Controlling Topography of Machined Surface for Adhesive-Sealing

2017 ◽  
Author(s):  
Shun Liu ◽  
Sun Jin ◽  
Xueping Zhang ◽  
Lixin Wang ◽  
Benfu Mei ◽  
...  
Keyword(s):  
Surface Topography ◽  
Adhesive Bonding ◽  
Bonding Process ◽  
Machining Process ◽  
Machining Parameters ◽  
Machined Surface ◽  
Sealing Performance ◽  
Joint Surfaces ◽  
Machining Productivity ◽  
Adhesive Performance

Adhesive is widely used in engine, airplane and other industry parts to bond and seal machined joint surfaces. Adhesive performance is important and mechanically complex, closely related to the adhesive material property, bonding process and topography of machined surfaces. The effects of material properties, bonding process, and the geometry and dimensions of adhesive layer on adhesive performance have been well studied in adhesive research field. However, the effect of the topography of machined surface on sealing performance was somehow neglected in literature. On the other hand, the texture of machined surface, especially at micro-level of surface roughness, usually used as the objective to determine process parameters in machining and also regarded as indicators of machining productivity, has been systemically and sufficiently studied. However sealing performance has not been widely investigated to relate to topography of machined surface generated from machining operation. Actually, the surface topography plays an important role in the both fields as an index for machining process and also a factor for functional performance. Desired surface should be determined firstly and then machining parameters are designed properly to achieve the desired surface, in order to improve the functional behavior such as the applied adhesive sealing performance of machined components. This research has objectives: 1) the desired surface topography is determined based on the relationship between machining operation and surface texture; 2) The effects of machined surface topography on the reliability of adhesive joint surfaces are analytically investigated. Thus, the research provides a systematic thinking for the selection of surface topography and parameters of face milling operation to improve the performance of adhesive bonding and sealing for its industry implementation.

scholarly journals Effects of the Tribological Behaviour of h-BN MQL Nano Cutting Fluid (NCF-MQL) on Turning Inconel 625

2019 ◽  
Vol 11 (4) ◽  
pp. 107-121 ◽  
Author(s):  
Chinmaya PADHY ◽  
Pariniti SINGH
Keyword(s):  
Optimization Technique ◽  
Minimum Quantity Lubrication ◽  
Chip Morphology ◽  
Machining Process ◽  
Cutting Fluid ◽  
Inconel 625 ◽  
Machining Parameters ◽  
Machining Performance ◽  
Tribological Behaviour ◽  
Machined Surface

Minimum quantity lubrication (MQL) is currently a widely used lubricating technique during machining, in which minimum amount of lubricant in the form of mist is delivered to the machining interface, thus helps to reduce the negative effects caused to the environment and human health. Further, to enhance the productivity of machining process specifically for hard-to-cut materials, nano cutting fluid (suitably mixed nano materials with conventional cutting fluid) is used as an alternative method to conventional lubrication (wet) in MQL. In this study, h-BN nano cutting fluid was formulated with 0.1% vol. concentration of h-BN in conventional cutting fluid (Servo- ‘S’) for NCF-MQL technique and its tribological behaviors on machining(turning) performance of Inconel 625 were studied and compared with other lubricating conditions (dry, wet, MQL conventional). The tribological effects were analyzed in terms of tool wear analysis, chip morphology along with statistical analysis for machined surface and evolved cutting forces during machining. The optimal input machining parameters for experiments were defined by the use of Taguchi and Grey relational based multi response optimization technique. Finally, the tribological study shows that the use of h-BN NCF-MQL is a viable and sustainable option for improving machining performance of hard- to- cut material like Inconel 625.

A normal contact stiffness model of machined joint surfaces considering elastic, elasto-plastic and plastic factors

2019 ◽  
Vol 234 (7) ◽  
pp. 1007-1016 ◽  
Author(s):  
Yongquan Zhang ◽  
Hong Lu ◽  
Xinbao Zhang ◽  
He Ling ◽  
Wei Fan ◽  
...  
Keyword(s):  
Surface Topography ◽  
Contact Stiffness ◽  
Fractal Theory ◽  
Fractal Model ◽  
Single Pair ◽  
Machined Surface ◽  
Normal Contact ◽  
Joint Surfaces ◽  
Stiffness Model ◽  
Normal Contact Stiffness

Considering the rough surface as a fractal model makes the research of contact parameters more practical. In the fractal model of the machined surface, the parameters describing the surface topography are independent of the measurement resolution. Based on the elastic, elasto-plastic and plastic deformations of a single pair of contact asperities, a normal contact stiffness model using the fractal model for surface topography description is proposed in this paper. The specimens machined by milling and grinding methods are used to verify the proposed contact stiffness model based on the fractal theory. The experimental and theoretical results indicate that the proposed contact stiffness model is appropriate for the machined joint surfaces.

A New Algorithm for the Numerical Simulation of Machined Surface Topography in Multiaxis Ball-End Milling

2008 ◽  
Vol 130 (1) ◽  
Author(s):  
Wei-Hong Zhang ◽  
Gang Tan ◽  
Min Wan ◽  
Tong Gao ◽  
David Hicham Bassir
Keyword(s):  
Numerical Simulation ◽  
Surface Topography ◽  
End Milling ◽  
Computing Time ◽  
Cutting Edge ◽  
Machining Parameters ◽  
Step Method ◽  
Time Step ◽  
Machined Surface ◽  
Ball End Milling

In milling process, surface topography is a significant factor that affects directly the surface integrity and constitutes a supplement to the form error associated with the workpiece deformation. Based on the tool machining paths and the trajectory equation of the cutting edge relative to the workpiece, a new and general iterative algorithm is developed here for the numerical simulation of the machined surface topography in multiaxis ball-end milling. The influences of machining parameters such as the milling modes, cutter runout, cutter inclination direction, and inclination angle upon the topography and surface roughness values are studied in detail. Compared with existing methods, the basic advantages and novelties of the proposed method can be resumed below. First, it is unnecessary to discretize the cutting edge and tool feed motion and rotation motion. Second, influences of cutting modes and cutter inclinations are studied systematically and explicitly for the first time. The generality of the algorithm makes it possible to calculate the pointwise topography value on any sculptured surface of the workpiece. Besides, the proposed method is proved to be more efficient in saving computing time than the time step method that is commonly used. Finally, some examples are presented and simulation results are compared with experimental ones.

Evaluation of Electrical Discharge Machining Performance on Al (6351)–SiC–B4C Composite

2019 ◽  
pp. 109-124
Author(s):  
Uthayakumar M. ◽  
Suresh Kumar S. ◽  
Thirumalai Kumaran S. ◽  
Parameswaran P.
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Research Work ◽  
Machining Process ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Machining Performance ◽  
Machined Surface ◽  
Output Performance ◽  
B4c Particles

Electrical discharge machining (EDM) process is a non-conventional machining process used for the material which are difficult to machine. In this research work, an attempt has been made to determine the influence of Boron Carbide (B4C) particles on the machinablity of the Al (6351) alloy reinforced with 5 wt. % Silicon Carbide (SiC) Metal Matrix Composite (MMC) through EDM. Influence of machining parameters such as pulse current (I), pulse on time (Ton), duty factor (τ), and gap voltage (V) on affecting the output performance characteristics namely Electrode Wear Ratio (EWR), Surface Roughness (SR) and Power Consumption (PC) which are studied. The result shows that the addition of B4C particles significantly affects the machinablity of the composite, with a contribution of 1.6% on EWR, 3.5% on SR and 19.8% on PC. The crater, recast layer formation, and Heat Affected Zone (HAZ) in the machined surface of the composite are also reported in detail.

scholarly journals Mathematical Modelling of Power Skiving for General Profile based on Numerical Enveloping

2021 ◽  
Author(s):  
Kang Jia ◽  
Junkang Guo ◽  
Tao Ma ◽  
Shaoke Wan
Keyword(s):  
Surface Topography ◽  
Cutting Tools ◽  
Mathematic Model ◽  
Machining Process ◽  
Machined Surface ◽  
High Productivity ◽  
Power Skiving ◽  
Involute Gear ◽  
Motion Speed ◽  
General Profile

Abstract Power skiving is an effective generating machining method for internal parts like gears with respect its high productivity. The general mathematic modelling for power skiving is the basis for cutting tools design, machining precision evaluation, and machining process optimization. Currently, mainly studies are focus on the involute gear machining with adopting the analytical enveloping equation. However, these analytical methods have failed to deal with overcutting for general profile skiving tasks. Moreover, little attention has been devoted to investigate the power skiving process with taking variable configuration parameters, which is significant to control the machined surface topography. Herein, we introduce a mathematic modelling method for power skiving with general profile based on the numerical discrete enveloping. Firstly, the basic mathematic model of power skiving is established, in which the center distance is formulated as polynomial of time. With transforming the power skiving into a forming machining of the swept volume of cutting edge, a numerical algorithm is designed to distinguish the machined transverse profile via the discrete enveloping ideology. Especially, the precise instant contact curve is extracted according to the feed motion speed inversely. Finally, simulations for involute gear and cycloid wheel are carried out to verify the effectiveness of this method and investigate the influence of variable radial motions on the machined slot surface topography. The results show this method is capable to simulate the dynamic power skiving process with general profiles and to evaluate the machined results.

scholarly journals Forward and Inverse Relational Models between Machined Surface Roughness and Key Parameters of Machining Process

2021 ◽  
Author(s):  
Ri Pan ◽  
Ren Xingfei ◽  
Zhenzhong Wang ◽  
Dongju Chen ◽  
Jinwei Fan
Keyword(s):  
Surface Roughness ◽  
Inverse Model ◽  
Forward Model ◽  
Machining Process ◽  
Relational Model ◽  
Universal Method ◽  
Machining Parameters ◽  
Machined Surface ◽  
Average Deviation ◽  
Machined Surface Roughness

Abstract The relational model between machined surface roughness (MSR) and the adopted key machining parameters (KMPs) significantly influences the predictability and controllability of the machining process; therefore, it has attracted considerable attention. However, two critical problems still persist in this field. First, although most existing studies focus on the prediction model for MSR (forward model), wherein the MSR is dependent on input KMPs values, the inverse model that can calculate the KMP based on input MSR value is equally important; however, the inverse model has not been investigated as extensively as the forward model. The second issue is that most of the existing forward models are mainly established based on mechanism analysis; however, due to the complexity of most machining processes, the accuracy and generality of the model are not optimal. Therefore, this paper proposes a universal method for mathematically establishing the inverse model of the relation between the MSR and KMP. Initially, based on the response surface methodology, orthogonal experiments were designed and conducted, and the results were used to establish the forward model between the MSR and KMP. Subsequently, by combining the forward model with a self-developed genetic algorithm-based multi-objective optimization algorithm, an establishing method for inverse model between MSR and KMPs was proposed. Finally, experiments were conducted to validate the developed models. The experimental results show that for the forward model, all the 10 experimental MSR values approach the MSR values predicted by the forward model, and the average deviation was only approximately 7%. Contrarily, for the inverse model, the average deviation was only approximately 7.64%. Both these results verify the accuracy and effectiveness of the proposed models. With this method, as long as the desired processing results and constraints are given, the process parameters can be accurately derived.

scholarly journals Effect of Micro-EDM Parameters on Material Removal Rate of Nonconductive ZrO2 Ceramic

2013 ◽  
Vol 465-466 ◽  
pp. 1329-1333 ◽  
Author(s):  
Abdus Sabur ◽  
Abdul Moudood ◽  
Mohammad Yeakub Ali ◽  
Mohammad Abdul Maleque
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Pyrolytic Carbon ◽  
Carbon Layer ◽  
Machining Process ◽  
Machining Parameters ◽  
Micro Edm ◽  
Machined Surface ◽  
Electro Discharge Machining

Micro-electro discharge machining (micro-EDM) technique, an advanced noncontact machining process, is used for structuring of nonconductive ZrO2 ceramic. In this study copper foil as a conductive layer is adhered on the workpiece surface to initiate the sparks and kerosene is used as dielectric for creation of continuous conductive pyrolytic carbon layer on the machined surface. Voltage (V) and capacitance (C) are considered as the parameters to investigate the process capability of machining parameters in continuous micro-EDM of ZrO2. Different voltage pulses are studied to examine the causes of lower material removal rate (MRR) in micro-EDM of nonconductive ceramics. The results showed that in micro-EDM of ZrO2 MRR increases with the increase of voltage and capacitance initially, but decreases at higher values and no significant materials are removed at capacitances higher than 1nF.

scholarly journals Application of Wavelet Analysis in Tool Wear Evaluation Using Image Processing Method

2018 ◽  
Vol 7 (4.36) ◽  
pp. 426
Author(s):  
Lee Woon Kiow ◽  
Syed Mohamad Aiman Tuan Muda ◽  
Ong Pauline ◽  
Sia Chee Kiong ◽  
Norfazillah Talib ◽  
...  
Keyword(s):  
Wavelet Analysis ◽  
Tool Wear ◽  
Cutting Tool ◽  
Wavelet Coefficient ◽  
Surface Profile ◽  
Machining Process ◽  
Machining Parameters ◽  
Continuous Wavelet ◽  
Monitoring Methods ◽  
Machined Surface

Tool wear plays a significant role for proper planning and control of machining parameters to maintain the product quality. However, existing tool wear monitoring methods using sensor signals still have limitations. Since the cutting tool operates directly on the workpiece during machining process, the machined surface provides valuable information about the cutting tool condition. Therefore, the objective of present study is to evaluate the tool wear based on the workpiece profile signature by using wavelet analysis. The effect of wavelet families, scale of wavelet and statistical features of the continuous wavelet coefficient on the tool wear is studied. The surface profile of workpiece was captured using a DSLR camera. Invariant moment method was applied to extract the surface profile up to sub-pixel accuracy. The extracted surface profile was analyzed by using continuous wavelet transform (CWT) written in MATLAB. The results showed that average, RMS and peak to valley of CWT coefficients at all scale increased with tool wear. Peak to valley at higher scale is more sensitive to tool wear. Haar was found to be more effective and significant to correlate with tool wear with highest R2 which is 0.9301.   

scholarly journals Surface topography after deep rolling with milling kinematics

2021 ◽  
Author(s):  
Berend Denkena ◽  
Alexander Krödel ◽  
Steffen Heikebrügge ◽  
Kolja Meyer ◽  
Philipp Pillkahn
Keyword(s):  
Surface Topography ◽  
Lateral Displacement ◽  
Machining Process ◽  
Analytical Prediction ◽  
Machining Parameters ◽  
Deep Rolling ◽  
Rolling Pressure ◽  
Lateral Displacements ◽  
Logarithmic Relationship ◽  
Experimental Stage

AbstractDeep rolling is a machining process which is used to decrease roughness and to induce compressive residual stresses into component surfaces. A recent publication of this research group showed possibilities to predict the topography during deep rolling of bars in a lathe. Although deep rolling can be used in a milling machine to machine flat specimens, it is still unclear, whether the topography can be predicted to a similar extend using this application. To investigate the influence of the machining parameters on topography, three experimental stages are performed in this paper on cast AlSi10Mg. First, single-track deep rolling experiments are performed under variation of the deep rolling pressure $$p_w$$ p w to find the relationship between $$p_w$$ p w and the indentation geometry. Here, a logarithmic relationship between deep rolling pressure and the indentation characteristics could be found that achieved a relatively high agreement. In the second stage, surfaces are prepared using multi-track deep rolling. Here, the deep rolling pressure $$p_w$$ p w and the lateral displacement $$a_b$$ a b are varied. The multi-track rolled surfaces were compared to an analytical model for the calculation of the theoretical roughness that is based on the logarithmic relationship found in the first experimental stage. Here, the limits of the analytical prediction were shown because high similarities between predicted and measured surfaces only occurred for certain deep rolling pressures $$p_w$$ p w and lateral displacements $$a_b$$ a b . To further investigate the limitations of this procedure, a novel tool concept, which utilizes the rotation of the machine spindle, is used in the third stage. Here, the generated surface can also be interpreted as a periodic sequence of spheric indentations as shown in the second experimental stage, whereas the measured surfaces differed from the expected surfaces. As a result of this paper, the predictability of the surface topography after deep rolling of flat specimens is known (minimum pressure $$p_{w,minAlSi10Mg}$$ p w , m i n A l S i 10 M g  = 5 MPa and minimum lateral displacement $$a_{b,minAlSi10Mg}$$ a b , m i n A l S i 10 M g  = 0.25 mm) and also first results regarding the final topography after using the novel tool concept are presented.

scholarly journals Cryogenic milling and formation of nanostructured machined surface of AISI 4340

2020 ◽  
Vol 9 (1) ◽  
pp. 1104-1117
Author(s):  
Shalina Sheik Muhamad ◽  
Jaharah A. Ghani ◽  
Che Hassan Che Haron ◽  
Hafizal Yazid
Keyword(s):  
End Milling ◽  
Testing Machine ◽  
Machining Process ◽  
Depth Of Cut ◽  
Case Hardening ◽  
Machining Parameters ◽  
Machined Surface ◽  
Radial Depth ◽  
Coated Carbide ◽  
Aisi 4340

AbstractHardened layers are commonly required for automotive components after their production using a machining process in order to enhance the service life of these components. This study investigates the possibility of producing a nanostructured machined surface which can increase the hardness of the machined surface by varying the machining parameters under cryogenic conditions in end milling of AISI 4340. The end milling experiments were performed using multi-layered TiAlN- and AlCrN-coated carbide. Prior to the experiment, a finite element method (FEM) was used to simulate the cutting temperature generated and it had been found that at cutting speed of 200–300 m/min, feed rate of 0.15–0.3 mm/tooth, axial depth of cut of 0.3–0.5 mm, and radial depth of cut of 0.2–0.35 mm, the temperature generated can be sufficiently high to cause austenitic transformation. A field emission scanning electron microscope (FESEM) equipped with angle selective backscattered (AsB) detection analysis was used to investigate the microstructure and machined-affected layers of the machined surfaces. The crystallographic orientation/phase change and nano-hardness were analysed through X-ray diffraction (XRD) and a nano-hardness testing machine. The results showed that the cryogenic machining had significantly affected the surface integrity characteristics of the AISI 4340 alloy due to refined microstructure, favourable phase structure, and higher hardness near the surface layer. The results of this study may be useful in providing an insight into a potential technological shift from conventional surface case hardening processes to the present technique.

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