scholarly journals Influence of cutting parameters on surface quality when machining a CoCrWNi alloy

2018 ◽  
Vol 178 ◽  
pp. 01009
Author(s):  
Manuela-Roxana Dijmărescu ◽  
Ioan-Cristian Tarbă ◽  
Maria-Cristina Dijmărescu ◽  
Vlad Gheorghiţă

Due to their excellent biocompatibility and mechanical properties, the use of Co-Cr based alloys in medical applications has increased substantially. An important characteristic of the medical implants is their surface quality, this being a significant constraint when machining this kind of products. The aim of this paper is to present a research conducted in order to determine and expose the influence of turning cutting parameters on the surface roughness of a CoCrWNi alloy.

2011 ◽  
Vol 88-89 ◽  
pp. 34-37
Author(s):  
Kuai Ji Cai

The relationship of the friction coefficient and the MTC were discussed, and the MTC and its effects on surface roughness were a theoretical analysised and experimental verification by AFM (atomic force microscope). The results show that the theoretical MTC tends to be minimal value then before the adhering effect to reach remarkable. Appropriate adjustments cutting parameters, the cutting process can always micro-cutting phase to reach the steady-thin chip, and no plowing phenomenon. So the surface residues highly were reduced and higher surface quality was achieved.


Materials ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 1497 ◽  
Author(s):  
Da Qu ◽  
Peng Zhang ◽  
Jiadai Xue ◽  
Yun Fan ◽  
Zuhui Chen ◽  
...  

In this study, minimum quantity coolant/lubrication (MQCL) is found to have significant impact on the surface quality and mechanical properties of the micromilled thin-walled work piece that is the core component of an aeroaccelerometer. Three kinds of coolants were used in the micromilling process to analyze their effects on surface quality and mechanical properties of the component. The experiment results show that an appropriate dynamic viscosity of coolant helps to improve surface roughness. The high evaporation rate of the coolants can enhance the cooling performance. Comparing with the dry machining case, MQCL has better performance on improving tool wear, surface quality, and mechanical properties of the micromilled work piece. It yielded up to 1.4–10.4% lower surface roughness compared with the dry machining case in this experiment. The machined work piece with the best mechanical properties and the one with the worst mechanical properties appeared in the ethyl alcohol and the dry machining case, respectively. The reasons for deteriorating surface quality and mechanical properties in dry machining cases are also analyzed. For improving the micromilling process, the penetration and cooling effect of the coolants are more important. This paper gives references to obtain better service performance of the component by improving the micromilling process.


2016 ◽  
Vol 686 ◽  
pp. 119-124 ◽  
Author(s):  
Balázs Mikó

The machining of free form surfaces is a current and important issue in die and mould industry. Beside the complex geometry, an accurate and productive machining and good surface quality are needed. The finishing milling carried out by a ball-end or toroid milling cutter defines the surface quality, which is characterized by the surface roughness and the tool path trace. The surface quality is defined by the properties of the milling cutter, the type of surface and its position, as well as the cutting parameters. This article focuses on the z-level milling of steep surfaces by 2.5D milling strategy. The importance of the different elements of the tool path is presented, the effect of cutting parameters is investigated, and a formula to predict the surface roughness is suggested.


2018 ◽  
Vol 24 (2) ◽  
pp. 501-508 ◽  
Author(s):  
Clayton Neff ◽  
Matthew Trapuzzano ◽  
Nathan B. Crane

Purpose Additive manufacturing (AM) is readily capable of producing models and prototypes of complex geometry and is advancing in creating functional parts. However, AM processes typically underperform traditional manufacturing methods in mechanical properties, surface roughness and hermeticity. Solvent vapor treatments (vapor polishing) are commonly used to improve surface quality in thermoplastic parts, but the results are poorly characterized. Design/methodology/approach This work quantifies the surface roughness change and also evaluates the effect on hermeticity and mechanical property impacts for “as-printed” and acetone vapor-polished ABS tensile specimens of 1-, 2- and 4-mm thicknesses produced by material extrusion (FDM). Findings Vapor polishing proves to decrease the power spectral density for surface roughness features larger than 20 µm by a factor of 10× and shows significant improvement in hermeticity based on both perfluorocarbon gross leak and pressure leak tests. However, there is minimal impact on mechanical properties with the thin specimens showing a slight increase in elongation at break but decreased elastic modulus. A bi-exponential diffusion decay model for solvent evaporation suggest a thickness-independent and thickness-dependent time constant with the latter supporting a plasticizing effect on mechanical properties. Originality/value The contributions of this work show vapor polishing can have a substantial impact on the performance for end-use application of ABS FDM components.


2017 ◽  
Vol 24 (Supp02) ◽  
pp. 1850033
Author(s):  
WENYONG SHI ◽  
YAN MA ◽  
CHUNMEI YANG ◽  
BIN JIANG ◽  
ZHE LI

Milling processing is an important way to obtain wood–polyethylene composite (WPC) end products. In order to improve the processing efficiency and surface quality of WPC and meet the practical application requirements, this paper focussed on morphology and roughness of the WPC-milled surface and studied surface quality changes under different cutting parameters and milling methods through multi-parameters milling experiments. The milling surface morphology and roughness of WPC were analyzed and measured during cut-in, cutting and cut-out sections. It also revealed the affect rule of different cutting parameters and milling methods on milled surface morphology and roughness. The results show that the milling surface roughness of WPC products with wood powder content of 70% is significantly larger than the one whose wood powder content is 60%, and defects such as holes are also relatively more. Finally, a surface roughness prediction model was established based on the mathematical regression method and its multi-factor simulation was carried out. A comparative analysis of predictive and experimental values was performed to verify the reliability of the model. It could also provide theoretical guidance and technical guarantee for high processing quality of WPC milling and cutting.


2011 ◽  
Vol 121-126 ◽  
pp. 4640-4645 ◽  
Author(s):  
Shu Ren Zhang ◽  
Xue Guang Li ◽  
Jun Wang ◽  
Hui Wei Wang

Three elements of Cutting dosages have a great effect on parts surface quality and working efficiency, the best organization of cutting three elements for parts surface quality must be found before machining, in order to surface roughness and machining cost of parts, multi-objective optimization model is established in this paper, model is solved by using genetic algorithm. Based on the BP neural network of three layers, forecasting model of surface roughness is established. According to existing experiment data and optimized cutting dosages, analysis and prediction of surface roughness is done. Machining experiment is done by using optimized data. The experiment result verifies feasibility of this optimistic method and prediction method of surface roughness.


Author(s):  
Xiao-fen Liu ◽  
Wen-hu Wang ◽  
Rui-song Jiang ◽  
Yi-feng Xiong ◽  
Kun-yang Lin ◽  
...  

Abstract The current state of surface roughness focuses on the 2D roughness. However, there are shortcomings in evaluating surface quality of particle reinforced metal matrix composites using 2D roughness due to the fact that the measuring direction has a vital impact on the 2D roughness value. It is therefore of great importance and significance to develop a proper criterion for measuring and evaluating the surface roughness of cutting particle reinforced metal matrix composites. In this paper, an experimental investigation was performed on the effect of cutting parameters on the surface roughness in cutting in-situ TiB2/7050Al MMCs. The 2D roughness Ra, 3D roughness Sa and Sq were comparatively studied for evaluating the machined surface quality of in-situ TiB2/7050Al MMCs. The influence of cutting parameters on the surface roughness was also analyzed. The big difference between roughness Ra measured along cutting and feed directions showed the great impact of measuring direction. Besides, surface defects such as pits, grooves, protuberances and voids were observed, which would influence 2D roughness value greatly, indicating that 3D roughness was more suitable for evaluating surface quality of cutting in-situ TiB2/7050Al MMCs. The cutting depth and feed rate were found to have the highest influence on 3D roughness while the effect of cutting speed was minimal. With increasing feed rate, cutting depth or width, the 3D roughness increased accordingly. But it decreased as cutting speed increased.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gökhan Sur ◽  
Ömer Erkan

Purpose Drilling of carbon fiber reinforced plastic (CFRP) composite plates with high surface quality are of great importance for assembly operations. The article aims to optimize the drill geometry and cutting parameters to improve the surface quality of CFRP composite material. In this study, CFRP plates were drilled with uncoated carbide drill bits with standard and step geometry. Thus, the effects of standard and step drill bits on surface quality have been examined comparatively. In addition, optimum output parameters were determined by Taguchi, ANOVA and multiple decision-making methods. Design/methodology/approach Drill bit point angles were selected as 90°, 110° and 130°. In cutting parameters, three different cutting speeds (25, 50 and 75 m/min) and three different feeds (0.1, 0.15 and 0.2 mm/rev) were determined. L18 orthogonal sequence was used with Taguchi experimental design. Three important output parameters affecting the surface quality are determined as thrust force, surface roughness and delamination factor. For each output parameter, the effects of drill geometry and cutting parameters were evaluated. Input parameters affecting output parameters were analyzed using the ANOVA method. Output parameters were estimated by creating regression equations. Weights were determined using the analytic hierarchy process (AHP) method, and multiple output parameters were optimized using technique for order preference by Similarity to An ideal solution (TOPSIS). Findings It has been determined from the experimental results that step drills generate smaller thrust forces than standard drills. However, it has been determined that it creates greater surface roughness and delamination factor. From the Taguchi analysis, the optimum input parameters for Fz step tool geometry, 90° point angle, 75 m/min cutting speed and 0.1 mm/rev feed. For Fd, are standard tool geometry, 90° point angle, 25 m/min cutting speed and 0.1 mm/rev feed and for Ra, are standard tool geometry, 130° point angle, 25 m/min cutting speed and 0.1 mm/rev feed. ANOVA analysis determined that the most important parameter on Fd is the tip angle, with 56.33%. The most important parameter on Ra and Fz was found to be 40.53% and 77.06% tool geometry, respectively. As a result of the optimization with multiple criteria decision-making methods, the test order that gave the best surface quality was found as 4–1-9–5-8–17-2–13-6–16-18–15-11–10-3–12-14. The results of the test number 4, which gives the best surface quality, namely, the thrust force is 91.86 N, the surface roughness is 0.75 µm and the delamination factor is 1.043. As a result of experiment number 14, which gave the worst surface quality, the thrust force was 149.88 N, the surface roughness was 3.03 µm and the delamination factor was 1.163. Practical implications Surface quality is an essential parameter in the drilling of CFRP plates. Cutting tool geometry comes first among the parameters affecting this. Therefore, different cutting tool geometries are preferred. A comparison of these cutting tools is discussed in detail. On the other hand, thrust force, delamination factor and surface roughness, which are the output parameters that determine the surface quality, have been optimized using the TOPSIS and AHP method. In this way, this situation, which seems complicated, is presented in a plain and understandable form. Originality/value In the experiments, cutting tools with different geometries are included. Comparatively, its effects on surface quality were examined. The hole damage mechanism affecting the surface quality is discussed in detail. The results were optimized by evaluating Taguchi, ANOVA, TOPSIS and AHP methods together.


2019 ◽  
Vol 9 (18) ◽  
pp. 3684 ◽  
Author(s):  
Tao Zhou ◽  
Lin He ◽  
Jinxing Wu ◽  
Feilong Du ◽  
Zhongfei Zou

Establishing and controlling the prediction model of a machined surface quality is known as the basis for sustainable manufacturing. An ensemble learning algorithm—the gradient boosting regression tree—is incorporated into the surface roughness modeling. In order to address the problem of a high time cost and tendency to fall into a local optimum solution when the grid search and conjugate gradient method is adopted to obtain the super-parameters of the ensemble learning algorithm, a genetic algorithm is employed to search for the optimal super-parameters in the training process, and a genetic-gradient boosting regression tree (GA-GBRT) algorithm is developed. A fitting goodness of fit is taken as the fitness function value of the genetic algorithm and combined with k-fold cross-validation, as such, the initial model parameters of the gradient boosting regression tree are optimized. Compared to the optimized artificial neural network (ANN) and support vector regression (SVR) and combined with the cutting experiment of 304 stainless steel with a micro-groove tool, a genetic algorithm multi-objective optimization model with the highest cutting efficiency and a supreme surface quality was constructed by applying the GA-GBRT model. The response relationship reveals the non-linear interaction that occurs between the cutting parameters and the surface roughness of 304 stainless steel that is machined by the micro-groove tool. As indicated by the results obtained from the multi-objective optimization, the cutting efficiency can be enhanced by increasing the cutting speed and depth within a small range of surface quality variations. The GA-GBRT model is validated to be reliable in making a prediction of the surface roughness and optimizing the cutting parameters with turning and milling data.


2015 ◽  
Vol 794 ◽  
pp. 201-206
Author(s):  
Vitali Dejkun ◽  
Sören Dietz ◽  
Eberhard Abele

The following article gives an overview on the manufacturing challenges of milling green stage zirconia. Significant influence factors on the surface quality like machine type, cutting parameters, milling strategy and post processing were investigated. The results show a minimal influence of the machine type. Furthermore machining zirconia with high cutting speed and low cutting depth best for surface quality. Tool wear and milling strategies have major influences on surface roughness and chipping. The combination milling strategy leads to material cracks and has negative impacts on the surface quality. Post processes like polishing and sintering improves surface roughness by 50 % after the milling.


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