This study proposes a novel approach to assess supplier disruption risks using a modified Pythagorean Fuzzy SWARA-TOPSIS method. The research identifies eight key risk factors for supplier disruptions, including insufficient production capacity, quality issues, significant price fluctuations, delivery delays, financial instability, changes in local government laws and regulations, technological changes or failures, and natural disasters and geopolitical risks. The study combines the Pythagorean Fuzzy Step-wise Weight Assessment Ratio Analysis (PF-SWARA) with the Pythagorean Fuzzy Technique for Order Preference by Similarity to Ideal Solution (PF-TOPSIS) to determine the importance weights of these risk factors and calculate the risk scores of suppliers. The findings indicate that "natural disasters and geopolitical risks," "financial instability," and "delivery delays" are the top three critical disruption risk factors. Suppliers facing higher disruption risks should focus on mitigating these three areas. The study provides targeted recommendations for suppliers with higher risk scores, offering practical solutions to reduce risks and improve supply chain resilience. The approach incorporates expert opinions and addresses uncertainties in the assessment environment, ensuring a robust and nuanced evaluation. The study also highlights the importance of supplier stability in maintaining the integrity and efficiency of the entire supply chain. The framework is applied to a multinational machine tool manufacturing company in Taiwan, aiming to systematize the process of assessing supplier disruption risks and provide reliable recommendations for supplier improvement. The study contributes to the field of supply chain management by introducing a comprehensive set of risk factors and a novel method for assessing supplier disruption risks. The approach enhances the traditional PF-SWARA-TOPSIS method by refining the ranking index based on the global risk range and incorporating the concept of aspiration level. The study addresses gaps in previous research by providing a comprehensive framework for supplier disruption risk factors and analyzing the importance of these risks using multiple-criteria decision-making tools. The study also considers expert importance and information fuzziness to ensure a robust and nuanced assessment. The results demonstrate the effectiveness of the modified PF-SWARA-TOPSIS approach in identifying and prioritizing suppliers with higher disruption risks, offering practical solutions for risk mitigation and supply chain resilience. The study concludes that the proposed approach is a significant advancement in the field of risk management in the machine tool manufacturing industry.This study proposes a novel approach to assess supplier disruption risks using a modified Pythagorean Fuzzy SWARA-TOPSIS method. The research identifies eight key risk factors for supplier disruptions, including insufficient production capacity, quality issues, significant price fluctuations, delivery delays, financial instability, changes in local government laws and regulations, technological changes or failures, and natural disasters and geopolitical risks. The study combines the Pythagorean Fuzzy Step-wise Weight Assessment Ratio Analysis (PF-SWARA) with the Pythagorean Fuzzy Technique for Order Preference by Similarity to Ideal Solution (PF-TOPSIS) to determine the importance weights of these risk factors and calculate the risk scores of suppliers. The findings indicate that "natural disasters and geopolitical risks," "financial instability," and "delivery delays" are the top three critical disruption risk factors. Suppliers facing higher disruption risks should focus on mitigating these three areas. The study provides targeted recommendations for suppliers with higher risk scores, offering practical solutions to reduce risks and improve supply chain resilience. The approach incorporates expert opinions and addresses uncertainties in the assessment environment, ensuring a robust and nuanced evaluation. The study also highlights the importance of supplier stability in maintaining the integrity and efficiency of the entire supply chain. The framework is applied to a multinational machine tool manufacturing company in Taiwan, aiming to systematize the process of assessing supplier disruption risks and provide reliable recommendations for supplier improvement. The study contributes to the field of supply chain management by introducing a comprehensive set of risk factors and a novel method for assessing supplier disruption risks. The approach enhances the traditional PF-SWARA-TOPSIS method by refining the ranking index based on the global risk range and incorporating the concept of aspiration level. The study addresses gaps in previous research by providing a comprehensive framework for supplier disruption risk factors and analyzing the importance of these risks using multiple-criteria decision-making tools. The study also considers expert importance and information fuzziness to ensure a robust and nuanced assessment. The results demonstrate the effectiveness of the modified PF-SWARA-TOPSIS approach in identifying and prioritizing suppliers with higher disruption risks, offering practical solutions for risk mitigation and supply chain resilience. The study concludes that the proposed approach is a significant advancement in the field of risk management in the machine tool manufacturing industry.