A Comparative Analysis Between High Speed Dynamic and Traditional Pocketing Toolpaths in Precision Milling Machines

2016 ◽  
Author(s):  
Gustavo M. Minquiz ◽  
Vicente Borja ◽  
Marcelo López-Parra ◽  
David Dornfeld ◽  
Pablo Flores
Keyword(s):  
Energy Consumption ◽  
Comparative Analysis ◽  
Tool Wear ◽  
Carbon Emissions ◽  
High Speed ◽  
Face Milling ◽  
High Speeds ◽  
Milling Operations ◽  
Different Types ◽  
Milling Machines

Different types of toolpaths have been extensively studied with regards to different factors such as energy consumption and tool wear. However, toolpaths have been introduced recently, where high speeds and dynamic movements are combined to provide higher performance. The aim of this paper is to compare a spiral toolpath strategy, which has been studied previously with good results in energy consumption, with a high speed dynamic toolpath strategy, which combines helical and dynamic movements, with regards to energy consumption, tool wear and carbon emissions. Several advantages are identified with a high speed dynamic toolpath strategy over the typical spiral toolpath strategy in terms of tool wear, energy consumption and carbon emissions. The results show that the high speed dynamic toolpath is a better alternative for different milling operations such as slotting, pocketing, and face milling.

scholarly journals Machining Parameters and Toolpath Productivity Optimization Using a Factorial Design and Fit Regression Model in Face Milling and Drilling Operations

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Gustavo M. Minquiz ◽  
Vicente Borja ◽  
Marcelo López-Parra ◽  
Alejandro C. Ramírez-Reivich ◽  
Leopoldo Ruiz-Huerta ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Linear Equations ◽  
Cutting Parameters ◽  
Face Milling ◽  
Machining Parameters ◽  
Significance Level ◽  
Manufacturing Operations ◽  
Milling Operations ◽  
Energy Consumption Optimization ◽  
Common Activity

Very commonly, a mechanical workpiece manufactured industrially includes more than one machining operation. Even more, it is a common activity of programmers, who make a decision in this regard every time a milling and drilling operation is performed. This research is focused on better understanding the power behavior for face milling and drilling manufacturing operations, and the methodology followed was the design of experiments (DOEs) with the cutting parameters set in combination with toolpath evaluation available in commercial software, having as main goal to get a predictive power equation validated in two ways, linear or nonlinear, and understanding the energy consumption and the quality surface in face milling and final diameter in drilling. The results show that it is possible to find difference in a power demand of 1.52 kW to 3.9 kW in the same workpiece, depending on the operations (face milling or drilling), cutting parameters, and toolpath chosen. Additionally, the equations modelled showed acceptable values to predict the power, with p values higher than 0.05 which is the significance level for the nonlinear and linear equations with an R square predictive of 98.36. Some conclusions established that optimization of the cutting parameters combined with toolpath strategies can represent an energy consumption optimization higher than 0.21% and the importance to try to find an energy consumption balance when a workpiece has different milling operations.

scholarly journals Analysis of tool wear and surface roughness in high-speed milling process of aluminum alloy Al6061

2021 ◽  
pp. 71-84
Author(s):  
Nhu-Tung Nguyen ◽  
Dung Hoang Tien ◽  
Nguyen Tien Tung ◽  
Nguyen Duc Luan
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Tool Wear ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Speed ◽  
Milling Process ◽  
Face Milling ◽  
Depth Of Cut ◽  
High Speed Milling

In this study, the influence of cutting parameters and machining time on the tool wear and surface roughness was investigated in high-speed milling process of Al6061 using face carbide inserts. Taguchi experimental matrix (L9) was chosen to design and conduct the experimental research with three input parameters (feed rate, cutting speed, and axial depth of cut). Tool wear (VB) and surface roughness (Ra) after different machining strokes (after 10, 30, and 50 machining strokes) were selected as the output parameters. In almost cases of high-speed face milling process, the most significant factor that influenced on the tool wear was cutting speed (84.94 % after 10 machining strokes, 52.13 % after 30 machining strokes, and 68.58 % after 50 machining strokes), and the most significant factors that influenced on the surface roughness were depth of cut and feed rate (70.54 % after 10 machining strokes, 43.28 % after 30 machining strokes, and 30.97 % after 50 machining strokes for depth of cut. And 22.01 % after 10 machining strokes, 44.39 % after 30 machining strokes, and 66.58 % after 50 machining strokes for feed rate). Linear regression was the most suitable regression of VB and Ra with the determination coefficients (R2) from 88.00 % to 91.99 % for VB, and from 90.24 % to 96.84 % for Ra. These regression models were successfully verified by comparison between predicted and measured results of VB and Ra. Besides, the relationship of VB, Ra, and different machining strokes was also investigated and evaluated. Tool wear, surface roughness models, and their relationship that were found in this study can be used to improve the surface quality and reduce the tool wear in the high-speed face milling of aluminum alloy Al6061

scholarly journals Evaluation of the influence of different clamping chuck types on energy consumption, tool wear and surface qualities in milling operations

2018 ◽  
Vol 21 ◽  
pp. 575-582
Author(s):  
B. Thorenz ◽  
H.-H. Westermann ◽  
M. Kafara ◽  
M. Nützel ◽  
R. Steinhilper
Keyword(s):  
Energy Consumption ◽  
Tool Wear ◽  
Milling Operations

Analysis of the Carbon Emissions Characteristics of Energy Consumption in Beijing between 1992-2011

2014 ◽  
Vol 962-965 ◽  
pp. 1587-1590
Author(s):  
Jing Ping Luo ◽  
Jian Feng Zhao
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Greenhouse Gases ◽  
Energy Saving ◽  
Carbon Emissions ◽  
High Speed ◽  
Carbon Recycling ◽  
Energy Saving Technology ◽  
Reduce Emissions

There is a long way to reduce emissions with the high speed of urbanization and economic growth in Beijing. In this article, depend on the IPCC country listing guidelines of greenhouse gases, carbon emissions has been calculated of Beijing beteeen1992-2011, then analysis of its historical characteristics . Beijing should seize the opportunity to research and carry out carbon recycling and energy saving technology in a planned and staged way.

scholarly journals Investigating the Design of Condition Monitoring Systems to Evaluate Surface Roughness under the Variability in Tool Wear and Fixturing Conditions

2013 ◽  
Vol 572 ◽  
pp. 467-470 ◽  
Author(s):  
Jabbar Abbas ◽  
Amin Al-Habaibeh ◽  
Dai Zhong Su
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Condition Monitoring ◽  
End Milling ◽  
Milling Operations ◽  
Different Types ◽  
Machined Parts ◽  
Condition Monitoring Systems ◽  
Condition Monitoring System

Surface finish of machined parts in end milling operations is significantly influenced by process faults such as tool wear and tool holding (fixturing system). Therefore, monitoring these faults is considerably important to improve the quality of the product. In this paper, an investigation is presented to design the condition monitoring system to evaluate the surface roughness of the workpiece under effects of gradual tool wear and different types of the fixturing system. Automated Sensor and Signal Processing Selection (ASPS) approach is implemented and tested to determine the sensitivity of the sensory signals to estimate surface roughness under the variable conditions in comparison to surface roughness measurement device. The results indicate that the system is capable of detection the change and the trend in surface roughness. However, the sensitive features are found to be different based on the change in the fixturing system.

Acoustic emission monitoring of tool wear during the face milling of steels and aluminium alloys using a fibre optic sensor. Part 2: Frequency analysis

1997 ◽  
Vol 211 (4) ◽  
pp. 311-319 ◽  
Author(s):  
T A Carolan ◽  
S R Kidd ◽  
D P Hand ◽  
S J Wilcox ◽  
P Wilkinson ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Frequency Analysis ◽  
Aluminium Alloys ◽  
Face Milling ◽  
Fibre Optic ◽  
Milling Operations ◽  
The Face ◽  
Wear Monitoring ◽  
Absolute Measurements

This paper describes the application of acoustic emission (AE) frequency analysis to cutting tool wear monitoring in finish milling operations. AE detection was achieved using a fibre optic interferometer which, unlike conventional piezoelectric transducers, allows absolute measurements of the frequency content of the signals, generated during face milling of various steels and aluminium alloys, to be made. A model detailing the expected variations in AE mean frequency with various forms of tool wear in the different processes is presented and is validated by the practical set of tool wear tests using the fibre optic interferometer.

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