Modeling and multi-response optimization of machining performance while turning hardened steel with self-propelled rotary tool

Rao, Thella Babu; Krishna, A. Murali; Katta, Ramesh Kumar; Krishna, K. Rama

doi:10.1007/s40436-014-0092-z

Cited by 27 publications

(11 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The regression models of the average roughness and material removal rate were developed for the SPRT process of the hardened steel. 9 The outcomes indicated that the average roughness was decreased by 38.0%, as compared to the initial value. The regression models of machining force components for the self-propelled rotary face milling were developed regarding the milling speed, f r , a, and a, respectively.…”

Section: Introductionmentioning

confidence: 93%

Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Nguyen

Duong

Mia

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

Boosting energy efficiency and machining quality are prominent solutions to achieve sustainable production for turning operations. In this work, a machining condition-based optimization has been performed to decrease the total specific energy (SEC), carbon emission (CE), and average roughness (AR) of the actively driven rotary turning (ADRT) process. The processing factors are the tool rotational speed (Tv), depth of cut (a), feed rate (fr), and workpiece speed (Wv). The turning experiments of the mold material labeled SKD11 have been conducted on a CNC lathe. The regression method is employed to develop comprehensive models of the total specific energy, carbon emissions, and average roughness. The entropy approach is then applied to drive out the weight value of each ADRT response. Finally, the non-dominated sorting particle swarm optimization (NSPSO) is utilized to determine the optimal parameters. The findings indicated that the optimal values of the Tv, a, fr, and Wv are 77 m/min, 0.32 mm, 0.25 mm/rev., and 128 m/min, respectively. The SEC, AR, and CE are decreased by 18.07%, 10.46%, and 5.02%, respectively, as compared to the initial approach. Moreover, the developed active rotary turning operation can be considered as an effective technical solution to boost the machining efficiency of hardened steels.

show abstract

Section: Introductionmentioning

confidence: 93%

Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Nguyen

Duong

Mia

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

show abstract

“…There are minimal studies in the open literature that implemented the multi-objective optimization approach in the area of machining with self-propelled rotary tools [31,32]. In addition, few models have been performed (either analytical or artificial intelligencebased models) to model wear behavior and surface integrity when machining with rotary tools; the majority of the developed models are focused on the cutting forces.…”

Section: Property Materialsmentioning

confidence: 99%

Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

et al. 2021

View full text Add to dashboard Cite

It is necessary to improve the machinability of difficult-to-cut materials such as hardened steel, nickel-based alloys, and titanium alloys as these materials offer superior properties such as chemical stability, corrosion resistance, and high strength to weight ratio, making them indispensable for many applications. Machining with self-propelled rotary tools (SPRT) is considered one of the promising techniques used to provide proper tool life even under dry conditions. In this work, an attempt has been performed to analyze, model, and optimize the machining process of AISI 4140 hardened steel using self-propelled rotary tools. Experimental analysis has been offered to (a) compare the fixed and rotary tools performance and (b) study the effect of the inclination angle on the surface quality and tool wear. Moreover, the current study implemented some artificial intelligence-based approaches (i.e., genetic programming and NSGA-II) to model and optimize the machining process of AISI 4140 hardened steel with self-propelled rotary tools. The feed rate, cutting velocity, and inclination angle were the selected design variables, while the tool wear, surface roughness, and material removal rate (MRR) were the studied outputs. The optimal surface roughness was obtained at a cutting speed of 240 m/min, an inclination angle of 20°, and a feed rate of 0.1 mm/rev. In addition, the minimum flank tool wear was observed at a cutting speed of 70 m/min, an inclination angle of 10°, and a feed rate of 0.15 mm/rev. Moreover, different weights have been assigned for the three studied outputs to offer different optimized solutions based on the designer’s interest (equal-weighted, finishing, and productivity scenarios). It should be stated that the findings of the current work offer valuable recommendations to select the optimized cutting conditions when machining hardened steel AISI 4140 within the selected ranges.

show abstract

“…There are minimal studies in the open literature that implemented the multi-objective optimization approach in the area of machining with self-propelled rotary tools [22,23]. In addition, few models have been performed (either analytical or arti cial intelligence-based models) to model the wear behavior and surface integrity when machining with rotary tools and the majority of the developed models are focused on the cutting forces.…”

Section: Introductionmentioning

confidence: 99%

Towards Analysis and Optimization during Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

Ahmed¹,

Hegab²,

Mohany³

et al. 2021

Preprint

View full text Add to dashboard Cite

It is necessary to improve the machinability of difficult-to-cut materials such as hardened steel, nickel-based alloys, and titanium alloys as these materials offer superior properties such as chemical stability, corrosion resistance, and high strength to weight ratio, making them indispensable for many applications. Machining with self-propelled rotary tools (SPRT) is considered as one of the promising techniques used to provide proper tool life even under dry conditions. In this work, an attempt has been performed to analyze, model, and optimize the machining process of AISI 4140 hardened steel using self-propelled rotary tools. Experimental analysis has been offered to (a) compare the fixed and rotary tools performance, and (b) study the effect of the inclination angle on the surface quality and tool wear. Moreover, the current study implemented some artificial intelligence-based approaches (i.e., genetic programming and NSGA-II) to model and optimize the machining process of AISI 4140 hardened steel with self-propelled rotary tools. The feed rate, cutting velocity, and inclination angle are selected to be the design variables, while the tool wear, surface roughness, and material removal rate (MRR) are the studied outputs. Moreover, different weights have been assigned for the three studied outputs to offer different optimized solutions based on the designer interest (equal-weighted, finishing, and productivity scenarios). It should be stated that the findings of the current work offer valuable recommendations to select the optimized cutting conditions when machining hardened steel AISI 4140.

show abstract

Modeling and multi-response optimization of machining performance while turning hardened steel with self-propelled rotary tool

Cited by 27 publications

References 18 publications

Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

Towards Analysis and Optimization during Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

Contact Info

Product

Resources

About