Optimization of Dry Turning Parameters for C45 Steel Using Simple Additive Weighting Method

In the manufacturing industry, optimizing machining parameters is crucial for enhancing both the quality and efficiency of the production process. This study focuses on the dry turning of C45 steel, a commonly used medium carbon steel known for its good machinability and stable mechanical properties. The objective is to minimize surface roughness (Rt) and maximize the material removal rate (MRR) by identifying the optimal machining parameters: cutting speed (Vc), feed rate (fz), and depth of cut (ap). An experimental factorial design was employed to systematically vary the machining parameters and collect data on the resulting surface roughness and material removal rates. The Simple Additive Weighting (SAW) method, a Multi-Criteria Decision Making (MCDM) technique, was utilized to evaluate and rank the different machining conditions. The SAW method involves normalizing the decision matrix, applying weights to each criterion, and calculating composite scores for each alternative to determine the optimal set of parameters. The SAW optimization process, implemented using Python, utilized powerful libraries such as pandas for data manipulation, numpy for numerical operations, and openpyxl for writing results to an Excel file. The results indicate that the optimal machining parameters are a cutting speed of 240 m/min, a feed rate of 0.30 mm/tooth, and a depth of cut of 0.30 mm under dry conditions. These parameters provide a balanced trade-off between achieving low surface roughness and high material removal rate. This study demonstrates the effectiveness of the SAW method in managing trade-offs between competing objectives and highlights its applicability in real-world manufacturing environments. Future work could expand on this approach by considering additional machining conditions and integrating other MCDM methods to further enhance optimization outcomes. The findings provide valuable insights for manufacturers seeking to improve both the quality and efficiency of their machining processes