Enhancing Efficiency and Cost-Effectiveness: A Groundbreaking Bi-Algorithm MCDM Approach

Abstract

Numerous scholars have thoroughly studied the topic of choosing machines considering the progress and technological growth seen in machinery options. This scholarly investigation explores decision-making methods specifically designed to aid the selection of machines in manufacturing businesses. Additionally, this research emphasizes the need for decision-making frameworks in manufacturing facilities, highlighting the importance of smart machine selection strategies in those contexts. In this research, we show a dual-MCDM approach that includes DEX—decision experts—and the EDAS method that are popularly employed to solve decision-making problems in both academic and practical industries. Throughout the previous decade, business leaders and managers increasingly use MCDM solutions to overcome machine selection challenges. At this time, while various decision-support technologies and procedures have been developed and used, it is essential that we discuss the sequence of our study objectives and drive the proposed method for widening use in practical firms. In short, this research may be helpful as a literature review for MDCM studies and related topics. It will also help executives, engineers, and specialists determine which equipment or machines to create and increase product quality in manufacturing and industry.

Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering

“…This research takes a holistic approach that considers the interdependencies and dynamic interactions between AI factors, aiming to offer insights into using AI technologies strategically for cost optimization in civil engineering projects. This hybrid methodology helps bridge the gap between theoretical AI advancements and practical cost management in civil engineering [4]. The findings of this study could guide decision-makers, practitioners, and researchers, contributing to the advancement of cost management practices in civil engineering.…”

“…Yenugula et al [2] applied the Delphi technique to elicit expert judgments on multicriteria decision-making in the context of environmental management and discussed the integration of the Delphi method with an Analytic Hierarchy Process (AHP) for decisionmaking in complex systems. Wang et al [4] utilized the Delphi method to determine the weights for criteria in a fuzzy AHP framework for supplier selection and also evaluated the effectiveness of the Delphi method in achieving consensus among experts during decision-making processes within healthcare management. Abbasnejad et al [5] conducted a systematic review assessing the reliability and validity of the Delphi method in various fields, including business, healthcare, and education.…”

“…The hybrid MCDM concept, combining the Delphi method, ISM, and a MICMAC analysis, integrates diverse perspectives from experts, stakeholders, and decision-makers, ensuring a comprehensive approach to the various factors and relationships affecting the decision problem. The incorporation of fuzzy sets into the hybrid MCDM model addresses the uncertainties and ambiguities in decision-making [4], allowing for a qualitative assessment of the criteria and factors, even amid the imprecision in expert judgments and preferences. The Delphi method promotes consensus-building among experts through iterative feedback, enhancing the credibility of their decisions.…”

“…Combining multiple methodologies like Delphi, ISM, MICMAC, and fuzzy sets can be time-consuming and create a complex framework. Implementing this hybrid approach requires considerable expertise and resources, posing challenges for its users [4,5]. The reliance on expert judgments in Delphi and ISM can introduce subjectivity and bias into the decision-making process, leading to results influenced by individual opinions.…”

“…This research aims to advance MCDM knowledge and create innovative methodologies to tackle the real-world challenges in civil engineering. By integrating these MCDM tools, this study provides a structured framework to identify, evaluate, and prioritize the AI factors relevant to cost management in civil engineering [3,4]. This research takes a holistic approach that considers the interdependencies and dynamic interactions between AI factors, aiming to offer insights into using AI technologies strategically for cost optimization in civil engineering projects.…”