Simultaneous optimization of surface roughness and material removal rate for turning of X20Cr13 stainless steel

Bouzid, Lakhdar; Boutabba, Smail; Yallese, Mohamed Athmane; Belhadi, Salim; Girardin, François

doi:10.1007/s00170-014-6043-9

Cited by 50 publications

(44 citation statements)

References 24 publications

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“…ANOVA results for arithmetic mean Ra are illustrated in Table 4, which indicates that feed and nose radius are the significant as well as dominant factors affecting Ra as their P value is less than 0.05 and larger F-value. This is in good agreement with previously published work (Bouzid et al 2014b;Meddour et al 2015;Nouioua et al 2017). Insert nose radius has the most important significant influence on surface finish and its contribution is 44.59%.…”

Section: Statistical Analysis On Surface Roughnesssupporting

confidence: 93%

Surface Roughness Analysis for Economical Feasibility Study of Coated Ceramic Tool in Hard Turning Operation

Panda

Das

Dhupal

2017

Process Integr Optim Sustain

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The paper addresses the assessment, modeling, and optimization study of surface roughness in finish dry hard turning (FDHT) of AISI 4340 steel with coated ceramic tool by considering the cutting speed, axial feed, depth of cut, and nose radius as machining parameters. Thirty sets of longitudinal turning trials based on central composite (CCD) design of experiments (DOEs) are performed, and response surface methodology (RSM), particle swarm optimization (PSO), and finally, Gilbert's approach are subsequently applied for mathematical modeling, response optimization, tool life estimation, and economic analysis. Additionally, various diagnostic tests have been executed to check the statistical significance and validity, adequacy, effectiveness, and fitness of data of the proposed model using analysis of variance (ANOVA) and Anderson-Darling normal probability test. Results indicated that nose radius and feed are the most significant controlled as well as dominant factors for hard turning operation if the minimization of the machined surface roughness is considered. The RSM model combined with PSO technique leads to minimum surface roughness value similar to cylindrical grinding of 0.2021 μm, corresponding to optimum process parameters: 220 m/min of cutting speed, 0.05 mm/rev of feed, 0.193 mm of depth of cut, and 1.6 mm of tool nose radius. Finally, under pre-cited optimum machining conditions, tool life was evaluated to perform cost analysis for the economical justification and feasibility of coated ceramic tools in hard turning. The total machining cost per piece is ensued to be lower ($0.34) as a consequence of higher tool life (44 min), reduction in downtime, and enhancement in savings, which finds economical benefits in hard turning. The novelty aspects of the present work are that (i) it demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing coated ceramic tool in hard turning processes considering technological, economical, and ecological aspects, which are helpful and efficient from industrial point of view and (ii) it contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-55 HRC.

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Section: Statistical Analysis On Surface Roughnesssupporting

confidence: 93%

Surface Roughness Analysis for Economical Feasibility Study of Coated Ceramic Tool in Hard Turning Operation

Panda

Das

Dhupal

2017

Process Integr Optim Sustain

View full text Add to dashboard Cite

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“…The rest of terms do not represent any significant effects on MRR. The same order of significant effect of machining parameters on the MRR was found by Bouzid et al (2014) when turning of X20Cr13 stainless steel. …”

Section: Analysis Of Variance (Anova)supporting

confidence: 67%

“…Bouzid et al (2014) optimized cutting parameters for determining the minimum surface roughness (Ra) which corresponds to the maximum material removal rate (MRR) in turning of X20Cr13 steel with mono and multi-objective optimizations based on the L16 OA of Taguchi. Taguchi's signal-to-noise ratio was used to accomplish the objective function.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous improvement of surface quality and productivity using grey relational analysis based Taguchi design for turning couple (AISI D3 steel/ mixed ceramic tool (Al2O3 + TiC))

Zerti¹,

Yallese²,

Zerti³

et al. 2018

10.5267/j.ijiec

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Current optimization strategies are based on the increase the productivity and the quality with lower cost in short time. Grey relational analysis "GRA" based on Taguchi design was proposed in this paper for simultaneous improvement of surface quality and productivity. The turning trials based on mixed Taguchi L18 factorial plan were conducted under dry cutting conditions for the machining couple: AISI D3 steel/mixed ceramic inserts (CC650). The machining parameters taken into account during this study are as follow: major cutting edge angle (χr), cutting insert nose radius (r), cutting speed (Vc), feed rate (f), and depth of cut (ap). Significant effects of machining parameters and their interactions were evaluated by the analysis of variance. Through this analysis, it have been found clearly that feed rate and cutting insert nose radius had a big significant effects on surface quality while depth of cut, feed rate followed by cutting speed had a major effect on productivity. The mathematical relationship between the machining parameters and the performance characteristics was formulated by using a linear regression model with interactions. Optimal levels of parametric combination for achieving the higher surface quality with maximum productivity were selected by grey relational analysis which is based on the high value of grey relational grade. Confirmation experiments were carried out to prove the powerful improvement of experimental results and to validate the effectiveness of the multi-optimization technique applied in this paper.

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“…The response surface methodology (RSM) (Bouzid et al, 2014a;Aouici et al, 2014;Hessainia et al, 2015;Bhaumik & Maity, 2017;Nayak et al, 2017) is both a statistical and a mathematical technique that is useful for modeling and analyzing problems in which responses can be affected by several variables.…”

Section: Response Surface Methodologymentioning

confidence: 99%

“…The study of this parameter is important: the goal is to manufacture low cost, high quality products in short time (Fnides et al, 2013;Bouzid et al, 2014a). The value of Material Removed Rate was calculated by the following Eq.…”

Section: Analysis Of Variance (Anova) For Mrrmentioning

confidence: 99%

Modeling and optimization of surface roughness and productivity thru RSM in face milling of AISI 1040 steel using coated carbide inserts

Fnides¹,

Yallese²,

Khattabi³

et al. 2017

10.5267/j.ijiec

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The aim of this study is to evaluate the impact of factors such as cutting speed, feed rate, and depth of cut on surface roughness and Material Removed Rate (MRR) when machining in dry face milling AISI 1040 steel with coated carbide inserts GC1030 using the response surface methodology (RSM). For this purpose, a number of machining experiments based on statistical three-factor and three-level factorial experiment designs, completed (L27) with a statistical analysis of variance (ANOVA), were performed in order to develop mathematical models and to identify the significant factors of these technological parameters. Multi-objective optimization procedure for minimizing Ra, Ry and Rz and maximizing MRR using desirability approach has been also implementented. The current study was also carried out to investigate the tool life of the inserts. The models found the relationship between the cutting parameters (Vc, fz and ap) and the studied technological parameters. It has been found that the cutting speed was the most affecting surface roughness which is due to the geometry of the insert which has a scraping edge and enables to obtain low roughness even at important feed rate, followed by the feed rate and the depth of cut at the end. The optimal combination of cutting parameters were cutting speed of 314 m/min, feed rate of 0.16 mm/tooth and depth of cut of 0.6 mm with a composite desirability of 0.924.

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Simultaneous optimization of surface roughness and material removal rate for turning of X20Cr13 stainless steel

Cited by 50 publications

References 24 publications

Surface Roughness Analysis for Economical Feasibility Study of Coated Ceramic Tool in Hard Turning Operation

Surface Roughness Analysis for Economical Feasibility Study of Coated Ceramic Tool in Hard Turning Operation

Simultaneous improvement of surface quality and productivity using grey relational analysis based Taguchi design for turning couple (AISI D3 steel/ mixed ceramic tool (Al2O3 + TiC))

Modeling and optimization of surface roughness and productivity thru RSM in face milling of AISI 1040 steel using coated carbide inserts

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