TRIZ Principles

  • Generative AI for Systematic Resource Modification in Creative Problem Solving

    Generative AI for Systematic Resource Modification in Creative Problem Solving

    Tanasak PheunghuaTANASAK 2024 10 27 093253

    The Inventor Development, Thailand

    Abstract

    This paper investigates the use of generative AI for the systematic modification of resources as part of the broader idea-generation process. By utilizing resource analysis and TRIZ-based problem-solving principles, the AI facilitates structured innovation by identifying, categorizing, and transforming various resource categories, including substance, field, time, space, information, and functional resources. The system supports diverse modification goals, such as resolving contradictions, achieving specific objectives, completing jobs to be done, or addressing other creative challenges. It begins by analyzing the existing system, defining the desired modification goal, and applying generative AI to suggest solutions based on appropriate TRIZ principles. The AI-driven modifications enhance resources by adapting their parameters or functions to meet new, optimized goals. This generative AI system accelerates the idea-generation process by providing innovative, practical solutions to real-world problems, improving efficiency and creativity. The integration of generative AI for resource modification offers significant potential across industries, fostering innovation in product development, conceptual ideation, and complex problem-solving.

    Keywords:Generative AI, Resource Modification, TRIZ Principles, Idea generation, Innovation Process

    Communicating Author: This email address is being protected from spambots. You need JavaScript enabled to view it.

    基于生成式人工智能的系整与造性问题解决

    摘要

     本文探讨了在更广泛的思维生成过程中,应用生成式人工智能进行系统性资源调整的实践。结合资源分析和基于发明问题解决理论 (Theory of Inventive Problem Solving, TRIZ) 的问题解决原则

    ,人工智能助力系统化创新,可对物质、场域、时间、空间、信息和功能资源进行识别、分类和转换。该系统支持多种目标导向的修改,如解决矛盾、实现特定目标、完成任务或应对其他创造性挑战

    。其流程始于分析现有系统,定义所需的修改目标,并应用生成式人工智能,依据TRIZ原则提出解决方案。人工智能驱动的修改通过调整资源的参数或功能,满足新的优化目标,从而增强资源效能。该生成式人工智能系统通过提供创新实用的解决方案,加速思维生成过程,提高效率和创造力。生成式人工智能在资源修改方面的应用,在各行各业中展现出巨大潜力,推动了产品开发、概念构思和复杂问题解决的创新进程。

    键词:生成式人工智能(Generative AI)、资源修改( Resource Modification)、TRIZ原则(TRIZ Principles)、思维生成(Idea Generation)、创新过程(Innovation Process)

    Biography

     

    Education

    King Mongkut’s Institute of Technology North Bangkok, Bachelor of Engineering/ Major in Production Engineering

    Training, Shinsuke Kurosawa, Trizit Benjaboonyazit.

    TRIZ Level 3 with Dr. Salamatov Tutorial Session, Nikolai Khomenko. Tutorial Session, Dr. Oleg Feygenson

    Tutorial Session, Dr. Simon Litvin, Japan TRIZ Symposium

    Tutorial Session, Dr. Sergei Ikovenko. Tutorial Session, Valeri Souchkov.

    Experience

    Published TRIZ and Generative AI articles in 2023 worldwide, presented at innovation

    conferences in France, Austria, and Taiwan.

    Innovation Consulting and TRIZ Training as part of a Design Thinking Co-Project with PTT 2023.

    Involved in Innovation Consulting and TRIZ Training with Bangchak since 2023.

    Providing Innovation Consulting, TRIZ Training, and Coaching at Agro. Fiber / Green

    Fiber (Double A Group) since 2023.

    Conducted Innovation Consulting, TRIZ Training, and Coaching for CPF Group from 2009 to 2022, involving approximately 1,000 Scientists and Engineers in various

    departments such as R&D, Farm, Animal Feed, Aqua Feed, and Food Product.

    Engaged in Innovation Consulting, TRIZ Training, and Coaching for Thai Container Group, a subsidiary of the SCG Group, since 2010, with a break in 2020 and a return in 2023.

    Provided Consulting for Process Improvement Projects and delivered TRIZ training

    programs for Somboon Group since 2008, with a break until 2013, and a return in 2023.

    Offered Innovation consulting services for the R&D division of the Building Material section within the SCG Group in 2010-2011.

    Conducted Consulting and delivered TRIZ training programs for Mahaphant Fiber Cement Group in 2008-2009.

    Extensive experience in process and quality improvement across a wide range of industries, including automotive suppliers, electric/electronic, and food packaging,

    with a track record of over 200 successful Black Belt Projects and numerous Green Belt Projects from 2002 to 2007.

    Proficient in process improvement using Design of Experiments (DOE), particularly for metal brazing, soldering, welding applications, and special material welding,

    plating, and coating processes involving materials like silver, nickel, gold, and copper.

    Experienced in optimizing painting processes and plastic injection.

    Conducted food processing optimization using the Taguchi method.

    Served as a Speaker and Judge Committee member for the final rounds of the MyTRIZ

    (Malaysia TRIZ) Competition in 2013, 2014, 2015, and 2016 in Penang, Malaysia.

    • Presented a poster showcasing the implementation of TRIZ in Thailand at the TRIZ

    Symposium 2011 held at Toshiba Education & Training Institute in Yokohama, Japan.

    • Presented a poster on the implementation of TRIZ in Thailand at the Global TRIZ Conference 2011 in Seoul, South Korea.
    • Authored the "TRIZ" handbook, published by E.I. Square Press in 2008, with over 8,000 copies published to date.

    Work Experience

    Managing Director / Consultant, (2004-present) The Inventor Development Co., Ltd.

    Innovex (Thailand) Co., Ltd.

    Schneider Electric (Thailand) Co., Ltd.

    HCC (Thailand) Co., Ltd. (Ford Motor / HCC Korea JV

  • Internship Bridging Academia, Industry, and TRIZ: The Path to a Successful Scientific Career for Professors and Students

    Internship Bridging Academia, Industry, and TRIZ:

    The Path to a Successful Scientific Career for Professors and Students

    Professor, Dr. Boris Farber, TRIZ Biopharma International LLC, Farber’s Center for Academic Success, Inc., Altshuller Institute of TRIZ Studies.

    This email address is being protected from spambots. You need JavaScript enabled to view it.

    AbstractBoris Farber 2024 10 31 144505

    The intersection of academia, industry, and TRIZ (Theory of Inventive Problem Solving) presents a unique opportunity for professors and students to bridge the gap between theoretical knowledge and practical application, paving the way for a successful scientific career. This abstract outlines such internships' benefits, structure, and future prospects.

    The Need for Interdisciplinary Collaboration

    Traditional academic programs often focus on theoretical foundations, while industrial settings demand practical problem-solving skills. TRIZ, with its systematic approach to innovation, fills this gap by providing a methodology that can be applied across various disciplines. An internship that bridges academia, industry, and TRIZ can:

    Integrate Theoretical Knowledge with Practical Skills:Students and professors can apply theoretical concepts to real-world problems, enhancing their understanding and applicability.

    Foster Innovation and Creativity: TRIZ principles encourage innovative thinking and the resolution of contradictions, which are essential skills in both academic and industrial settings.

    Enhance Career Prospects: Such internships provide valuable experience, networking opportunities, and a competitive edge in the job market.

    Structure of the Internship

    An effective internship program at the intersection of academia, industry, and TRIZ should include:

    Academic Foundation: Participants should have a solid understanding of their field of study and the principles of TRIZ.

    Industrial Placement: Interns should be placed in industrial settings where they can apply TRIZ tools to solve real-world problems.

    Mentorship and Guidance: Experienced mentors from academia and industry should guide interns, providing feedback and support.

    Project-Based Learning: Interns should work on specific projects that require the application of TRIZ principles to drive innovation and solve complex problems.

    Benefits for Professors and Students

    This type of internship offers numerous benefits for both professors and students:

    For Students:

    Practical Experience: Hands-on experience in applying theoretical knowledge to industrial problems.

    Networking Opportunities: Building relationships with industry professionals and academics.

    Career Readiness: Enhanced skills and experience make them more attractive to potential employers.

    For Professors:

    Industry Insights: Exposure to the latest industrial practices and challenges.

    Research Opportunities: Collaboration with industry partners can lead to new research avenues and funding opportunities.

    Teaching Enhancement: Professors can integrate real-world examples and case studies into their teaching, making it more relevant and engaging.

    Future Prospects

    As the demand for innovative and practical problem-solving skills grows, internships that bridge academia, industry, and TRIZ are likely to become more prevalent. Future trends include:

    Increased Collaboration: More universities and industries will partner to offer such internships, creating a pipeline of skilled professionals.

    Advanced TRIZ Applications: Integrating AI, machine learning, and other emerging technologies with TRIZ to enhance innovation capabilities.

    Global Opportunities: Internships that offer international placements, exposing participants to diverse industrial and cultural environments.

    Conclusion

    Internships that bridge academia, industry, and TRIZ offer a unique and powerful pathway to a successful scientific career. These programs prepare professors and students to excel in both academic and industrial settings by combining theoretical knowledge with practical skills and innovative problem-solving methodologies. As the world demands more innovative and effective solutions, such internships will play a critical role in shaping the next generation of scientists and innovators. This abstract highlights the importance and benefits of internships that integrate academia, industry, and TRIZ, providing a comprehensive overview of their structure, benefits, and future prospects.

     

    Biography

    Dr. Boris Farber,CEO, dual Ph.D., D.Sc.., Professor, Academician

    Title: President, Chief Executive Officer
    Company: TRIZ Biopharma International LLC, Noigel LLC., Farber’s Center for Academic Success, Inc., TRIZ Biopharma Innovations LLC.

    Vice President of The Altshuller Institute for TRIZ Studies,
    Vice President of the European Academy of Natural Sciences, American-European Association of Sciences, Business, Technology, and Art, World Innovation Association, Vice-President of the "TRIZ Developers Summit" for North America (USA and Canada), Vice-President of the International Council of TRIZ Masters for scientific and practical activities based on TRIZ

    Dr. Boris Farber, TRIZ Master, VP of the Altshuller Institute of TRIZ Studies, President and Chief Executive Officer of TRIZ Biopharma International LLC, Noigel LLC., Farber’s Center for Academic Success, Inc., TRIZ Biopharma Innovations LLC, has been recognized by Marquis Who’s Who Top Executives, by International Association of Top Professionals in different years from 2010-2023 for dedication, achievements, and leadership in Bio and Nanotechnologies, Molecular Modeling,  Applied Mathematics, Education, Bioengineering, Prosthetics, and Orthotics.

    His significant contributions to the field have been acknowledged with numerous awards, a testament to his expertise and the confidence the industry has in his work. Based on this robust and diverse foundation, TRIZ (the Theory of Inventive Problem Solving), the laws of system evolution, system vision, and an international patent law education, he is credited with more than 1,000 inventions, scientific articles, and books in the areas mentioned earlier. His four books, "Theoretical Aspects of Motion Control and Electro-stimulation,” became bestsellers for professionals in this domain. He has participated in designing a unique software: Expert Systems for Biomechanical Measurement and Prosthetics and Orthotics Prescription, based on Artificial Intelligence; Interactive Anthropomorphic Models with Kelvin–Voigt viscoelastic elements; and Problem Formulator and Directed Evolution for inventive problem-solving for medical technologies. His pioneer magnetorheological fluid appliances are implemented in a new generation of computer control prosthetics and muscle training machines based on myoelectric control. His inventions attained six gold and one silver award during the World Exhibition of Inventions in Brussels and have been produced in the space–rocket industry to date. The inventions have helped hundreds of thousands of patients in rehabilitation and improved their lifestyles. Some of his inventions have been used not only on Earth for patient rehabilitation after strokes but also in space for spacemen in spaceships and the orbital space station.

    2024 is a significant year, marking the 49th anniversary of Dr. Farber and his colleagues’ pioneering teaching method. This year also celebrates 40 years of implementing rational, self-adjusted bioengineering design and 25 years of molecular self-adjusted robot design. Dr. Farber's academic journey includes becoming a corresponding member of the Rocket-Space Academy in 1994, a Full Member-Academician of the Academy of Medical Technical Sciences in 1994, and joining various Professional and Mathematical Societies, including the International Society for Prosthetics and Orthotics, the International Society of Biomechanics, and the New York Academy of Science.

    He was named an Honorary Recipient of the “Honored Inventor of Russian Federation” in 1993, the highest prize that may be issued to inventors by the Russian government. He was nominated as Professor of the Year (New York, 2010); Scientist of the Year (New York, 2011-2023); Member of The Top Executive Club, 2016; VIP Person, 2016-2021; Professional of the Year by Worldwide Branding for his impact and contributions to the field of Education(Object-Oriented Patterns and Images Method), and R&D in: Applied Mathematics, Bioengineering, Bio- and Nano-Technologies; dynamic drug design based on quasi-living, self-organizing dynamic medicinal and diagnostic medicine with variable structure and synergy.