Application of the Taguchi method to select the optimum cutting parameters for tangential cylindrical grinding of AISI D3 tool steel

Özay, Çetin; Ballikaya, Hasan; Savaş, Vedat

doi:10.17222/mit.2014.293

Cited by 10 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Applying formulas ( 5), (6) to calculate ni value. Applying formulas (7), (8) to calculate vi value. The results are presented in Table 4.…”

Section: Multi-criteria Decision Making Using the Waspas Methodsmentioning

confidence: 99%

“…Study on determination of cutting parameters to ensure the minimum value of surface roughness when grinding the AISI D3 steel was also performed according to matrix using Taguchi method. S/N method was also applied to analyze the experimental results [8]. The analyzed results showed that to obtain the smallest surface roughness, the grinding wheel speed was 2000 rev/min, workpiece speed 220 rev/min, feed rate was 3.2 mm/rev, and depth of cut was 0.005 mm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Combination of Taguchi – Entropy – WASPAS - PIV Methods for Multi-Criteria Decision Making when External Cylindrical Grinding of 65G Steel

Duc¹

2021

Journal of Machine Engineering

View full text Add to dashboard Cite

This paper presents a study on the multi-creteria decision making in the external cylindrical grinding process of 65G steel. An aluminum oxide grinding wheel was used in the experimental process. The experimental matrix was designed according to the Taguchi method with twenty-seven experiments. Five parameters were used to design the experimental matrix including workpiece velocity, feed rate, depth of cut, dressing feed rate, and dressing depth of cut. The surface roughness and Material Removal Rate (MRR) were determined for each experiment. This is the first time that the Weighted Aggregates Sum Product ASsessment (WASPAS) and Proximity Indexed Value (PIV) methods were used to make the multi-criteria decision for grinding process. The weighs of ouput criteria (surface roughness and MRR) were determined by Entropy method. Both WASPAS and PIV methods determined an experiment that simultaneously ensured the "minimum value" of surface roughness and "maximum value" of MRR.

show abstract

“…Applying formulas ( 5), (6) to calculate ni value. Applying formulas (7), (8) to calculate vi value. The results are presented in Table 4.…”

Section: Multi-criteria Decision Making Using the Waspas Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Combination of Taguchi – Entropy – WASPAS - PIV Methods for Multi-Criteria Decision Making when External Cylindrical Grinding of 65G Steel

Duc¹

2021

Journal of Machine Engineering

View full text Add to dashboard Cite

show abstract

“…The work on cylindrical grinding had also been reported by various researchers (Kumar et al 2016, Ozay et al 2016. The grinding wheel grain size and work speed are the most influential parameters that affect MRR and R a (Kumar et al 2016).…”

Section: Introductionmentioning

confidence: 87%

“…The grinding wheel grain size and work speed are the most influential parameters that affect MRR and R a (Kumar et al 2016). The parameters like depth of cut and feed rate increases the surface roughness, while the wheel speed reduces the roughness in the cylindrical grinding of AISI D3 tool steel (Ozay et al 2016). Demir et al (2010) reported that an increase in grain size and depth of cut influenced the grinding forces and surface roughness of the ground samples.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the effect of grinding wheel for grinding of AISI D3 tool steel under different conditions

et al. 2022

View full text Add to dashboard Cite

The surface finish of ground samples is highly influenced by the grinding parameters, grinding conditions and the type of grinding wheel. This paper emphasizes on the effect of various grinding factors such as the grinding conditions, the type of grinding wheel and operating process parameters like depth of cut and table speed on the surface roughness of the ground samples. Two types of grinding wheels alumina (Al2O3) and cubic boron nitride (CBN) were used for grinding AISI D3 tool steel under dry and wet conditions. The material removal rate and surface roughness were evaluated for all the ground samples. The results showed that wet grinding outperformed dry grinding and provided a better surface finish while using both grinding wheels. Machine Learning was implemented to optimize the grinding parameters. Multi-objective optimization using genetic algorithm was done and a Pareto frontier chart was made to help determine what values for the input parameters would achieve the required outputs such as material removal rate and surface roughness. Two different approaches Genetic Algorithm and Principle Component Analysis were then compared for multi-objective optimization. The type of grinding wheel used had a dominant effect on the surface roughness of ground samples while the depth of cut had a lesser effect.

show abstract

“…During the machining process of Inconel 718 (Kivak, 2012), tool temperature easily increases due to the low thermal conductivity of this material. As a result of the higher toughness level of the material, shavings formation proves challenging during the machining process (Ay, 2010;Özay et al, 2016;Savaş et al, 2016). As the manufacturing cost of this material is relatively high, any fault during the machining process may lead to serious monetary losses (Ay et al, 2010;Lima et al, 2016;Bhattacharya et al, 1983;Özay et al, 2016;Savaş et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Design Optimization of Machining Parameters for AWJ Turning Operations of 718 Inconel Super alloy Based on the Taguchi

Kartal¹

2018

Uluslararası Muhendislik Arastirma Ve Gelistirme Dergisi

View full text Add to dashboard Cite

Inconel Alloy 718 super alloy was machined using abrasive water jet (AWJ) in this study. Following the cutting process, average surface roughness (Ra µm) and material removal rate (MRR) were investigated and operating parameters were optimized using Taguchi method. Among the machining parameters were pump pressure (PP) (200, 350 MPa), nozzle feed rate (NFR) (5, 105 and 205 mm/min); abrasive flow rate (AFR) (50, 200 and 350 g/min); spindle speed (SS) (25, 50 and 75 RPM) and standoff distance (SOD) (2, 8 and 14 mm). Taguchi L18 (21 x34) orthogonal factorial experiment organization is adopted as experiment design. The effect of parameters on Ra and depth of cut (DoC) was investigated statistically using the outcomes of the variance analysis and S/N rates. As a result of the empirical studies, PP proved to have the highest effect on Ra by 42.35%. On the other hand, NFR proved to have the highest effect on DoC by 72.85%. Increasing SS has improved Ra value while increasing DoC.

show abstract

Application of the Taguchi method to select the optimum cutting parameters for tangential cylindrical grinding of AISI D3 tool steel

Cited by 10 publications

References 9 publications

The Combination of Taguchi – Entropy – WASPAS - PIV Methods for Multi-Criteria Decision Making when External Cylindrical Grinding of 65G Steel

The Combination of Taguchi – Entropy – WASPAS - PIV Methods for Multi-Criteria Decision Making when External Cylindrical Grinding of 65G Steel

Investigation on the effect of grinding wheel for grinding of AISI D3 tool steel under different conditions

Design Optimization of Machining Parameters for AWJ Turning Operations of 718 Inconel Super alloy Based on the Taguchi

Contact Info

Product

Resources

About