Application of the Hybrid GRA-MARCOS Technique for Decision-Making in the Selection of Artificial Intelligence Technologies to Enhance Production and Management Efficiency in Industrial Plants
DOI:
https://doi.org/10.14456/jeit.2025.24Keywords:
Multi-Criteria Decision Making, Artificial Intelligence, Hybrid GRA-MARCOSAbstract
In an era where the industrial sector is faced with intense competition and rapid technological advancement, the strategic adoption of artificial intelligence (AI) technologies has become essential for enhancing production and management efficiency. However, selecting the most suitable AI technology tailored to the specific context of each organization remains a complex challenge due to the diversity of available options, each offering different capabilities and limitations. This study introduces the application of the Hybrid GRA-MARCOS technique, which integrates the strengths of Grey Relational Analysis (GRA) noted for its ability to handle incomplete and uncertain data with the MARCOS method, which ranks alternatives based on both ideal and anti-ideal solutions. This hybrid approach facilitates a systematic and transparent decision-making process for AI technology selection. The research employed expert input from 15 industrial engineers to evaluate 14 AI alternatives using 6 key criteria: accuracy, coding capability, system integration, processing speed, cost-effectiveness, and real-world reliability. The analysis revealed that Gemini (by Google) emerged as the most suitable alternative, followed by Microsoft Copilot, IBM Watsonx, and Grok. These results affirm the robustness of the Hybrid GRA-MARCOS method in supporting multi-criteria decision-making in complex industrial environments with high precision and credibility.
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เนื้อหาและข้อมูลในบทความที่ลงตีพิมพ์ในวารสารศูนย์ดัชนีการอ้างอิงวารสารไทย ถือเป็นข้อคิดเห็นและความรับผิดชอบของผู้เขียนบทความโดยตรงซึ่งกองบรรณาธิการวารสาร ไม่จำเป็นต้องเห็นด้วย หรือร่วมรับผิดชอบใด ๆ
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