Optimization of material removal rate in the CNC milling of polypropylene + 60 wt% quarry dust composites using the Taguchi technique

Shagwira, Harrison; Mbuya, Thomas Ochuku; Akinlabi, Esther Titilayo; Mwema, Fredrick Madaraka; B, Tanya

doi:10.1016/j.matpr.2020.11.229

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…The optimal response combination is obtained from a high feed rate and depth of cut. Like the research results of VISWANATHAN, et al [24] , SHAGWIRA, et al [25] , and LU, et al [26] also used a high feed rate and high depth of cut to provide an optimal response, namely the material removal rate.…”

Section: S/n Ratio (Taguchi)mentioning

confidence: 91%

Integration of Taguchi and Promethee for CNC Milling Machining Parameter Optimization on Aa6061

Ihsan,

Sumantri,

Irawan

2024

MECHTA

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In the manufacturing industry, machining has developed quite rapidly from the use of conventional machines to unconventional machines. Unconventional machines that are often used today are optimize computer numerically controlled (CNC), the use of CNC in the manufacturing industry provides many benefits in product quality and productivity. One of them is CNC milling, this type is one of the main machines on the production floor. Machining optimization becomes the main goal to achieve the ideal response in order to produce products with good and consistent quality and productivity. Surface quality leads to surface roughness, while productivity leads to material removal rate. This study aims to optimize CNC milling machining parameters on AA6061 with Taguchi experimental design and preference ranking organization method for enrichment evaluation (PROMETHEE) method. Machining was controlled using wet machining conditions to maintain temperature during machining. Experiments were conducted nine times with three factors and levels. These factors included spindle speed, feed rate, and depth of cut. The result of this research is the ideal value of the combination of surface roughness and material burning rate which is 0.565 (experiment 3). This best experiment is influenced by spindle speed 2600 rpm, feed rate 65 mm/min, and depth of cut 2.5 mm. Feed rate has the largest contribution in influencing the response which is 43.23%, followed by depth of cut 25.24%, and spindle speed 15.91%.

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Section: S/n Ratio (Taguchi)mentioning

confidence: 91%

Integration of Taguchi and Promethee for CNC Milling Machining Parameter Optimization on Aa6061

Ihsan,

Sumantri,

Irawan

2024

MECHTA

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“…The research paper [28] was dedicated to optimize the input parameters for computer numerical controlled milling of a polypropylene + 60 wt% quarry dust composite. The primary focus was to enhance the efficiency and profitability through the evaluation of the material removal rate.…”

Section: Introductionmentioning

confidence: 99%

Multi-Response Optimization Analysis of the Milling Process of Asphalt Layer Based on the Numerical Evaluation of Cutting Regime Parameters

et al. 2023

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The present study aimed to optimize the process parameters (milling depth and advanced speed) for an asphalt milling operation using a multi-response approach based on Taguchi design of experiments (DOE) and Grey Relational Analysis (GRA). Nine simulations tests were conducted using Discrete Element Method (DEM) in order to determine the forces acting on the cutting tooth support and tip. The considered performance characteristics were cutting forces (smaller is better category) and chip section area (larger is better category). A Grey Relational Grade (GRG) was determined from GRA, allowing to identify the optimal parameter levels for the asphalt milling process with multiple performance characteristics. It was found that that the optimal milling parameters for multi-response analysis are a milling depth of 200 mm and an advanced speed of 30 mm/min. Furthermore, analysis of variance (ANOVA) was used to determine the most significant factor influencing the performance characteristics. The analysis results revealed that the dominant factor affecting the resultant cutting force was milling depth, while the main factor affecting chip section area was the advanced speed. Optimizing milling efficiency is essential in machining operations. A key factor in this direction is comprehending the interplay between chip removal and cutting forces. This understanding is fundamental for achieving increased productivity, cost-effectiveness, and extended tool lifespan during the milling process.

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“…This has warranted research and experimental studies to determine the optimal parameters for machining different materials to reduce the chance occurrences and minimize impacts of external factors. Such studies include that conducted by Shagwira et al (2020), who concluded that the optimal parameters for the highest MRR were 600 rpm for cutting speed, 200 mm/min for feed rate, and 0.8 mm for depth of cut in the milling of polypropylene + 60 wt% quarry dust composite. The feed rate was the most significant factor towards the material removal rate.…”

Section: Introductionmentioning

confidence: 99%

CNC Milling of Medical-Grade PMMA

Wambua

Mwema

Buddi³

et al. 2022

International Journal of Manufacturing, Materials, and Mechanical Engineering

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This study evaluates CNC milling parameters (spindle speed, depth of cut, and feed rate) on medical-grade PMMA. A single objective analysis conducted showed that the optimal material removal rate (MRR) occurs at a spindle speed of 1250 rpm, a depth of cut of 1.2 mm, and a feed rate of 350 mm/min. The ANOVA showed that feed rate is the most significant factor towards the MRR, and spindle speed (11.83%) is the least contributing. The optimal surface roughness (Ra) occurred at spindle speed of 500 rpm, depth of cut of 1.2 mm, and feed rate of 200 mm/min. The milling factors were insignificant. A regression analysis for prediction was also conducted. Further, a multi-objective optimization was conducted using the Grey Relational Analysis. It showed that the best trade-off between the MRR and the Ra could be obtained from a combination of 1250 rpm (spindle speed), 1.2 mm (depth of cut), and 350 mm/min (feed rate). The depth of cut was the largest contributor towards the grey relational grade (54.48%), followed by the feed rate (10.36%), and finally, the spindle speed (4.28%).

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Optimization of material removal rate in the CNC milling of polypropylene + 60 wt% quarry dust composites using the Taguchi technique

Cited by 8 publications

References 8 publications

Integration of Taguchi and Promethee for CNC Milling Machining Parameter Optimization on Aa6061

Integration of Taguchi and Promethee for CNC Milling Machining Parameter Optimization on Aa6061

Multi-Response Optimization Analysis of the Milling Process of Asphalt Layer Based on the Numerical Evaluation of Cutting Regime Parameters

CNC Milling of Medical-Grade PMMA

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Optimization of material removal rate in the CNC milling of polypropylene + 60 wt% quarry dust composites using the Taguchi technique

Cited by 8 publications

References 8 publications

Integration of Taguchi and Promethee for CNC Milling Machining Parameter Optimization on Aa6061

Integration of Taguchi and Promethee for CNC Milling Machining Parameter Optimization on Aa6061

Multi-Response Optimization Analysis of the Milling Process of Asphalt Layer Based on the Numerical Evaluation of Cutting Regime Parameters

CNC Milling of Medical-Grade PMMA

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Product

Resources

About

Optimization of material removal rate in the CNC milling of polypropylene + 60 wt% quarry dust composites using the Taguchi technique