Fine-tuned tuna swarm optimization for enhanced multi-pass turning performance

Even with advances in machining optimization approaches, the complexity of multi-pass turning tasks is too much for current approaches to handling. This is because current techniques are not able to fine-tune or change dynamically to achieve the best possible results. A novel Fine-Tuned Tuna Swarm Optimisation (FTSO) is presented in this study for a specialized optimization method. FTSO actively modifies its parameters to optimize toolpath preparation, tool decision-making and cutting specifications in an effort to enhance turning performance generally. It is motivated by the group behavior of tuna swarms. To achieve improved multi-pass turning performance, the suggested FTSO technique offers a reliable and effective solution that adjusts to the ever-evolving machining situations. The FTSO method is set into practice and verified using machining trials and Matlab tools. The effectiveness of FTSO in enhancing cutting parameters is demonstrated by the results, which surpass those of conventional optimization techniques and offer significant perspectives for augmenting the productivity and caliber of multi-pass turning operations. In order to achieve improved multi-pass turning efficiency, the suggested FTSO methodology offers a reliable and effective solution that adjusts to the ever-evolving character of machining surroundings.