Enhancing energy efficiency in turning operations by optimizing cutting parameters

Improving energy and resource efficiency is becoming increasingly important in the absence of a typical industrial environment, mainly because of the expansion of global population and industrial demands. This research explores ways to improve the energy efficiency of CNC machines by optimizing key cutting parameters. The objective is to simultaneously reduce the energy consumption and increase the material removal rate (MRR) by adjusting the cutting speed, rate of progress, and depth of cut. Experiments were conducted using aluminum alloy as the material and the response surface method (RSM) to show the relationship between the cutting parameters and process results. Analysis of variance was used to assess the importance of each parameter, while the Artificial Bee Colony (ABC) algorithm was used to find the most efficient parameter configuration. The results indicated that the ideal result of reducing SCE without increasing MRR occurred at a cutting speed of 280 m/min, cutting depth of 4 mm, and feed rate of 1.6 mm/rev. The research findings suggest that adjusting cutting parameters can notably reduce energy usage and enhance machining productivity, thereby providing a sustainable manufacturing method.

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Publication Details

Journal
Journal of Statistics and Management Systems
Published
2025-01-01
DOI
https://doi.org/10.47974/jsms-1460
Primary Topic
Engineering Technology and Methodologies
Type
article
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article

Enhancing energy efficiency in turning operations by optimizing cutting parameters

Sandeep Pimpalgaonkar, Shashank B. Thakre, Chandrashekhar Meshram, Vishesh P. Gaikwad et al.
Journal of Statistics and Management Systems
Engineering Technology and Methodologies
article

Enhancing energy efficiency in turning operations by optimizing cutting parameters

Sandeep Pimpalgaonkar, Shashank B. Thakre, Chandrashekhar Meshram, Vishesh P. Gaikwad, Subhash Khatarkar
article en

Abstract

Improving energy and resource efficiency is becoming increasingly important in the absence of a typical industrial environment, mainly because of the expansion of global population and industrial demands. This research explores ways to improve the energy efficiency of CNC machines by optimizing key cutting parameters. The objective is to simultaneously reduce the energy consumption and increase the material removal rate (MRR) by adjusting the cutting speed, rate of progress, and depth of cut. Experiments were conducted using aluminum alloy as the material and the response surface method (RSM) to show the relationship between the cutting parameters and process results. Analysis of variance was used to assess the importance of each parameter, while the Artificial Bee Colony (ABC) algorithm was used to find the most efficient parameter configuration. The results indicated that the ideal result of reducing SCE without increasing MRR occurred at a cutting speed of 280 m/min, cutting depth of 4 mm, and feed rate of 1.6 mm/rev. The research findings suggest that adjusting cutting parameters can notably reduce energy usage and enhance machining productivity, thereby providing a sustainable manufacturing method.

Journal of Statistics and Management SystemsVol. 28(5)
Openalex Percentile: Top 75%
Engineering Technology and Methodologies
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