Selecting the Appropriate Machine Using the Entropy and Combined Compromise Solution Methods: An Application for A Steel-Fabrication Company

Laser cutting machines play a critical role in modern manufacturing processes because of their ability to provide highly precise cuts, speed, and flexibility. Particularly in industries such as metalworking, automotive, and aerospace, laser cutting machines can perform highly accurate cuts on complex geometric shapes with minimal errors. As such, laser machines enhance production efficiency by reducing material waste and labor costs when compared with those with compared to manual cutting techniques. The aim of the present study was to provide information to a steel-fabrication company that would aid in purchasing the most efficient and cost-effective laser plate-cutting machine. In complex decision-making processes such as machine selection, managers must consider numerous criteria; therefore, entropy and combined compromise solution (CoCoSo) methods were used to rank the most suitable machines for the company. The criteria were weighted using the entropy calculation method, with positioning accuracy identified as the most important criterion. The importance weights of the criteria are calculated using the Entropy method, and positioning accuracy is identified as the most important criterion. These weighted criteria were then used in the CoCoSo method to establish the machine rankings. Based on the final ranking, machine 2 was identified as the most suitable option and was recommended to company management.