World Conference of AI-Powered Innovation and TRIZ Methodology

2nd IFIP WG 5.4 International TRIZ Future Conference, TRAI 2025, Paris, France, November 5-7, 2025, Proceedings, Part I
Erscheinungsjahr 2025
ISBN: 978-3-032-08846-8
Verlag: Springer

Buch, Englisch, 336 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 692 g

Reihe: IFIP Advances in Information and Communication Technology

This book constitutes the proceedings of the 25th IFIP WG 5.4 International TRIZ Future Conference on AI-Powered Innovation and Inventive Design, TFC 2025, held in Paris, France, during November 5–7, 2025.

The 48 full papers  included in this book were carefully reviewed and selected from 75 submissions. They were focused on topical section as below.

Part I: Neuro-Symbolic and AI-Assisted Contradictions; Generative Agents for Ideation and Design; Tech Mining, Forecasting and Cross-Domain Exploration; Modeling, Verification and Optimization of Technical Systems and Frameworks for Digital Transformation and Industry 5.0. 

Part II Cognition, Causality and Systematic Prototyping; Innovation Governance and Standardization; Innovation Governance and Standardization; Data, Forecasting and Intelligent Services and User Experience and Interoperable Public Policies.

Zielgruppe

Research

Autoren/Hrsg.

Cavallucci, Denis

Brad, Stelian

Livotov, Pavel

Houssin, Rémy

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Information Retrieval
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Inhaltsverzeichnis

.- Neuro-Symbolic and AI-Assisted Contradictions.

.- Research on Technology Opportunity Discovery and Implementation Based on Multi-Layer Knowledge Graphs .
.- Systematic Cause Elimination in TRIZ Cause-Effect Models With Partially Defined Logical Operators.
.- Comparative Study on AI-Augmented Inventive Problem Solving With TRIZ, TRIZ-AI Hybrid, and Autonomous AI: An Inline Coating Measurement Case in Lithium-Ion Cell Production.
.- AI-Powered Identification of Main Parameters of Value (MPVs) for Trends of Engineering System Evolution (TESE): Benchmarking Language Models on Wound Care Medical Device Patents.

.- Generative Agents for Ideation and Design.

.- Enhancing Patent Drafting Through Contradiction Identification.
.- Discovery Omnia: Dynamic RAG for Enhanced Patent Analysis and Systematic Innovation.
.- Study on PBL (Problem/Project-Based Learning) Based on TRIZ Methodology.
.- Evaluating LLM Performance in TRIZ-Based System Forecasting: A Study Using the 9-Windows Tool.
.- Leveraging Problem Graph Extraction and Improvement Perspectives for AI-Assisted Invention.
.- Leveraging Large Language Models and TRIZ for Automated Patent Drafting and Innovation Generation.

 .- Tech Mining, Forecasting and Cross-Domain Exploration.

.- Artificial Intelligence for Contradiction Solving in Lean Green Supply Chain Performance Context: A Comparative Case Study.
.- Contradiction Formulation Using Large Language Models and Generative AI.
.- Patents as Signals for Green Investment Opportunity Evaluation: A Full-Cycle AI-Powered TRIZ Framework.
.- Automated TRIZ Function Model Generation Using Large Language Models: An Ontology-Guided Framework for Engineering Problem Analysis.
.- TRIZ in Speech Analytics: Overcoming the AI Precision-Resource Efficiency Contradiction for Scalable Contact Center Innovation.

.- Modeling, Verification and Optimization of Technical Systems.

.- LLM-Based Functional Modeling of Technical Systems.
.- Measuring Transdisciplinarity in Startups With NLP and TRIZ Principles.
.- CPU-Efficient Verification of Science Problem-Solution Pairs: Design Rationale and Baselines.
.- Classification of Geometric Effects Based on the 40 Inventive Principles.

.- Frameworks for Digital Transformation and Industry 5.0.

.- A TRIZ and Socratic AI-Based Problem-Solving Framework.
.- Resilient Innovation Portfolio Management Approach: Exploring Alternative Strategies.
.- Investigating the Integration and Adaptation of ARIZ With Large Language Models.
.- Seeking Additional Mitigation Strategies for State Machine Cause-Effect Modeling.