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Sustainable machining practices: a comparative study of MQL and MQL with wheel cleaning jet applied to different abrasives

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With the increased use of polymeric products and, consequently, steel molds, the growth in grinding applications and the use of lubricoolant fluids is inevitable. As a result, studying different process configurations is of great interest to both the industry and society in general, by making it more economical and sustainable. This work focuses on evaluating the application of different lubricooling methods (conventional, MQL, and MQL + WCJ), cutting tools (green silicon carbide, black silicon carbide, and alumina), and cutting speeds (0.25 mm/min, 0.5 mm/min, and 0.75 mm/min) in the grinding of VP50IM. The goal is to identify the combination with the lowest cost and CO2 production, while assessing its performance through output parameters such as surface roughness, roundness error, G ratio, grinding power, cost analysis, and CO2 emission. Furthermore, SEM images were taken to analyze the machined surface of the workpiece. Based on this data, it was determined that the conventional method still achieved the highest machining efficiency, even though it was more expensive and more polluting. However, the MQL + WCJ technique significantly reduced costs, up to 45%, and CO2 emissions by 67.5%, even though it presented slightly lower performance compared to the conventional method. On the other hand, the MQL system obtained the worst results due to its deficiency in wheel cleaning and heat removal from the cutting zone. It was also observed that increasing the process speed reduces costs and gas emissions, but directly affects performance since machining intensity increases, resulting in lower quality. Finally, the tool with the best heat conduction capacity, green silicon carbide, led to the best process performance, while the alumina tool, with lower thermal conductivity, achieved the poorest results.

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International Journal of Advanced Manufacturing Technology, v. 132, n. 5-6, p. 2395-2409, 2024.

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