Multi-Objective Optimization for Turning Using MOORA and Novel CoCoSO Approach

In the modern manufacturing sector, producing precise components at a low cost is essential to meet the growing demands for quality, efficiency, and profitability. As the complexity of manufacturing processes increases, manufacturers face the challenge of optimizing multiple performance characteristics simultaneously. Achieving the right balance between machining parameters is critical for ensuring optimal product quality while minimizing operational costs. However, optimizing these multi-performance characteristics is often more challenging and time-consuming compared to optimizing single performance characteristics. To address these complexities, this study employs a robust and systematic approach using the Taguchi method with an L9 Orthogonal Array (OA) for experimental design. In addition to the Taguchi design of experiments, the study integrates two advanced Multi-Criteria Decision-Making (MCDM) methods namely Multi Objective Optimization based on Ratio Analysis (MOORA) and Combined Compromise Solution (CoCoSo) to evaluate and determine the optimal machining parameters. The MOORA method uses ratio analysis to handle multi-objective optimization, while CoCoSo evaluates alternatives based on a combination of cost and benefit criteria, ensuring that the most efficient and cost-effective solutions are identified.