Semantic TRIZ feasibility in technology development, innovation, and production: A systematic review

Autor: Mostafa Ghane, Mei Choo Ang, Denis Cavallucci, Rabiah Abdul Kadir, Kok Weng Ng, Shahryar Sorooshian
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Heliyon, Vol 10, Iss 1, Pp e23775- (2024)
Druh dokumentu: article
ISSN: 2405-8440
DOI: 10.1016/j.heliyon.2023.e23775
Popis: The study unfolds with an acknowledgment of the extensive exploration of TRIZ components, spanning a solid philosophy, quantitative and inductive methods, and practical tools, over the years. While the adoption of Semantic TRIZ (S-TRIZ) in high-tech industries for system development, innovation, and production has increased, the application of AI technologies to specific TRIZ components remains unexplored. This systematic literature review is conducted to delve into the detailed integration of AI with TRIZ, particularly S-TRIZ. The results elucidate the current state of AI applications within TRIZ, identifying focal TRIZ components and areas requiring further study. Additionally, the study highlights the trending AI technologies in this context. This exploration serves as a foundational resource for researchers, developers, and inventors, providing valuable insights into the integration of AI technologies with TRIZ concepts. The study not only paves the way for the development and automation of S-TRIZ but also outlines limitations for future research, guiding the trajectory of advancements in this interdisciplinary field.
Databáze: Directory of Open Access Journals