scholarly journals Determination of the optimal cutting parameters for machining technical plastics

2020 ◽  
Vol 54 (1) ◽  
pp. 11-15
Author(s):  
P. Mošorinski ◽  
S. Prvulovic ◽  
L. Josimovic
Keyword(s):  
Cutting Parameters ◽  
Optimal Cutting Parameters

scholarly journals Intelligent Selection of Machining Parameters in Multipass Turnings Using Firefly Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Abderrahim Belloufi ◽  
Mekki Assas ◽  
Imane Rezgui
Keyword(s):  
Production Cost ◽  
Firefly Algorithm ◽  
Optimization Technique ◽  
Cutting Parameters ◽  
Machining Parameters ◽  
Metal Parts ◽  
Multipass Turning ◽  
Optimal Cutting Parameters ◽  
Selection Of

Determination of optimal cutting parameters is one of the most important elements in any process planning of metal parts. In this paper, a new optimization technique, firefly algorithm, is used for determining the machining parameters in a multipass turning operation model. The objective considered is minimization of production cost under a set of machining constraints. The optimization is carried out using firefly algorithm. An application example is presented and solved to illustrate the effectiveness of the presented algorithm.

scholarly journals Milling of Complex Surfaces of EN 10060 Steel after HVOF Sprayed NiCrBSi Coatings

Coatings ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 744 ◽  
Author(s):  
Jan Valíček ◽  
Marta Harničárová ◽  
Jan Řehoř ◽  
Milena Kušnerová ◽  
Jaroslava Fulemová ◽  
...  
Keyword(s):  
Steel Substrate ◽  
Spherical Surface ◽  
High Strength ◽  
Cutting Parameters ◽  
Surface Adhesion ◽  
Complex Surfaces ◽  
Optimal Cutting Parameters ◽  
Spraying Process ◽  
Nicrbsi Coatings

The high-velocity oxy-fuel spraying process was used to investigate and improve the surface properties of a workpiece. The research was focused on the spherical surface of a workpiece made of high-strength steel, a ball and socket assembly. After spraying with a nickel alloy, the surface was machined by milling. The coating was carried out as a process in which a very thin layer of coating of the required thickness and the required specific properties, i.e., high Vickers hardness, adhesion to the surface, wear resistance and other important characteristics, which must be respected in other machining methods, was applied to the already finished, heat-prepared metal substrate. This article deals with the milling of complex surfaces of steel substrate EN 10060 after spraying with NiCrBSi alloy. After spraying, a total of 15 milling experiments were performed in order to determine precisely the optimal cutting parameters of milling and surface adhesion, based on newly acquired prediction relations. The main presented results are new relations for the determination of optimal technological milling conditions based on the identification of adhesive sections using derived equations. The new relations were verified and also compared with the current literature in the field.

The Development of an Economic Model for the Milling of Titanium Alloys

2010 ◽  
Vol 458 ◽  
pp. 362-367 ◽  
Author(s):  
Song Lin Ding ◽  
R. Izamshah R.A. ◽  
John Mo ◽  
Yong Wei Zhu
Keyword(s):  
Titanium Alloys ◽  
Design Of Experiment ◽  
Economic Model ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Taguchi Methods ◽  
Specific Data ◽  
Optimal Function ◽  
Optimal Cutting Parameters

This paper presents a model for the determination of optimal cutting parameters in the milling of Titanium alloys based on real manufacturing data collected from cutting tests. The objective of the optimal function is to achieve the lowest overall costs. Design of Experiment and Taguchi methods are applied in the design of cutting tests. Optimal cutting parameters such as cutting speed, feed, depths of cut are obtained by solving the economic model which is developed according to workshop-specific data.

Determination of Cutting Forces for Micro Milling

2008 ◽  
Author(s):  
Shih-Ming Wang ◽  
Zou-Sung Chiang ◽  
Da-Fun Chen
Keyword(s):  
Cutting Force ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Micro Milling ◽  
Force Model ◽  
Machining Parameters ◽  
Cutting Force Model ◽  
Optimal Cutting Parameters

To enhance the implementation of micro milling, it is necessary to clearly understand the dynamic characteristics of micro milling so that proper machining parameters can be used to meet the requirements of application. By taking the effect of minimum chip thickness and rake angle into account, a new cutting force model of micro-milling which is function the instantaneous cutting area and machining coefficients was developed. According to the instantaneous rotation trajectory of cutting edge, the cutting area projected to xy-plane was determined by rectangular integral method, and used to solve the instantaneous cutting area. After the machining coefficients were solved, the cutting force of micro-milling for different radial depths of cut and different axial depths of cut can be predicted. The results of micro-milling experimental have shown that the force model can predict the cutting force accurately by which the optimal cutting parameters can be selected for micro-milling application.

Optimization of CNC Cutting Parameters by the Electrical Power Method: Turning Case

2005 ◽  
Author(s):  
E. Gutierrez Romo ◽  
J. Caldero´n
Keyword(s):  
Material Removal ◽  
Electrical Power ◽  
Cutting Parameters ◽  
Experimental Methodology ◽  
Power Method ◽  
Machining Processes ◽  
Manufacturing Line ◽  
Optimal Cutting Parameters ◽  
Material Tool

As machining processes become one of the most common kinds of manufacturing processes in industry, it becomes imperative to optimize cutting parameters in order to reduce machining times and increase surface quality. This is specially true when piece geometry demands high rates of material removal. In previous work by the authors, piezoelectric dynamometers have been used to find cutting forces which in turn allows finding of optimal cutting parameters. Although the methodology reported has proved to be very effective, its application in the production line has not been straightforward as the use of a piezoelectric dynamometer requires an expensive setup and skilled technicians. The objective of this work is to propose and validate an experimental methodology that allows the determination of optimal cutting parameters for material-tool pairs by measuring the electrical power consumed by the machine-tool during cutting. This latter approach is more economical and easy to apply in the manufacturing line. Optimized parameters obtained through this methodology yield improvements up to more than twice on removal rates compared to those recommended by tool suppliers for the same process requirements.

Development of Graphical Interface for Determination of Optimal Cutting Parameters in Turning Operations

2016 ◽  
Vol 685 ◽  
pp. 948-951 ◽  
Author(s):  
M.N. Bogoljubova ◽  
O.V. Sumtsova ◽  
D.V. Doschinsky
Keyword(s):  
Cutting Parameters ◽  
Graphical Form ◽  
Graphical Interface ◽  
Optimal Parameters ◽  
Turning Process ◽  
The Impact ◽  
Optimal Cutting Parameters ◽  
The Given ◽  
Cutting Modes

The present paper proposes graphical interface for determination of optimal parameters of cutting modes for turning process. The proposed graphical interface is different from other well-known ones. The impact of different factors on the cutting process in order to determine optimal parameters in accordance with the given effectiveness criteria are analyzed. The visual graphical form of information presentation, database, mathematical model of optimization, algorithms and computer programs have been developed.

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.

Optimization of Cutting Conditions in Multi-Pass Milling

2016 ◽  
Vol 823 ◽  
pp. 525-530
Author(s):  
Abderrahim Belloufi ◽  
Mekki Assas ◽  
Mabrouk Hecini ◽  
Imane Rezgui
Keyword(s):  
Hybrid Genetic Algorithm ◽  
Cutting Parameters ◽  
Cutting Conditions ◽  
Optimum Number ◽  
Optimization Strategy ◽  
Milling Operations ◽  
Optimal Values ◽  
Number Of Passes ◽  
Fine Tune

In this paper, a new, optimization strategy is used for the determination of the optimum cutting parameters for multipass milling operations. This strategy is based on the “minimum production time” criterion. The optimum number of passes is determined via dynamic programming, and the optimal values of the cutting conditions are found based on the objective function developed for the typified criterion by using a hybrid genetic algorithm with SQP. GA is the main optimizer of this algorithm, whereas SQP is used to fine-tune the results obtained from the GA. Furthermore, the convergence characteristics and robustness of the proposed method have been explored through comparisons with results reported in literature. The obtained results indicate that the proposed strategy is effective compared to other techniques carried out by different researchers.

Experimental study on cutting factors of multi-layer machining for large aerospace thin-walled structural parts

2021 ◽  
pp. 095440892110403
Author(s):  
Hangzhuo Yu ◽  
Han Zhong ◽  
Yong Chen ◽  
Lei Lin ◽  
Jing Shi ◽  
...  
Keyword(s):  
Coordinate System ◽  
Experimental Method ◽  
Cutting Parameters ◽  
Machining Process ◽  
Machining Error ◽  
Machining Errors ◽  
Inner Surface ◽  
Thin Walled ◽  
Optimal Cutting Parameters ◽  
Cutting Path

Large aerospace thin-walled structures will produce deformation and vibration in the machining process, which will cause machining error. In this paper, a cutting experimental method based on multi-layer machining is proposed to analyze the influence of cutting tool, cutting path, and cutting parameters on machining error in order to obtain the optimal cutting variables. Firstly, aiming at the situation that the inner surface of the workpiece deviates from the design basis, the laser scanning method is used to obtain the actual shape of the inner surface, and the method of feature alignment is designed to realize the unification of the measurement coordinate system and machining coordinate system. Secondly, a series of cutting experiments are used to obtain the machining errors of wall thickness under different cutting tools, cutting paths, and cutting parameters, and the variation of machining errors is analyzed. Thirdly, a machining error prediction model is established to realize the prediction of machining error, and the multi-objective optimization method is used to optimize the cutting parameters. Finally, a machining test was carried out to validate the proposed cutting experimental method and the optimal cutting parameters.

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