Determination of input parameters for machining process DSS

2013 ◽  
Vol 0 (39) ◽  
Author(s):  
В В ЛИМАРЕНКО ◽  
И П ХАВИНА
Keyword(s):  
Machining Process ◽  
Input Parameters

Analysis of methodologies for determination of DEM input parameters

2021 ◽  
Author(s):  
Rondinelli M. Lima ◽  
Rodolfo J. Brandao ◽  
Raphael L. Santos ◽  
Claudio R. Duarte ◽  
Marcos A. S. Barrozo
Keyword(s):  
Input Parameters

Identification of the Minimal Thickness of Cutting Layer Based on the Acoustic Emission Signal

2016 ◽  
Vol 686 ◽  
pp. 39-44 ◽  
Author(s):  
Józef Gawlik ◽  
Joanna Krajewska-Śpiewak ◽  
Wojciech Zębala
Keyword(s):  
Signal Strength ◽  
Machining Process ◽  
Precision Machining ◽  
Emission Signal ◽  
Minimal Thickness ◽  
Machining Allowance ◽  
Forming Precision ◽  
Ae Signal ◽  
Cutting Zone

The chip-forming precision machining process plays a significant role in the mechanical technology. In planning of machining operation, it is crucial to supply the information about the possible minimal value of the machining allowance. For the technologist, when planning the machining operation, it is important to define the minimal thickness of cutting layer correctly. This article presents a new method of describing the start of decohesion process in a workpiece, meaning the determination of the minimal thickness of cutting layer based on the AE signal generated in the cutting zone. The research conducted on the turning of an alloy steel and the analysis of the AE signal strength confirmed that the proposed method opens new possibilities in quickening the identification of the minimal thickness of cutting layer under normal machining conditions.

Device Modeling of a-Si:H Alloy Solar Cells: Calibration Procedure for Determination of Model Input Parameters

1998 ◽  
Vol 507 ◽  
Author(s):  
M. Zeman ◽  
R.A.C.M.M. Van Swaaij ◽  
E. Schroten ◽  
L.L.A. Vosteen ◽  
J.W. Metselaar
Keyword(s):  
Solar Cell ◽  
Material Properties ◽  
Calibration Procedure ◽  
Model Parameters ◽  
Model Input ◽  
A Value ◽  
Input Parameters ◽  
Simulated Material ◽  
Good Agreement

ABSTRACTA calibration procedure for determining the model input parameters of standard a-Si:H layers, which comprise a single junction a-Si:H solar cell, is presented. The calibration procedure consists of: i) deposition of the separate layers, ii) measurement of the material properties, iii) fitting the model parameters to match the measured properties, iv) simulation of test devices and comparison with experimental results. The inverse modeling procedure was used to extract values of the most influential model parameters by fitting the simulated material properties to the measured ones. In case of doped layers the extracted values of the characteristic energies of exponentially decaying tail states are much higher than the values reported in literature. Using the extracted values of model parameters a good agreement between the measured and calculated characteristics of a reference solar cell was reached. The presented procedure could not solve directly an important issue concerning a value of the mobility gap in a-Si:H alloys.

scholarly journals Improvement of Machining Processes: A Case Study

2019 ◽  
Vol 2 (3) ◽  
pp. 634-641
Author(s):  
Hakan Gökçe ◽  
Ramazan Yeşilay ◽  
Necati Uçak ◽  
Ali Teke ◽  
Adem Çiçek
Keyword(s):  
Material Removal ◽  
Current Practice ◽  
Complex Geometry ◽  
Vital Role ◽  
Machining Process ◽  
Machining Processes ◽  
Machining Time ◽  
Machining Strategy ◽  
Removal Processes

In material removal processes, determination of optimal machining strategy is a key factor to increase productivity. This situation is gaining more importance when machining components with complex geometry. The current practice in the determination of machining strategy mostly depends on the experience of the machine operator. However, poorly designed machining processes lead to time-consuming and costly solutions. Therefore, the improvement of machining processes plays a vital role in terms of machining costs. In this study, the machining process of a boom-body connector (GGG40) of a backhoe loader was improved. Improvements of toolpaths and cutting conditions of 22 different material removal processes were checked through a CAM software. According to the simulation results, the process plan was rearranged. Besides, some enhancements in casting model were conducted to decrease in the number of machining operations. When compared to current practice, a reduction of 55% in machining time was achieved.

Last-Verlagerungsverhalten von Kugelgewindetrieben/Load displacement behavior on ball screws

2020 ◽  
Vol 110 (05) ◽  
pp. 295-298
Author(s):  
Christian Brecher ◽  
Florian Kneer ◽  
Stephan Neus
Keyword(s):  
Machine Tools ◽  
Machining Process ◽  
Ball Screw ◽  
Elastic Displacement ◽  
Technical Paper ◽  
Process Forces ◽  
Displacement Behavior ◽  
Load Displacement ◽  
Machine Structure

Die axiale Steifigkeit von Kugelgewindetrieben ist wesentlich für das Betriebsverhalten von Werkzeugmaschinen. Während der Bearbeitung werden die Prozesskräfte über den Kugelgewindetrieb in die Maschinenstruktur übertragen. Kugelgewindetriebe tragen daher maßgeblich zur Qualität und Produktivität von Werkzeugmaschinen bei. Dieser Beitrag beschreibt eine Methode zur messtechnischen, prüfstandsgebundenen Ermittlung des Last-Verlagerungsverhaltens an Kugelgewindetrieben.   The axial elastic displacement of ball screws are essential for the operating behavior of machine tools. During machining, process forces must be transmitted to the machine structure via the ball screw. Ball screws contribute significantly to the quality and productivity of machine tools. This technical paper describes a methodology for the metrological determination of the load-displacement behavior on ball screws.

A Simulation Study on the End Milling Operation with Multiple Process Steps of Aeronautical Frame Monolithic Components

2011 ◽  
Vol 66-68 ◽  
pp. 569-572
Author(s):  
Hai Chao Ye ◽  
Guo Hua Qin ◽  
Cong Kang Wang ◽  
Dong Lu
Keyword(s):  
End Milling ◽  
Machining Process ◽  
Deformation Analysis ◽  
Tool Paths ◽  
Milling Operation ◽  
Multiple Process ◽  
Monolithic Components ◽  
Milling Forces ◽  
The Given

Machining deformation has always been a bottleneck issue in the manufacturing field of aeronautical monolithic components. On the base of finite element method, the effect of the process steps and tool paths on the workpiece stiffness and the redistribution of residual stress in the machining process of aeronautical frame monolithic component was investigated under the given fixturing scheme. Thus, the prediction of the workpiece deformation can be carried out in reason. The proposed simulation approach to deformation analysis can be used to observe the true characteristic of milling forces and machining deformations. Therefore, the proposed method can supply the theoretical basis for the determination of the optimal process parameters.

Modelling of tribological responses of composites using integrated ANN-GA technique

2020 ◽  
pp. 002199832096052
Author(s):  
Santanu Sardar ◽  
Swati Dey ◽  
Debdulal Das
Keyword(s):  
Optimization Technique ◽  
Matrix Composites ◽  
Large Numbers ◽  
Wide Range ◽  
Input Parameters ◽  
Input Variables ◽  
Velocity Input ◽  
Abrasive Size

In the present article, artificial neural networks (ANNs) and genetic algorithm (GA) methodology were integrated to model tribological characteristics of stir-cast Al-Zn-Mg-Cu matrix composites under two-body abrasion considering large numbers of experimentally generated results. Tribo-responses of wear rate (Wrt), coefficient of friction (COF) and roughness of abraded surface (RAS) were evaluated under wide range of intrinsic ( i.e., particle quantity) and extrinsic ( i.e., abrasive size, load, distance and velocity) input parameters. Characteristics of Wrt, COF and RAS are often mutually contradictory in nature and so, multi-objective optimization technique becomes imperative for selection and design of machine components. Accordingly, those were optimized through Pareto solutions. Sensitivity of different factors was analyzed on each of the tribo-performances and validated via experimental evidences. Amongst the input variables, particle quantity and abrasive size dominated significantly over other variables except load which imparted modest influences. The role of various input parameters was explained through determination of different micromechanisms via exhaustive post wear characterizations, microstructural and surface topography attributes. Lowest values of Wrt and COF with a modest value of RAS were identified at 15 ± 2 wt.% particle quantity.

Sign in / Sign up

Export Citation Format

Share Document