This study’s objective is to review the literature on the environmental impact of the additive manufacturing process. When this new manufacturing technology is employed, it aims to create a healthy environment free of pollutants. The work is motivated by the lack of universal guidelines on new design approaches, the classification of manufacturing materials, and processes that address environmental concerns. Using additive manufacturing over traditional subtractive technologies may result in considerable material and energy resource savings, especially if the component is appropriately designed for manufacture. In this scenario, additive manufacturing, regarded as a potential breakthrough innovation, has grown in popularity in producing parts with complex geometry. AM encourages constant product development and flexible modifications that enable stakeholders to create better products faster. This study examines the state-of-the-art essentials of the fast-expanding manufacturing technique known as additive manufacturing (or 3D printing) and compares the environmental impact caused due to environmental issues. With increasing pressure on firms to provide transparency in their product sourcing and manufacturing processes, sustainability is no longer a distant goal but a strategic requirement. Manufacturers must also pay particular attention to their products’ total energy usage and overall environmental impact.

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Because aluminium is a lightweight and low-density material, its alloys, such as Al 6061 alloy, are extensively used in numerous automobile, defense, and aviation components. This study aims to develop a predictive model to investigate the impact of tool nose radius on the CNC turning process of Al 6061 alloy and better recognize the implications of operating machining considering cutting speed, rate of feed, cutting depth, and tool nose radius. The trials were carried out by using the response surface methodology (RSM), with an Al2O3 coated carbide tool as the cutter and an Al 6061 workpiece as the material. A mathematical model of the second-order was created. The analysis of variance (ANOVA) approach was used to analyze the performance characteristics of the turning operation. Individual desirability values from the desirability function analysis for the multi-responses are used to construct a composite desirability value. The ideal parameter levels were determined by using the composite desirability value, and the significant impact of parameters was assessed by using the analysis of variance. The minimum temperature attained at the machining parameters are 98.0 m/min cutting speed, 0.26 mm/rev rate of feed, 0.893 mm cutting depth, and 0.84 mm tool nose radius. The best total desirability value is 23.615 °C, indicating that the experimental results are close to the predicted values.

Aluminum alloy is the second most abundant metal on Earth, known for its wide range of utilization in commercial goods due to its heat capacity and tensile strength. This study examines the effect of nose radius on the turning process. Further, it explores the implications of cutting parameters such as the cutting speed, the rate of feed, the cutting depth, and the nose radius of the tool. The trials were carried out with an Al 6061 workpiece and an Al2O3-coated carbide tool as the cutter, utilizing the response surface methodology. A mathematical model was developed to investigate the performance characteristics of the turning operation using the analysis of variance method. The multi-response desirability function analysis combines individual desirability values to create a composite desirability value. The ideal parameter levels were determined using the composite desirability value, and the significant influence of parameters was assessed. The obtained optimum surface roughness and temperature parameters are at a cutting speed of 116.37 m/min, a rate of feed of 0.408 mm/rev, a cutting depth of 0.538 mm, and a tool nose radius of 0.20 mm. The related ideal surface roughness and temperature values are 0.374 µm and 27.439 °C. The optimal overall desirability value is 0.829, close to the target response.

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