A Multi-Criteria Decision-Making Framework to Evaluate the Impact of Industry 5.0 Technologies: Case Study, Lessons Learned, Challenges and Future Directions
本研究运用混合多准则决策方法，在不确定环境下评估工业5.0技术在医疗领域的优势，发现人工智能和云计算最具影响力，而纳米技术、无人机和机器人排名靠后。
Abstract Smart technologies have demonstrated striking outcomes regarding the early diagnosis of diseases and the delivery of the necessary healthcare in the last decade. However, by emphasizing the core fundamentals of social justice and sustainability, together with digitalization and smart technologies that predicate raising productivity and flexibility, Industry 5.0 has proven to achieve more efficient results. Industry 5.0 technologies provide more intelligent ways for human employees and higher efficiency development while also improving safety and performance in many applications. In this research, the contribution is focused on the healthcare and how Industry 5.0 technologies demonstrate several advantages for the healthcare sector, starting with automated and precise disease prediction, moving on to aiding medical personnel in continual surveillance and monitoring and concluding with successful digital automation of smart equipment. The objective of this study is to apply a hybrid multi-criteria decision-making approach under a neutrosophic environment to evaluate the advantages of industry 5.0 technologies in the healthcare sector. Industry 5.0 primary value is to reach human-centric, sustainable, and resilient industries. While Industry 5.0 technologies sub-values regarding the healthcare sector are determined and distinguished according to the 3-main values mentioned previously based on literature. The methodologies applied in this study are: The Analytical Hierarchy approach (AHP) evaluates the main values and sub-values. Subsequently, the effectiveness of industry 5.0 technologies according to their values to the healthcare sector are ranked by Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The approach is constructed under uncertainty based on a neutrosophic environment to achieve accuracy in the evaluation process. The results show that the most influential technology in healthcare are AI and cloud computing, while nano-technology, drone technology, and robots are at the end of the ranking. While validating the suggested technique, outcome comparisons were carried out to demonstrate the benefits of the methodologies. A sensitivity study indicates that adjusting the weightings of the sub-values has no significant effect on the ranking of technologies.