International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 06 | Jun 2025
p-ISSN: 2395-0072
www.irjet.net
Optimising nose radius and feed rate in the milling of gray cast iron to minimise machining time and reduce surface roughness Sandeep Chowdhry1 1 Engineering Consultancy & Training, Chandigarh, India
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Abstract - Gray cast iron dampen vibrations and has
periodically measured with a roughness tester. Once measuring data is out of standard, all the products between the last two testing periods need to be inspected. Repairing failed products leads to additional costs. Therefore, online monitoring of surface roughness during production has attracted much attention. Surface roughness monitoring has become a potential objective in a smart manufacturing or Industry 4.0 environment [6]. Cutting and machining costs for castings are frequently more than the casting cost. Therefore, a significant challenge in the cutting and machining cast iron materials is to minimise the manufacturing costs and increase production efficiency without affecting engineered parts’ quality or the high-strength properties [7]. It is evident from the literature that optimisation techniques are needed to ensure a practical selection of cutting parameters to achieve a balance between machining efficiency and surface quality. However, whether there is a linear or non-linear relationship between the cutting parameters, such as feed rate, cutting speed, and machining time, is unclear. For instance, full factorial design (FFD) was used to study the effect of milling cutting parameters and lubrication on the machinability characteristics of mold steel [8]. In contrast, the response surface method (RSM) was used to differentiate the cutting conditions and analyse the process parameter influence on surface roughness [9].
high thermal conductivity, making it an excellent choice for housing or industrial applications such as machinery bases. However, the machining cost of the GCI workpiece can be more than the casting cost. This study aims to use the appropriate optimisation method to select values for feed rate, spindle speed and nose radius to minimise the machining time and reduce the surface roughness of the machined GCI workpiece. The results show that the response surface method is an appropriate optimisation method. An increase in feed rate contributes more compared to an increase in the spindle speed, to the reduction in machining time. The increase in feed rate leads to a rise in surface roughness. At the same time, an increase in nose radius leads to a decrease in surface roughness. The results show that response surface method should be used for optimisation. Increase in feed rate contributes more compared to increase in the spindle speed to the reduction in machining time. The increase in feed rate leads to increase in the surface roughness. Whereas, increase in nose radius leads to decrease in surface roughness.
Key Words: milling, full factorial design, response surface method, solidworks cam, gray cast iron 1. INTRODUCTION Cast iron offers a competitive strength-to-cost ratio, good cast-ability, and high machinability; thus, it is widely used in industry [1]. Gray cast iron (GCI) has a graphitic microstructure. The size and shape of the graphite flakes control its mechanical properties. It also has a high ability to dampen vibrations [2]. Gray cast iron has good strength, wear resistance, vibration damping, excellent casting performance, and low manufacturing costs [3]; as a result, it is currently the most used material for cast iron parts. Based on the Modern Casting Census reported at the end of 2018 [4], the most produced type of cast metal is GCI, which covers about 44.6% of the total world casting production. The world output of GCI parts reached 49.53 million tons in 2019, accounting for approximately 46.9% of the world output of castings. These parts are used in many fields [5], such as the beds of industrial instruments, bearing housings, end caps, and the automotive industry.
Therefore, the main aim of the study is 1) To select the optimisation method by determining whether there is a linear or non-linear relationship between the input milling cutting parameters, such as cutting speed and feed rate, and the response variable machining time; 2) To optimise the spindle speed and feed rate to minimise the machining time of GCI workpiece; 3) To optimise the feed rate and nose radius of the insert to minimise the surface roughness. This study aims to contribute to adopting an appropriate optimisation method to select the cutting parameter values to minimise the machining time and reduce the surface roughness of the machined GCI workpiece.
2 METHODOLOGY 2.1 Material
Surface roughness is vital in evaluating machining quality. The surface roughness will determine a product's fatigue strength, tribological property, corrosion resistance, and aesthetic requirement. In industry, surface roughness is
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A specimen of GCI material with dimensions of 100 mm x 100 mm x 10 mm and a contour of 50 mm x 50 mm x 4 mm, as shown in Fig. 1, was used for milling machining.
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