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Despite the significant potential of elasticity in mechanical design, a unified methodological framework for selecting and implementing compliant mechanisms and other elastic structures remains elusive for practitioners. This work addresses this gap by compiling a comprehensive library of structures and mechanisms, integrating compliant mechanisms, origami-inspired designs, metamaterial-based solutions, and advancements in 4D and multi-material printing. This collection offers a broad perspective on the diverse possibilities of elastic elements. Recognizing the need for a systematic approach, we propose a method for navigating this database, grounded in the application of 40 TRIZ inventive principles. This framework aims to assist designers in both understanding the efficacy of elastic mechanical parts and identifying suitable concepts for functional modification. Future work will explore the integration of Large Language Models (LLMs) for enhanced database querying and exploration.

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Classification of Geometric Effects Based on the 40 Inventive Principles

  • 会议论文

  • 发表日期：

    2026年

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  • Matteo Cattaneo,
  • Christian Spreafico,
  • Davide Russo

摘要

Despite the significant potential of elasticity in mechanical design, a unified methodological framework for selecting and implementing compliant mechanisms and other elastic structures remains elusive for practitioners. This work addresses this gap by compiling a comprehensive library of structures and mechanisms, integrating compliant mechanisms, origami-inspired designs, metamaterial-based solutions, and advancements in 4D and multi-material printing. This collection offers a broad perspective on the diverse possibilities of elastic elements. Recognizing the need for a systematic approach, we propose a method for navigating this database, grounded in the application of 40 TRIZ inventive principles. This framework aims to assist designers in both understanding the efficacy of elastic mechanical parts and identifying suitable concepts for functional modification. Future work will explore the integration of Large Language Models (LLMs) for enhanced database querying and exploration.