Understanding the role of multi-agent technology on quality of manufacturing organizations: A hybrid MCDM analysis

Maintaining quality in the manufacturing system has become a critical challenge in today’s rapidly evolving technological landscape. To overcome this, current research examines the role of Multi-Agent Technology (MAT) in improving the quality of manufacturing processes. For this, a conceptual framework consisting of eight factors and thirty-seven variables of MAT, identified from the literature, was analyzed using the Analytical Hierarchical Process (AHP), Sensitivity Analysis, Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). AHP findings revealed ‘Production Planning’ as the highest-priority factor, followed by ‘Process Monitoring, Control, and Data Acquisition.’ DEMATEL established the interrelationships among variables, ensuring a collaborative approach to maintaining quality. Sensitivity analysis and TOPSIS validated the AHP results for consistency and robustness. The findings also indicated that Virtual Manufacturing, Distributed Digital Manufacturing, and Adaptive Agent-Based Architecture were the globally top ranked variables in the framework that help to ensure the quality of manufacturing processes. These findings contribute to developing autonomous, high-precision manufacturing systems for long-term competitiveness and quality assurance. This study provides valuable insights for researchers and managers, demonstrating that MAT and its parameters can be customized to optimize manufacturing quality. • A conceptual framework of variables of multi-agent technology is proposed for increasing the quality of manufacturing processes. • To measure the effectiveness of the variables , a novel methodology integrated with AHP, Sensitivity analysis, DEMATEL, and TOPSIS is proposed. • As per the outcomes, the practical and theoretical implications of multi-agent variables are proposed to increase the awareness among the managers, researchers, and others. • A higher accuracy can be achieved while properly implementing multi-agent technology in the manufacturing industry.