Outline: "From Traditional TRIZ to DIKWP-TRIZ"

Yucong Duan

International Standardization Committee of Networked DIKWP for Artificial Intelligence Evaluation(DIKWP-SC)

World Artificial Consciousness CIC(WAC)

World Conference on Artificial Consciousness(WCAC)

(Email: duanyucong@hotmail.com)

• The Origins and Evolution of TRIZ:

• Overview of the origins of TRIZ and its relevance in the context of innovation management.

• Emphasis on the widespread use of TRIZ in various industries (e.g., engineering, manufacturing, and product design).

• Changing Innovation Needs in the Age of AI and Digitization:

• Explanation of how the shift to AI and digital transformation has created new demands for innovation.

• How traditional TRIZ faces limitations when dealing with the complexities and speed of modern technological environments.

• Limitations of Traditional TRIZ in Addressing Modern Challenges:

• Analysis of why traditional TRIZ struggles to deal with the highly dynamic, multi-dimensional, and data-rich problems posed by modern innovation challenges.

• Purpose of the Research:

• To introduce and analyze DIKWP-TRIZ as an innovative framework that extends traditional TRIZ to better address the complexities of AI and digitization.

• Significance of the Research:

• Academic Contributions: How DIKWP-TRIZ enriches innovation theory, particularly in improving completeness, consistency, and efficiency in problem-solving processes.

• Practical Contributions: Potential benefits for industries and enterprises in managing more effective, adaptive innovation processes.

• Overview of Methodology:

• Mapping of traditional TRIZ principles to the DIKWP model.

• Cognitive space coverage analysis.

• Redundancy and inconsistency evaluation within TRIZ principles.

• Constructing complexity standards using DIKWP interactions.

• Outline of Chapters:

• A preview of each section to guide the reader through the overall structure of the research, highlighting the connections between theoretical development, methodology, and empirical studies.

• Origins and Key Concepts of TRIZ:

• Background on the creation of TRIZ, its foundational ideas, and the evolution of its core concepts.

• The Evolution of TRIZ:

• The development of key tools such as the Contradiction Matrix, 40 Inventive Principles, and Substance-Field Analysis.

• Core Tools and Methods of TRIZ:

• Detailed descriptions of traditional TRIZ's key tools (e.g., 40 Principles, Contradiction Matrix, Ideal Final Result, and Evolution Trends).

• Applications of Traditional TRIZ Across Industries:

• Case studies highlighting successful applications of traditional TRIZ in various industries such as engineering, manufacturing, and innovation management.

• Lack of Completeness and Consistency:

• How traditional TRIZ struggles to provide comprehensive solutions, particularly when dealing with multi-dimensional problems.

• Challenges in Efficiency:

• Issues with processing efficiency when applying traditional TRIZ to complex, dynamic, or data-rich systems.

• Challenges in the AI and Digital Era:

• Why traditional TRIZ, with its static nature, is increasingly unsuited to the speed and complexity of modern digital and AI-driven environments.

• Introduction to DIKWP-TRIZ:

• The development of DIKWP-TRIZ as an extension of traditional TRIZ, integrating the DIKWP model to address modern challenges.

• Theoretical Basis of DIKWP-TRIZ:

• The five core elements of DIKWP: Data (D), Information (I), Knowledge (K), Wisdom (W), and Purpose (P), and how they interact to support innovation.

• Explanation of DIKWP-TRIZ’s unique approach to networked interactions and state transitions compared to traditional TRIZ’s static model.

• Introduction to DIKWP Structure:

• Detailed explanation of the five DIKWP elements and how they interact to support problem-solving in a dynamic, multi-dimensional way.

• Mapping Process:

• How each of the 40 Inventive Principles from traditional TRIZ maps onto the DIKWP model’s elements.

• Challenges and Solutions in Mapping:

• Discussion of the challenges encountered during the mapping process and how they were addressed.

• 5x5 DIKWP*DIKWP Interaction Analysis:

• Explanation of how the DIKWP*DIKWP 5x5 space evaluation method is used to assess cognitive space coverage.

• Evaluating Completeness in Problem-Solving:

• Detailed steps and principles used to analyze the completeness of coverage in cognitive space using the DIKWP framework.

• Analyzing Redundancy Across TRIZ Rules:

• Using the DIKWP*DIKWP interaction model to analyze potential redundancies in the TRIZ principles.

• Identifying Inconsistencies:

• Detailed methods for identifying and addressing inconsistencies between mapped rules.

• Theoretical Basis for Complexity Metrics:

• Discussion on how path lengths, interactions, and the nature of the DIKWP model help create standards for measuring complexity.

• Using DIKWP to Evaluate Complexity in TRIZ Rules:

• Explanation of how DIKWP*DIKWP interaction lengths are used to construct complexity standards for traditional TRIZ combinations.

• Tabular Presentation of Mapped Rules:

• Present the mapping of TRIZ’s 40 principles onto DIKWP, with an explanation for each mapped principle’s positioning within the DIKWP structure.

• Results of DIKWP Coverage Analysis:

• Present results from the 5x5 cognitive space evaluation and show how well TRIZ rules are covered within DIKWP.

• Data Visualization:

• Use graphs and charts to represent the extent of coverage achieved by traditional TRIZ within the DIKWP model.

• Advantages of DIKWP-TRIZ in Coverage:

• Analyze the benefits of DIKWP-TRIZ’s more complete cognitive space coverage compared to traditional TRIZ.

• Identification of Redundant Rules:

• Present redundancy analysis results, identifying rules in TRIZ that offer overlapping functionality when mapped onto DIKWP.

• Tabular Presentation of Redundant Rules:

• A table displaying which rules are redundant and to what extent.

• Inconsistency Analysis Results:

• Present cases of inconsistency found when TRIZ rules are mapped to DIKWP.

• Effect on Innovation Efficiency:

• Discussion of how redundancy and inconsistency in traditional TRIZ may reduce innovation efficiency and how DIKWP-TRIZ addresses these issues.

• Explanation of Path Lengths and Interaction Factors:

• Theoretical reasoning behind using path lengths and interaction complexity as evaluation metrics for innovation processes.

• Steps for Evaluating Complexity:

• Detailed steps for using DIKWP*DIKWP interaction lengths to assess the complexity of TRIZ rule combinations.

• Case Studies in Complexity:

• Examples of how complexity standards are applied to real-world TRIZ rule combinations.

• Optimizing Rule Combinations:

• The significance of complexity standards in optimizing TRIZ combinations and enhancing innovation efficiency.

• Overview of Study Design:

• Explanation of the study design, including data collection methods, sample population, and analytical tools used.

• Description of Data Sources:

• Discussion of the sources of data, how it was collected, and how it was processed for analysis.

• Detailed Case Studies:

• Introduction of case studies where DIKWP-TRIZ was applied, including background and context.

• Analysis of DIKWP-TRIZ’s Performance:

• Discussion of how DIKWP-TRIZ performed in these case studies, focusing on cognitive space coverage, efficiency, and complexity.

• Presentation of Key Findings:

• Presentation of major findings, particularly in areas like redundancy, inconsistency, and complexity evaluation.

• Specific AI-Driven Innovation Scenarios:

• Examples of DIKWP-TRIZ applications in AI and digital innovation.

• Case Studies from Industry:

• Specific examples of DIKWP-TRIZ being applied during digital transformations.

• Innovation Management Impact:

• Discussion of how DIKWP-TRIZ improves enterprise innovation and R&D efficiency.

• Theoretical Contributions:

• Summary of how DIKWP-TRIZ enhances innovation theory by integrating dynamic, real-time adaptability.

• Practical Contributions:

• How DIKWP-TRIZ improves real-world innovation processes.

• Current Limitations of DIKWP-TRIZ:

• Identification of areas where DIKWP-TRIZ could be further refined.

• Suggestions for Improvement:

• Future research directions, including expanding DIKWP-TRIZ into new fields and refining its methods.

• Comparison of DIKWP-TRIZ with Other Innovation Approaches:

• Comparison of DIKWP-TRIZ’s strengths and weaknesses compared to other contemporary innovation methods.

• Overview of Key Points:

• Summarize the main findings and arguments presented in the paper.

• Theoretical and Practical Impact:

• Highlight the key contributions of the research to both theory and practice.

• Proposed Areas for Further Study:

• Suggest future research topics that can further explore the potential of DIKWP-TRIZ.

• Comprehensive List of References:

• List all references cited in the paper following proper citation guidelines.

• Supplementary Material:

• Include any questionnaires, interview guides, and data tables that support the empirical research (if applicable).

1. Strengthened Theoretical Contributions:

• The optimized outline better highlights DIKWP-TRIZ’s theoretical foundation, providing a more detailed analysis of how DIKWP interacts with traditional TRIZ and introduces dynamic, real-time problem-solving mechanisms.

2. Enhanced Methodology:

• Detailed steps and processes are included to explain how DIKWP-TRIZ can map TRIZ principles, evaluate cognitive space, and address redundancy and inconsistency, which are critical improvements over traditional TRIZ.

3. Empirical Evidence:

• The addition of empirical case studies strengthens the application of DIKWP-TRIZ in real-world settings, showcasing its practical value and effectiveness in modern innovation management, especially in AI and digitization.

4. Visual and Quantitative Analysis:

• The use of tables, charts, and graphical representations of data enriches the outline by making complex concepts like cognitive space coverage and complexity analysis more digestible and visually clear.

This optimized and enriched outline ensures a clear, logical flow of content that will help showcase the unique contributions of DIKWP-TRIZ over traditional TRIZ, both in theory and practice.