Investigation of GFRP Gear Accuracy and Surface Roughness Using Taguchi and Grey Relational Analysis

2020 ◽  
Vol 19 (01) ◽  
pp. 147-165
Author(s):  
Atul Sharma ◽  
M. L. Aggarwal ◽  
Lakhwinder Singh
Keyword(s):  
Surface Roughness ◽  
Cutting Speed ◽  
Root Diameter ◽  
Cutting Fluid ◽  
Thickness Variation ◽  
Machining Parameters ◽  
Glass Fiber Reinforced ◽  
Grey Relational Grade ◽  
Optimum Response ◽  
Grey Relational

Glass fiber reinforced polymer (GFRP) composite gear is used in a number of applications where fine motion transmission and silent rotation is required. In order to increase its usage there is a need to increase the quality of gear. Shrinkage problem is associated with injection molded gear. In present case blank is prepared by injection molding and teeth are cut on gear shaper by which metrology can be controlled by optimizing the machining parameters. An analysis of variance was applied on 27 experiments to validate the process and found out that rotary feed is at rank 1 which is 0.15[Formula: see text]mm/stroke, cutting fluid ratio is at rank 2 which is 12%, cutting speed is at rank 3 which is 240 stroke/min, fluid flow rate is at rank 4 which is 30 ml/min. By using these parameters optimum performance obtained is 0.213[Formula: see text]mm root diameter deviation (RD), 0.165[Formula: see text]mm tooth thickness variation (TT) and 1[Formula: see text][Formula: see text]m roughness average (Ra) with grey relational grade of 0.8318. The optimum response provided the best value of RD, TT and Ra for the range included in experimental results which is 0.138 to 0.416[Formula: see text]mm, 0.012 to 0.187[Formula: see text]mm and 1.2 to 2.43[Formula: see text][Formula: see text]m respectively. Surface roughness improvement in this work is 49.8% higher as compared to result available in literature.

Machining parameters effect in dry turning of AISI 316L stainless steel using coated carbide tools

2015 ◽  
Vol 231 (4) ◽  
pp. 676-683 ◽  
Author(s):  
Rusdi Nur ◽  
MY Noordin ◽  
S Izman ◽  
D Kurniawan
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Power Consumption ◽  
Cutting Force ◽  
Tool Life ◽  
Cutting Speed ◽  
Cutting Fluid ◽  
Machining Parameters ◽  
Aisi 316L ◽  
Coated Carbide

Austenitic stainless steel AISI 316L is used in many applications, including chemical industry, nuclear power plants, and medical devices, because of its high mechanical properties and corrosion resistance. Machinability study on the stainless steel is of interest. Toward sustainable manufacturing, this study also includes the power consumption during machining along with other machining responses of cutting force, surface roughness, and tool life. Turning on the stainless steel was performed using coated carbide tool without using cutting fluid. The turning was performed at various cutting speeds (90, 150, and 210 m/min) and feeds (0.10, 0.16, and 0.22 mm/rev). Response surface methodology was adopted in designing the experiments to quantify the effect of cutting speed and feed on the machining responses. It was found that cutting speed was proportional to power consumption and was inversely proportional to tool life, and showed no significant effect on the cutting force and the surface roughness. Feed was proportional to cutting force, power consumption, and surface roughness and was inversely proportional to tool life. Empirical equations developed from the results for all machining responses were shown to be useful in determining the optimum cutting parameters range.

scholarly journals The Experimental Investigation of Surface Roughness After Dry Turning of Steel S235

2019 ◽  
Vol 26 (4) ◽  
pp. 179-184
Author(s):  
Justyna Molenda
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Scientific Work ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Workpiece Material ◽  
Important Indicator

AbstractNowadays lot of scientific work inspired by industry companies was done with the aim to avoid the use of cutting fluids in machining operations. The reasons were ecological and human health problems caused by the cutting fluid. The most logical solution, which can be taken to eliminate all of the problems associated with the use of cooling lubricant, is dry machining. In most cases, however, a machining operation without lubricant finds acceptance only when it is possible to guarantee that the part quality and machining times achieved in wet machining are equalled or surpassed. Surface finish has become an important indicator of quality and precision in manufacturing processes and it is considered as one of the most important parameter in industry. Today the quality of surface finish is a significant requirement for many workpieces. Thus, the choice of optimized cutting parameters is very important for controlling the required surface quality. In the present study, the influence of different machining parameters on surface roughness has been analysed. Experiments were conducted for turning, as it is the most frequently used machining process in machine industry. All these parameters have been studied in terms of depth of cut (ap), feed rate (f) and cutting speed (vc). As workpiece, material steel S235 has been selected. This work presents results of research done during turning realised on conventional lathe CDS 6250 BX-1000 with severe parameters. These demonstrate the necessity of further, more detailed research on turning process results.

scholarly journals OPTIMASI PARAMETER MESIN LASER CUTTING TERHADAP KEKASARAN DAN LAJU PEMOTONGAN PADA SUS 316L MENGGUNAKAN TAGUCHI GREY RELATIONAL ANALYSIS METHOD

2016 ◽  
Vol 11 (2) ◽  
pp. 97
Author(s):  
Rakasita R ◽  
Karuniawan BW ◽  
Anda Iviana Juniani
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Laser Cutting ◽  
Cutting Speed ◽  
Cutting Process ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Cutting Rate ◽  
Grey Relational

Optimasi parameter adalah teknik yang digunakan pada proses manufaktur untuk menghasilkan produk terbaik. Penelitian ini bertujuan untuk mengoptimasi parameter CNC laser cutting, yaitu titik fokus sinar laser, tekanan gas cutting dan cutting speed untuk mengurangi variasi terhadap respon kekasaran dan laju pemotongan pada material SUS 316L. Masing-masing parameter memiliki 3 level dan pada penelitian ini menggunakan matriks orthogonal L9 (34). Metode ANOVA dan Taguchi digunakan untuk menganalisis data hasil percobaan. Optimasi kekasaran minimum permukaan dan laju pemotongan maksimum pada proses laser cutting dilakukan dengan menggunakan Grey relational analysis. Eksperimen konfirmasi digunakan untuk membuktikan hasil optimal yang telah didapatkan dari metode Taguchi Grey relational analysis. Hasil eksperimen menunjukkan bahwa Taguchi Grey relational analysis efektif digunakan untuk mengoptimasi parameter pemesinan pada laser cutting dengan multi respon. AbstractParameter optimization is used in manufacturing as an indicator to produce the best manufacturing product. This paper studies an optimization parameters of CNC laser cutting such as focus of laser beam, pressure cutting gases and cutting speed for reducing variation of surface roughness and cutting rate on material SUS 316L. Based on L9(34) orthogonal array parameters, it is analized using ANOVA based on Taguchi method. In order to optimaze the minimum surface roughness and maximum cutting rate in laser cutting process, it is used Grey relational analysis. The confirmation experiments used to validate the optimal results that has done by Taguchi method. The results show that the Taguchi Grey relational analysis is being effective to optimize the machining parameters for laser cutting process with two responses.

scholarly journals Simultaneous optimization of machine and tool parameters for EDM using WC/Co P/M electrode made with micron and nano sized particles

10.30544/582 ◽  
2021 ◽  
Author(s):  
Nadimpalli Sarada Purnima ◽  
Srinivasa Rao Pujari ◽  
Siva Prasad Dora
Keyword(s):  
Surface Roughness ◽  
Particle Size ◽  
Surface Hardness ◽  
Response Characteristic ◽  
Performance Measure ◽  
Influential Factor ◽  
Simultaneous Optimization ◽  
Machining Parameters ◽  
Grey Relational Grade ◽  
Grey Relational

Multi-response characteristic optimization is the most desired aspect of the components produced from electric discharge machining (EDM). Obtaining the optimal combination of parameters for surface roughness (SR) and micro-hardness (MH) is always a challenging task as the machining parameters favourable to one performance measure adversely affects the other. The present paper deals with the simultaneous optimization of SR and MH of D2 alloy steel during EDM with tungsten carbide (WC)/cobalt (Co) P/M electrode by considering electrode and machine tool parameters. Experimental run order was planned with Taguchi’s orthogonal arrays (OA) and in the present investigation, it is based on L18 OA. The analysis of variance (ANOVA) performed for the grey relational grade (GRG) showed that the tool parameter “particle size” (PS) is the most influential factor (61.43%) for simultaneous improvement of performance measures. The P/M electrode made of fine particle size (i.e., at nano level) has improved the process stability and reduced the arcing and short-circuiting results in reduced surface roughness. Simultaneously, the formation of the hard intermetallic phase’s viz., Fe3C, Cr23C6, W2C, Fe6W6C, and Cr2Fe14C on the EDMed surface has increased the surface hardness. The optimal set of parameters was validated through confirmation experiments.

scholarly journals Comparative Analysis of Machining Stainless Steel using Soluble and Vegetable Oils as Cutting Fluids

2019 ◽  
Vol 4 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Temitayo Samson Ogedengbe ◽  
Peter Awe ◽  
Ojotu Ijiwo Joseph
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Vegetable Oil ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Fluid ◽  
Cutting Fluids ◽  
Machining Parameters ◽  
Groundnut Oil ◽  
Machining Parameter

In this study, the performance of groundnut oil as an alternate cutting fluid was compared with that of soluble oil during machining of stainless steel. The temperature at the cutting zone, surface roughness and the chip formation were monitored under the two cutting conditions (soluble oil and vegetable oil). The machining parameters used were cutting speed (75 – 135 rev/min), feed rate (0.01 – 0.05 mm3/mm) and depth of cut (0.01 – 0.08 mm). The experiment was designed using Taguchi orthogonal array of Minitab 18 which generated a 9 run machining parameter mix for the experimentation. The Physiochemical properties of the various fluids were also analyzed to determine the properties and constituent elements of the cutting fluids. The actual machining of the stainless steel bar was done using a Colchester mastiff lathe machine. Results show that feed rate and cutting speed had the most significant effect on surface roughness during machining of stainless steel both with groundnut oil and soluble oil. Soluble oil was a better coolant but poorer in lubrication as vegetable oil reduced surface roughness more when used. Surface roughness value improved from 9.21μm during machining with soluble oil to 3.84μm during machining with groundnut oil which represented a 58.3% improvement. Hence, vegetable oil is therefore recommended as good alternative cutting fluid to soluble oil during machining of stainless steel.

The Use of the Taguchi-Grey Based to Optimize High Speed End Milling with Multiple Performance Characteristics

2006 ◽  
Vol 505-507 ◽  
pp. 835-840 ◽  
Author(s):  
Shen Jenn Hwang ◽  
Yunn Lin Hwang ◽  
B.Y. Lee
Keyword(s):  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Performance ◽  
Grey Relational Grade ◽  
Grey Relational

This paper presents a new approach for the optimization of the high speed machining (HSM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis has been studied. Optimal machining parameters can then be determined by the grey relational grade as the performance index. In this study, the machining parameters such as cutting speed, feed rate and axial depth of cut are optimized under the multiple performance characteristics including, tool life, surface roughness, and material removal rate(MMR). As shown experimental results, machining performance in the HSM process can be improved effectively through this approach.

Selecting Significant Process Parameters of ECG Process Using Fuzzy-MCDM Technique

2015 ◽  
Vol 2 (1) ◽  
pp. 38-53 ◽  
Author(s):  
Goutam Kumar Bose
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Multiple Criteria Decision Making ◽  
Lower Surface ◽  
Substantial Improvement ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Performance ◽  
Grey Relational Grade ◽  
Grey Relational

The present paper highlights selection of significant machining parameters during Electrochemical grinding while machining alumina-aluminum interpenetrating phase composites by MCDM techniques. The conflicting responses like higher material removal rate, lower surface roughness, lower overcut and lower cutting force are ensured simultaneously by a single parametric combination. Control parameters like electrolyte concentration, voltage, depth of cut and electrolyte flow rate have been considered for experimentation. VIKOR is one of the multiple criteria decision making (MCDM) models to determine the reference ranking from a set of alternatives in the presence of conflicting criteria. Finally Grey Relational Analysis is performed to optimize multiple performances in which different levels combinations of the factors are ranked based on grey relational grade. Surface roughness is given more importance than other responses, using Fuzzy Set Theory considering basic objective of the process. It is observed that substantial improvement in machining performance takes place following this technique. The study highlights the effects of different process variables on multiple performances for complex process like ECG.

scholarly journals Multiple Response Optimization of machining parameters on turning of AA 6063 T6 aluminum alloy which established on Taguchi L9 orthogonal array coupled with Grey relational analysis

2021 ◽  
pp. 974-982
Author(s):  
D. S. Sai Ravi Kiran ◽  
Sanapala Sri Ram ◽  
Tangeti Bhaskararao ◽  
Boddu Eswar Venkat Sai ◽  
Kari Suraj Kumar ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Orthogonal Array ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dry Cutting ◽  
Grey Relational Grade ◽  
Grey Relational

With numerous responses established on Taguchi L9, orthogonal array coupled with current work proposes a novel methodology for optimizing machining parameters on turning of AA 6063 T6 aluminum alloy. Experimental assessments are accomplished on AA 6063 T6 aluminum alloy. Turning trails are carried out under dry cutting conditions using an uncoated carbide insert. Cutting parameters such as cutting speed, feed rate, and depth of cut are optimized in this effort while numerous responses such as surface roughness(Ra) and material removal rate are taken into consideration (MRR). From the grey analysis, a grey relational grade(GRG) is calculated. The optimal amounts of parameters have been identified based on the values of grey relational grade, and then ANOVA is used to determine the significant influence of parameters. To authenticate the test result, a confirmation test is executed. The result of the experiments shows that by using this method. the turning process responses can be significantly improved.

Analysis for optimal decisions on turning Ti–6Al–4V with Taguchi–grey method

2013 ◽  
Vol 228 (1) ◽  
pp. 152-157 ◽  
Author(s):  
Kosaraju Satyanarayana ◽  
Anne Venu Gopal ◽  
Popuri Bangaru Babu
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Experimental Studies ◽  
Cutting Speed ◽  
Rake Angle ◽  
Individual Performance ◽  
Process Parameter ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Grey Relational Grade

The problem of machining titanium is one of the ever-increasing magnitudes due to its low thermal conductivity and work-hardening characteristic. In the present work, experimental studies have been carried out to obtain the optimum conditions for machining titanium alloy. The effect of machining parameters such as speed, feed, depth of cut and back rake angle on cutting force, and surface roughness were investigated. The significance of these parameters, on cutting force and surface roughness, has been established using the analysis of variance. The degree of influence of each process parameter on individual performance characteristic was analyzed from the experimental results obtained using the grey relational grade matrix. The back rake angle was identified as the most influential process parameter on cutting force and surface roughness. The cutting speed is identified as the most significant parameter for the turning operation according to the weighted sum grade of the cutting force and surface roughness.

scholarly journals Multi-response Optimization of Surface Roughness Roundness and MRR in Precision Turn-Boring of 15-5PH Stainless Steel Using Taguchi-Grey Approach

2017 ◽  
Author(s):  
Shen-Jenn Hwang ◽  
Yi-Hung Tsai
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Feed Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Experimental Results ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Fluid Temperature ◽  
Grey Relational

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for 15-5PH Stainless steel by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as concentration of cutting fluid , temperature of cutting fluid , feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error and material removal rate, the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is shown that the most significant factor is cutting speed, followed by feed rate, concentration of cutting fluid, radial depth of cut and temperature of cutting fluid. Finally, confirmation tests were carried out to make a comparison between the experimental results and developed model. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

Sign in / Sign up

Export Citation Format

Share Document