Knowledge Based Expert System Approach To Optimize Innovation And Technology In Industry 5.0

Abstrak

The rapid development towards the Industry 5.0 era demands closer integration between artificial intelligence and human expertise in driving innovation and sustainable technology implementation. This research aims to examine and develop a knowledge-based expert system approach as a strategic solution in optimizing the process of innovation and technological transformation in the industrial sector. By adopting a qualitative research method and a system design approach, this study designed a prototype expert system capable of representing expert knowledge in the field of industrial technology and digital innovation, and integrating it in complex decision-making processes. Data was obtained through a literature study, in-depth interviews with industry experts, and analysis of system requirements in the smart manufacturing sector. The results show that knowledge-based expert systems can improve decision-making efficiency, accelerate the adoption of new technologies, and support the human-machine collaboration that is a key characteristic of Industry 5.0. In addition, the system proved to be adaptive to the fast-changing dynamics of the industry and was able to provide precise recommendations based on historical cases and knowledge. These findings make a significant contribution to the development of expert system models in the context of industrial digital transformation, while opening up opportunities for wider application in various sectors. Thus, the knowledge-based expert system approach is a relevant solution to answer the challenges of sustainable innovation and increasing industrial competitiveness in the Industry 5.0 era.