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<p>The research paper presents a superior decision-making model for managing uncertainty, risk, and various operational needs for autonomous manufacturing systems in Industry 5.0. It is a three-way decision (3-WD) model constructed on the basis of Fermatean fuzzy numbers (FFNs) that is built through a combination of probability-based loss functions and grey relational analysis (GRA) method. The suggested model helps optimize real-time predictive maintenance planning and reduce production risks in intelligent manufacturing environments. To confirm its efficacy, a thorough comparative study is conducted against a range of existing decision-making methods using a case study of autonomous manufacturing system selection for an automotive production line. The findings indicate that the suggested Fermatean fuzzy three-way decision (FF-3WD) model produces identical optimal alternatives when measured by various evaluation metrics and better results when tested using a similarity measure. Decision thresholds and loss parameters are analyzed through sensitivity analysis to determine the stability and strength of the model. The results suggest that ranking outcomes are consistent across parameters, proving the effectiveness of the suggested framework. The framework offers effective decision support for complex and high-risk manufacturing processes and helps build resilient and sustainable smart manufacturing systems.</p>

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Robust hybrid analytical three-way decision paradigms for conflict resolution in manufacturing systems: integrating fermatean fuzzy logic and risk assessment mechanisms

  • 期刊论文

  • 发表日期：

    2026年7月24日

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  • Muhammad Tahir,
  • Sami Ullah Khan

摘要

The research paper presents a superior decision-making model for managing uncertainty, risk, and various operational needs for autonomous manufacturing systems in Industry 5.0. It is a three-way decision (3-WD) model constructed on the basis of Fermatean fuzzy numbers (FFNs) that is built through a combination of probability-based loss functions and grey relational analysis (GRA) method. The suggested model helps optimize real-time predictive maintenance planning and reduce production risks in intelligent manufacturing environments. To confirm its efficacy, a thorough comparative study is conducted against a range of existing decision-making methods using a case study of autonomous manufacturing system selection for an automotive production line. The findings indicate that the suggested Fermatean fuzzy three-way decision (FF-3WD) model produces identical optimal alternatives when measured by various evaluation metrics and better results when tested using a similarity measure. Decision thresholds and loss parameters are analyzed through sensitivity analysis to determine the stability and strength of the model. The results suggest that ranking outcomes are consistent across parameters, proving the effectiveness of the suggested framework. The framework offers effective decision support for complex and high-risk manufacturing processes and helps build resilient and sustainable smart manufacturing systems.