# Enhancing Efficiency and Cost-Effectiveness: A Groundbreaking Bi-Algorithm MCDM Approach +
## 1 Introduction  
The field of manufacturing is vast and encompasses intricate products like automobiles, ships, boats, drafts, bearings and milling machines. It requires a deal of precision and expertise. Professionals from various domains have meticulously studied this landscape, contributing their valuable insights to decision-making methodologies. We are grateful for the technology and software that have ushered in a new era in machining products by combining scientific advancements with technological prowess. These innovative tools play a role in improving design precision, evaluative abilities, compliance and construction oversight. Every aspect of their development, production and implementation is carefully planned to generate value. One essential component in manufacturing plants is the welding machine that serves as the linchpin for factory processes. Take shipbuilding as an example--a domain where customized prototypes are created with attention to detail and incorporating technological advancements. The process of building a vessel can take from 24 to 36 months and requires collaboration among hundreds or even thousands of skilled professionals, from various disciplines. European shipyards are known for their standards in terms of quality, adherence to health and safety protocols and rigorous regulatory requirements. The safety and seaworthiness of each vessel greatly depend on the expertise and professionalism of the teams involved in its construction. With the advancement of production methods, automation has become a feature in parts of the process led by skilled individuals proficient in specialized technologies and tools. Companies have successfully integrated paradigms and techniques into their workshops to enhance competitiveness and maintain global leadership in key industries. Real-life problems involve several parameters and trade-offs, all of which must be considered during decision making. As a result, this kind of decision making [1; 2; 3; 4; 5; 6] is known as multicriteria decision making (MCDM), and it can be broken down into a variety of subcategories, including comparative/relative measurement methods, reference point methods, outranking methods and other methods (such as supremacy, max-min and min-max). The analytical hierarchical process, or AHP [5; 7; 8; 9; 10], is a relative measurement technique that can evaluate several options by considering qualitative and quantitative criteria. MCDM divides problems into components. Once decisions are made regarding these parts, they are reassembled to reveal the picture of decision making. The criteria values can be either ordinal or cardinal. The information can be precise or somewhat ambiguous [10; 11; 12], decided in periods. In today's world, the rise of multicriteria decision making methodologies has greatly empowered decision makers to tackle the complexities mentioned earlier. However, the challenge lies in choosing the aggregation method within the MCDM framework. In this context, the variety of options available poses a task requiring consideration by multiple criteria decision makers. Multicriteria decision making has seen growth in several fields in recent years. This progress encompasses three aspects: models that incorporate complex algorithms, procedural frameworks and selection paradigms; evaluation theories that establish assumptions about values or preferences supported by well-structured representations; and assessment methodologies covering various aspects such as elicitation, estimation and scaling of individual choices, utilities and subjective probabilities within multicriteria decision-making scenarios. The practical application has been vital for adopting techniques, particularly in manufacturing. In this domain, decision makers face the task of selecting choices from a range of attribute-defined options. This approach brings together the foundations of MCDM with the demands of manufacturing environments. A wide range of decision-making techniques and approaches have developed over the years.