Machining parameter optimization in turning process for sustainable manufacturing

Dambhare, Sunil; Deshmukh, Suraj; Borade, A. B.

doi:10.5267/j.ijiec.2015.3.002

Cited by 8 publications

(5 citation statements)

References 16 publications

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“…Although this is not the smallest value of surface roughness, it is still relatively small, ranked tenth out of twenty-seven trials (higher than trial No.1, No. 10,No.11,No.12,No.19,No.20,No.21,No.24 and No.25). It can be said that considering purpose of determining the value of the input parameters for achieving the "minimum" surface roughness and the "maximum" MRR, test No.9 is "the best".…”

Section: Resultsmentioning

confidence: 97%

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Multi-Objective Optimization in Turning Process Using RIM Method

Nguyen¹,

Vo²

2022

Applied Engineering Letters

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In all machining methods, surface roughness greatly influences the working ability and the life of parts. Besides, material removal rate (MRR) is the parameter that reflects machining productivity. Low surface roughness and high MRR values are ideal for most of the methods. This article presents a research on multi-objective optimization of turning process. The material used in the experiments is SCM440steel. And Taguchi method is applied to design an orthogonal array (L27), in which five parameters are selected as the input of testing process including cutting tool material, tool nose radius, spindle speed, feed rate and depth of cut. In addition, Reference Ideal Method (RIM) is applied to identify the value of the input parameters to achieve the minimum surface roughness and the maximum MRR. Accordingly, in order to obtain the maximum MRR and the minimum surface roughness at the same time, it is necessary to use TiN coated cutting tool, with the tool nose radius of 0.6 mm, the cutting speed of 94.25 m/min, the feed rate of 0.16 mm/rev, and the depth of cut of 0.5 mm. Impact of input parameters on output parameters is also analyzed in this study.

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Section: Resultsmentioning

confidence: 97%

“…Several researchers optimized the AISI 1040 steel turning process [10]. In their study, three cutting tools including Brazed tip, TiN coated insert and TiAlN coated insert were used in three cutting environment including dry, MQL and wet.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization in Turning Process Using RIM Method

Nguyen¹,

Vo²

2022

Applied Engineering Letters

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“…The experiment was carried out to optimize the cutting factors while machining AISI 1040 carbon steel with CNMG 12012 TF aluminum tungsten nitride coated insert and CNMG 120412 MP tungsten nitride coated insert for different machining parameters. The results obtained from this study suggested that the machining condition and cutting insert type influenced the power consumption while machining AISI 1040 [5].…”

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confidence: 82%

Evaluation and Performance Improvement of Environmentally Friendly Sustainable Turning of 6063 Aluminum Alloy in Dry Conditions Using Grey Relational Analysis

Kannan,

N.M.Sivaram

2024

Int. J. Automot. Mech. Eng.

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Sustainable machining has gained importance in recent years due to its environmental, economic, and societal implications. Aluminium (Al) 6063 alloy involves turning operation to make it suitable for various applications. The work's novelty is assessing the machining characteristics along with sustainability indicators. This study aims to find the best-turning parameters for machining Al 6063 alloy. The turning parameters considered were cutting speed, feed rate, and depth of cut. A cutting speed of 200 m/min, feed rate of 0.05 mm/rev, and depth of cut of 0.25 mm were the best parameter combinations for achieving a good machining response. From the response value of mean grey relational grade (GRG) and analysis of variance (ANOVA), the depth of cut ranks one with 34.38%, which is the most dominating parameter in achieving the sustainable machining of Al 6063 alloy. Through grey relational analysis, optimized machining parameters resulted in a 72.84 percent reduction in carbon emissions, 72.82 percent reduction in energy consumption, 18.58 percent reduction in cutting power, and 6.83 percent reduction in surface roughness considering the initial parameter settings and best machining parameters. The enhancement in total GRG was 0.1702, indicating improvement in the desired responses. As a result of this study, it is clear that appropriate machining parameter selection aids sustainable machining of Al 6063 alloy.

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“…Minimum quantity lubrication (MQL) technology improves overall machining performance in terms of cutting fluid consumption [ 188 ]. The cutting environment is an important parameter for energy consumption compared to others, as pump power in wet conditions and compressor power in MQL conditions are added for measuring the total energy [ 186 ]. To achieve environmentally friendly manufacturing, dry cutting is highly recommended [ 62 ].…”

Section: Optimization With Cooling/lubrication Techniques For Energy ...mentioning

confidence: 99%

Optimization techniques for energy efficiency in machining processes—a review

abdelaoui

Jabri

Barkany

2023

Int J Adv Manuf Technol

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Metal working process is one of the main activities in mechanical manufacturing industry; it is considered as a major consumer of energy and natural resources. In material removal process, the selection of cutting parameters and cooling or cutting liquid is necessary to save energy and achieve energy efficiency as well as sustainability. During the last two decades, the number of publications in this field has rapidly increased and has shown the importance of this research area. This review paper identifies and reviews in detail a total of 166 scientific studies which exhibit original contributions to the field and address multiple energy efficiency challenges. The recently developed models of energy consumption and different materials used in the machining process are presented. Therefore, this study describes various techniques for modeling and optimizing machining operations such as turning, milling, and drilling. Modeling techniques, experimental methods, multi-objective and single-objective optimization methods, and hybrid techniques optimization are presented in a detailed manner compared to previous review papers where only energy models are discussed. It can help practitioners and researchers to select the most appropriate approach for the desired experience and to highlight the progress of these methods in terms of machining energy efficiency. Additionally, this paper provides a review of different cutting fluids adopted in machining processes. This paper assists researchers and manufacturers in making advantageous technical decisions that have substantial economics in terms of energy saving.

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Machining parameter optimization in turning process for sustainable manufacturing

Cited by 8 publications

References 16 publications

Multi-Objective Optimization in Turning Process Using RIM Method

Multi-Objective Optimization in Turning Process Using RIM Method

Evaluation and Performance Improvement of Environmentally Friendly Sustainable Turning of 6063 Aluminum Alloy in Dry Conditions Using Grey Relational Analysis

Optimization techniques for energy efficiency in machining processes—a review

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