scholarly journals Optimization of Manufacturing Production and Process

2021 ◽  
Author(s):  
YinQuan Yu
Keyword(s):  
Fourier Transform ◽  
Wavelet Packet ◽  
Cutting Speed ◽  
Rotation Velocity ◽  
Vibration Velocity ◽  
Operational Parameters ◽  
Vibration Data ◽  
Spindle Rotation ◽  
Optimization Parameters ◽  
Processing Optimization

This chapter mainly introduces production processing optimization, especially for machining processing optimization on CNC. The sensor collects the original vibration data in time domain and converts them to the main feature vector using signal processing technologies, such as fast Fourier transform (FFT), short-time Fourier transform (STFT), and wavelet packet in the 5G AI edge computing. Subsequently, the main feature will be sent for cloud computing using genetic programming, Space Vector Machine (SVM), etc. to obtain optimization results. The optimization parameters in this work include machining spindle rotation velocity, cutting speed, and cutting depth, while, the result is the optimized main spindle rotation speed range of CNC, which met machining roughness requirements. Finally, the relationship between vibration velocity and machining quality is further studied to optimize the three operational parameters.

IDENTIFICATION OF INTERHARMONICS BASED ON WAVELET PACKET TRANSFORM

2021 ◽  
Vol 3 (1) ◽  
pp. 031-036
Author(s):  
S. A. GOROVOY ◽  
◽  
V. I. SKOROKHODOV ◽  
D. I. PLOTNIKOV ◽  
◽  
...  
Keyword(s):  
Fourier Transform ◽  
Simulation Model ◽  
Frequency Domain ◽  
Time Domain ◽  
Wavelet Packet ◽  
High Accuracy ◽  
Wavelet Packet Transform ◽  
Mathematical Apparatus ◽  
Nonlinear Load ◽  
The Time Domain

This paper deals with the analysis of interharmonics, which are due to the presence of a nonlinear load. The tool for the analysis was a mathematical apparatus - wavelet packet transform. Which has a number of advantages over the traditional Fourier transform. A simulation model was developed in Simulink to simulate a non-stationary non-sinusoidal mode. The use of the wavelet packet transform will allow to determine the mode parameters with high accuracy from the obtained wavelet coefficients. It also makes it possible to obtain information, both in the frequency domain of the signal and in the time domain.

scholarly journals Machine Fault Classification Based on Local Discriminant Bases and Locality Preserving Projections

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Qingbo He ◽  
Xiaoxi Ding ◽  
Yuanyuan Pan
Keyword(s):  
Feature Extraction ◽  
Wavelet Packet ◽  
Fault Classification ◽  
Feature Extraction Method ◽  
Locality Preserving Projections ◽  
Vibration Data ◽  
Pattern Structure ◽  
Locality Preserving ◽  
Machine Fault

Machine fault classification is an important task for intelligent identification of the health patterns for a mechanical system being monitored. Effective feature extraction of vibration data is very critical to reliable classification of machine faults with different types and severities. In this paper, a new method is proposed to acquire the sensitive features through a combination of local discriminant bases (LDB) and locality preserving projections (LPP). In the method, the LDB is employed to select the optimal wavelet packet (WP) nodes that exhibit high discrimination from a redundant WP library of wavelet packet transform (WPT). Considering that the obtained discriminatory features on these selected nodes characterize the class pattern in different sensitivity, the LPP is then applied to address mining inherent class pattern feature embedded in the raw features. The proposed feature extraction method combines the merits of LDB and LPP and extracts the inherent pattern structure embedded in the discriminatory feature values of samples in different classes. Therefore, the proposed feature not only considers the discriminatory features themselves but also considers the dynamic sensitive class pattern structure. The effectiveness of the proposed feature is verified by case studies on vibration data-based classification of bearing fault types and severities.

scholarly journals Surface Quality Assessment after Milling AZ91D Magnesium Alloy Using PCD Tool

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 617 ◽  
Author(s):  
Ireneusz Zagórski ◽  
Jarosław Korpysa
Keyword(s):  
Surface Roughness ◽  
Magnesium Alloy ◽  
High Speed ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Roughness Parameters ◽  
Operational Parameters

Surface roughness is among the key indicators describing the quality of machined surfaces. Although it is an aggregate of several factors, the condition of the surface is largely determined by the type of tool and the operational parameters of machining. This study sought to examine the effect that particular machining parameters have on the quality of the surface. The investigated operation was the high-speed dry milling of a magnesium alloy with a polycrystalline diamond (PCD) cutting tool dedicated for light metal applications. Magnesium alloys have low density, and thus are commonly used in the aerospace or automotive industries. The state of the Mg surfaces was assessed using the 2D surface roughness parameters, measured on the lateral and the end face of the specimens, and the end-face 3D area roughness parameters. The description of the surfaces was complemented with the surface topography maps and the Abbott–Firestone curves of the specimens. Most 2D roughness parameters were to a limited extent affected by the changes in the cutting speed and the axial depth of cut, therefore, the results from the measurements were subjected to statistical analysis. From the data comparison, it emerged that PCD-tipped tools are resilient to changes in the cutting parameters and produce a high-quality surface finish.

Experimental Design Applied to the Machining of Windows Cage Ball Joints Homokinetic SAE 8620 Steel with CBN Tool

2011 ◽  
Vol 223 ◽  
pp. 573-578
Author(s):  
Nivaldo Lemos Coppini ◽  
José C. C. Santana ◽  
Elesandro Antonio Baptista ◽  
Daniel B. da Rosa ◽  
Aroldo Alcantara
Keyword(s):  
Tool Life ◽  
Cutting Speed ◽  
Life Time ◽  
Steel Part ◽  
Hyperbolic Model ◽  
23 Factorial Design ◽  
Cbn Tool ◽  
Processing Optimization ◽  
Ball Joints ◽  
Sae 8620 Steel

In this work a factorial planning had been used to evaluate the CBN tool life during cut-ting SAE 8620 steel. Part U2222 of a TPGW 160408 insert of TX-LS TB650 and 2NU-SHMA6942 S7182BN300 classes from two manufacturers were used in this experiment. A 23 factorial design was used In cutting process to evaluate the behavior of the tool life and reason of the exchange of the part on influences of the chamfer (in S and T+S), the advancing speeds (0.09, 0.10 and 0.11 mm/rpm) at a cutting speed of 91.2 m/min. Model have been fit by variance analysis (ANOVA) and the processing optimization was done by response surface methodology (RSM). Results showed that a hyperbolic model had more adjusting than other models and the optimization showed a high life time for the TX-LS TB650 tool from A manufacturer on 0.09 mm/rpm of advancing speed, where it was observed that the pre-cranking was the reason of the exchange.

A Brief Review on Fault Diagnosis of Rotating Machineries

2014 ◽  
Vol 541-542 ◽  
pp. 635-640 ◽  
Author(s):  
S.P. Mogal ◽  
D.I. Lalwani
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Fault Diagnosis ◽  
Vibration Signal ◽  
Response Measurement ◽  
Rotor Systems ◽  
Vibration Data ◽  
Systems Model ◽  
Processing Techniques ◽  
Signal Processing Techniques

Vibration in any rotating machines is due to faults like misalignment, unbalance, crack, mechanical looseness etc. Identification of these faults in rotor systems, model and vibration signal based methods are used. Signal processing techniques such as Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), Wigner-Ville Distribution (WVD) and Wavelet Transform (WT) are applied to vibration data for faults identification. The intent of the paper is to present a review and summarize the recent research and developments performed in condition monitoring of rotor system with the purpose of rotor faults detection. In present paper discuss the different signal processing techniques applied for fault diagnosis. Vibration response measurement has given information concerning any fault within a rotating machine and many of the methods utilizing this technique are reviewed. A detail review of the subject of fault diagnosis in rotating machinery is presented.

scholarly journals Optimizing Uniaxial Oil Extraction of Bulk Rapeseeds; Spectrophotometric and Chemical Analyses of the Extracted Oil under Pretreatment Temperatures and Heating Intervals

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1755
Author(s):  
Cimen Demirel ◽  
Abraham Kabutey ◽  
David Herák ◽  
Petr Hrabě ◽  
Čestmír Mizera ◽  
...  
Keyword(s):  
Response Surface ◽  
Acid Value ◽  
Statistical Technique ◽  
Deformation Energy ◽  
Oil Extraction ◽  
Heating Time ◽  
Optimization Parameters ◽  
Response Surface Regression ◽  
Processing Optimization ◽  
Experimental Runs

Optimizing the operating factors in edible oil extraction requires a statistical technique such as a response surface methodology for evaluating their effects on the responses. The examined input factors in this study were the diameter of pressing vessel, VD (60, 80, and 100 mm), temperature, TPR (40, 60, and 80 °C), and heating time, HTM (30, 60 and 90 min). The combination of these factors generated 17 experimental runs where the mass of oil, oil yield, oil extraction efficiency, and deformation energy were calculated. Based on the response surface regression analysis, the combination of the optimized factors was VD: 100 (+1) mm; TPR: 80 °C (+1) and HTM: 60 (0) min); VD: 60 (−1) mm; TPR: 80 °C (+1) and HTM: 75 (+0.5) min and VD: 100 (+1) mm; TPR: 80 °C (+1) and HTM: 90 (+1). The absorbance and transmittance values significantly (p < 0.05) correlated with the wavelength and temperature, but they did not correlate significantly (p > 0.05) with heating time. The peroxide value did not correlate significantly with temperature, however, it correlated significantly with heating time. Neither the acid value nor the free fatty acid value correlated with both temperature and heating time. The findings of the present study are part of our continuing research on oilseeds’ processing optimization parameters.

scholarly journals Process Simulation and Optimization of Anaerobic Co-Digestion

2021 ◽  
Vol 9 ◽  
Author(s):  
Abrar Inayat ◽  
Shams Forruque Ahmed ◽  
F. Djavanroodi ◽  
Fatima Al-Ali ◽  
Mira Alsallani ◽  
...  
Keyword(s):  
Process Simulation ◽  
Waste Treatment ◽  
Production Systems ◽  
Biogas Production ◽  
System Optimization ◽  
Design Development ◽  
Operational Parameters ◽  
Simulation And Optimization ◽  
Optimization Parameters ◽  
Biogas Output

Anaerobic digestion (AD) is an established method that has been extensively utilized for waste management, waste treatment, and biogas production. Anaerobic co-digestion (AcoD) is regarded as a practical approach to address substrate characteristics and system optimization issues. The distinction between AcoD and mono-digestion is that AcoD has a higher organic loading and significant substrate composition variation. There are many factors involved in AcoD which affect the biogas plant’s production ability and performance. Using response surface methodology (RSM) to forecast the optimal conditions for maximum biogas output, this article provides an overview of the different operational parameters in the AcoD process, modeling of the AcoD process, and overall process optimization. Standard software used for AcoD process simulation are Aspen Plus, SuperPro Designer, BioWin, CFD, and MATLAB. Review addresses design, development, and optimization frameworks for biogas production systems that take numerous aspects into account. The most significant AcoD optimization parameters include temperature, co-substrate concentration, inoculum ratio (percent), and C/N ratio.

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