the triplet state has been characterised to validate a previously postulated experimental-based mechanism. The transition states and minimums have been initially located by local scanning in partial constrained optimisation, followed by a fully relaxed search procedure. The UV spectra has shown to be better described with PBE0 functional when compared with the experimental results, having the M06-HF a shift of 40 nm. From the energetic point of view, the postulated mechanism has been validated in this work showing a concerted photoextrusion of the N2 molecule. The intramolecular proton transfer occurs at a later stage of the mechanism after cyclization of the allyl group on a triplet biradical intermediate. The photoproduct observed experimentally, a pyrimidinone, has been characterised. The infrared spectroscopic reaction profile has also been proposed.

scholarly journals A surrogate-assisted optimization approach for multi-response end milling of aluminum alloy AA3105

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2419-2439
Author(s):  
Tamal Ghosh ◽  
Yi Wang ◽  
Kristian Martinsen ◽  
Kesheng Wang
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Data Driven ◽  
Optimal Cutting Parameters

Abstract Optimization of the end milling process is a combinatorial task due to the involvement of a large number of process variables and performance characteristics. Process-specific numerical models or mathematical functions are required for the evaluation of parametric combinations in order to improve the quality of the machined parts and machining time. This problem could be categorized as the offline data-driven optimization problem. For such problems, the surrogate or predictive models are useful, which could be employed to approximate the objective functions for the optimization algorithms. This paper presents a data-driven surrogate-assisted optimizer to model the end mill cutting of aluminum alloy on a desktop milling machine. To facilitate that, material removal rate (MRR), surface roughness (Ra), and cutting forces are considered as the functions of tool diameter, spindle speed, feed rate, and depth of cut. The principal methodology is developed using a Bayesian regularized neural network (surrogate) and a beetle antennae search algorithm (optimizer) to perform the process optimization. The relationships among the process responses are studied using Kohonen’s self-organizing map. The proposed methodology is successfully compared with three different optimization techniques and shown to outperform them with improvements of 40.98% for MRR and 10.56% for Ra. The proposed surrogate-assisted optimization method is prompt and efficient in handling the offline machining data. Finally, the validation has been done using the experimental end milling cutting carried out on aluminum alloy to measure the surface roughness, material removal rate, and cutting forces using dynamometer for the optimal cutting parameters on desktop milling center. From the estimated surface roughness value of 0.4651 μm, the optimal cutting parameters have given a maximum material removal rate of 44.027 mm3/s with less amplitude of cutting force on the workpiece. The obtained test results show that more optimal surface quality and material removal can be achieved with the optimal set of parameters.

scholarly journals Analysis of Forces in Vibro-Impact and Hot Vibro-Impact Turning of Advanced Alloys

2011 ◽  
Vol 70 ◽  
pp. 315-320 ◽  
Author(s):  
Riaz Muhammad ◽  
Agostino Maurotto ◽  
Anish Roy ◽  
Vadim V. Silberschmidt
Keyword(s):  
Finite Element ◽  
Cutting Forces ◽  
Three Dimensional ◽  
Element Model ◽  
Machining Process ◽  
Strain Rates ◽  
Machining Processes ◽  
Machined Surface ◽  
Cutting Zone

Analysis of the cutting process in machining of advanced alloys, which are typically difficult-to-machine materials, is a challenge that needs to be addressed. In a machining operation, cutting forces causes severe deformations in the proximity of the cutting edge, producing high stresses, strain, strain-rates and temperatures in the workpiece that ultimately affect the quality of the machined surface. In the present work, cutting forces generated in a vibro-impact and hot vibro-impact machining process of Ti-based alloy, using an in-house Ultrasonically Assisted Turning (UAT) setup, are studied. A three-dimensional, thermo-mechanically coupled, finite element model was developed to study the thermal and mechanical processes in the cutting zone for the various machining processes. Several advantages of ultrasonically assisted turning and hot ultrasonically assisted turning are demonstrated when compared to conventional turning.

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