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The increasing diffusion of rapidly developing AI technologies led to the idea of the experiment to combine TRIZ-based automated idea generation with the natural language processing tool ChatGPT, using the chatbot to interpret the automatically generated elementary solution principles. The article explores the opportunities and benefits of a novel AI-enhanced approach to teaching systematic innovation, analyses the learning experience, identifies the factors that affect students' innovation and problem-solving performance, and highlights the main difficulties students face, especially in interdisciplinary problems.
Enhancing engineering creativity with automated formulation of elementary solution principles
(2023)
The paper describes a method for the automated formulation of elementary creative stimuli for product or process design at different levels of abstraction and in different engineering domains. The experimental study evaluates the impact of structured automated idea generation on inventive thinking in engineering design and compares it with previous experimental studies in educational and industrial settings. The outlook highlights the benefits of using automated ideation in the context of AI-assisted invention and innovation.
TRIZ Inventive Principles
(2022)
The analysis of several thousand patents led to the conclusion that inventive engineering problems and technical contradictions in all kinds of industrial sectors could be solved by a limited number of basic Inventive Principles (Altshuller, 1984). The modern Theory of Inventive Problem Solving TRIZ (VDI 4521) contains 40 basic Inventive Principles (IP). These principles are simple to use or modify and can be easily integrated in brainstorming or daily engineer’s work. One established part of industrial practice is the composition of the specific groups of principles for solving different kinds of problems (Livotov, Petrov, 2011). Based on interdisciplinary experience of TRIZ application in the industrial companies in the last 25 years the a general order in the application of 40 Inventive Principles can be recommended for idea generation and problem solving (Livotov, Chandra, Mas'udah et al, 2019). This brochure presents an update of the 40 Inventive Principles extending the original version (Altshuller, 1984) with additional 70 sub-principles, resulting in the advanced set of 160 sub-principles, regarded as elementary inventive operators. These extended version of inventive principles finds its application in the AIDA Automatic IDEA & IP Generator https://www.tris-europe.com/eng/software/innovationssoftware.htm
As engineering graduates and specialists frequently lack the advanced skills and knowledge required to run eco-innovation systematically, the paper proposes a new learning materials and educational tools in the field of eco-innovation and evaluates the learning experience and outcomes. This programme is aimed at strengthening student’s skills and motivation to identify and creatively overcome secondary eco-contradictions in case if additional environmental problems appear as negative side effects of eco-friendly solutions. The paper evaluates the efficiency of the proposed interdisciplinary tool for systematic eco-innovation including creative semi-automatic knowledge-based idea generation and concept development. It analyses the learning experience and identifies the factors that impact the eco-innovation performance of the students.
The internal crowdsourcing-based ideation within a company can be defined as an involvement of its staff, specialists, managers, and other employees, to propose solution ideas for a pre-defined problem. This paper addresses a question, how many participants of the company-internal ideation process are required to nearly reach the ideation limit for the problems with a finite number of workable solutions. To answer the research question, the author proposes a set of metrics and a non-linear ideation performance function with a positive decreasing slope and ideation limit for the closed-ended problems. Three series of experiments helped to explore relationships between the metric attributes and resulted in a mathematical model which allows companies to predict the productivity metrics of their crowdsourcing ideation activities such as quantity of different ideas and ideation limit as a function of the number of contributors, their average personal creativity and ideation efficiency of a contributors’ group.
In the modern knowledge-based and digital economy, the value of knowledge is growing relative to other assets and new intellectual property is being created at an ever-increasing rate. Therefore, the ability to find non-trivial solutions, systematically generate new concepts, and create intellectual property rapidly become crucial to achieving competitive advantage and leveraging the intellectual potential of organizations.
Sustainable design of equipment for process intensification requires a comprehensive and correct identification of relevant stakeholder requirements, design problems and tasks crucial for innovation success. Combining the principles of the Quality Function Deployment with the Importance-Satisfaction Analysis and Contradiction Analysis of requirements gives an opportunity to define a proper process innovation strategy more reliably and to develop an optimal process intensification technology with less secondary engineering and ecological problems.
Process engineering industries are now facing growing economic pressure and societies' demands to improve their production technologies and equipment, making them more efficient and environmentally friendly. However unexpected additional technical and ecological drawbacks may appear as negative side effects of the new environmentally-friendly technologies. Thus, in their efforts to intensify upstream and downstream processes, industrial companies require a systematic aid to avoid compromising of ecological impact. The paper conceptualises a comprehensive approach for eco-innovation and eco- design in process engineering. The approach combines the advantages of Process Intensification as Knowledge-Based Engineering (KBE), inventive tools of Knowledge-Based Innovation (KBI), and main principles and best-practices of Eco-Design and Sustainable Manufacturing. It includes a correlation matrix for identification of eco-engineering contradictions and a process mapping technique for problem definition, database of Process Intensification methods and equipment, as well as a set of strongest inventive operators for eco-ideation.
As engineering graduates and specialists frequently lack the advanced skills and knowledge required to run eco-innovation systematically, the paper proposes a new teaching method and appropriate learning materials in the field of eco-innovation and evaluates the learning experience and outcomes. This programme is aimed at strengthening student’s skills and motivation to identify and creatively overcome secondary eco-contradictions in case if additional environmental problems appears as negative side effects of eco-friendly solutions.
Based on a literature analysis and own investigations, authors propose to introduce a manageable number of eco-innovation tools into a standard one-semester design course in process engineering with particular focus on the identification of eco-problems in existing technologies, selection of the appropriate new process intensification technologies (knowledge-based engineering), and systematic ideation and problem solving (knowledge-based innovation and invention).
The proposed educational approach equips students with the advanced knowledge, skills and competences in the field of eco-innovation. Analysis of the student’s work allows one to recommend simple-to-use tools for a fast application in process engineering, such as process mapping, database of eco-friendly process intensification technologies, and up to 20 strongest inventive operators for solving of environmental problems. For the majority of students in the survey, even the small workload has strengthened their self-confidence and skills in eco-innovation
Economic growth and ecological problems have pushed industries to switch to eco-friendly technologies. However, environmental impact is still often neglected since production efficiency remains the main concern. Patent analysis in the field of process engineering shows that, on the one hand, some eco-issues appear as secondary problems of the new technologies, and on the other hand, eco-friendly solutions often show lower efficiency or performance capability. The study categorizes typical environmental problems and eco-contradictions in the field of process engineering involving solids handling and identifies underlying inventive principles that have a higher value for environmental innovation. Finally, 42 eco-innovation methods adapting TRIZ are chronologically presented and discussed.
Accelerated transformation of the society and industry through digi-talization, artificial intelligence and other emerging technologies has intensified the need for university graduates that are capable of rapidly finding breakthrough solutions to complex problems, and can successfully implement innovation con-cepts. However, there are only few universities making significant efforts to com-prehensively incorporate creative and systematic tools of TRIZ (theory of in-ventive problem solving) and KBI (knowledge-based innovation) into their de-gree structure. Engineering curricula offer little room for enhancing creativity and inventiveness by means of discipline‐specific subjects. Moreover, many ed-ucators mistakenly believe that students are either inherently creative, or will in-evitably obtain adequate problem-solving skills as a result of their university study. This paper discusses challenges of intelligent integration of TRIZ and KBI into university curricula. It advocates the need for development of standard guidelines and best-practice recommendations in order to facilitate sustainable education of ambitious, talented, and inventive specialists. Reflections of educa-tors that teach TRIZ and KBI to students from mechanical, electrical, process engineering, and business administration are presented.
The comprehensive assessment method includes 80 innovation performance parameters and 10 key indicators of innovation capability, such as innovation process performance, innovating system performance, market and customer orientation, technology orientation, creativity, leadership, communication and knowledge management, risk and cost management, innovative climate, and innovation competences. The cross-industry study identifies parameters critical for innovation success and reveals different innovation performance patterns in companies.
CONTEXT
The paper addresses the needs of medium and small businesses regarding qualification of R&D specialists in the interdisciplinary cross-industry innovation, which promises a considerable reduction of investments and R&D expenditures. The cross-industry innovation is commonly understood as identification of analogies and transfer of technologies, processes, technical solutions, working principles or business models between industrial sectors. However, engineering graduates and specialists frequently lack the advanced skills and knowledge required to run interdisciplinary innovation across the industry boundaries.
PURPOSE
The study compares the efficiency of the cross-industry innovation methods in one semester project-oriented course. It identifies the individual challenges and preferred working techniques of the students with different prior knowledge, sets of experiences, and cultural contexts, which require attention by engineering educators.
APPROACH
Two parallel one-semester courses were offered to the mechanical and process engineering students enrolled in bachelor’s and master’s degree programs at the faculty of mechanical and process engineering. The students from different years of study were working in 12 teams of 3…6 persons each on different innovation projects, spending two hours a week in the classroom and additionally on average two hours weekly on their project research. Students' feedback and self-assessments concerning gained skills, efficiency of learned tools and intermediate findings were documented, analysed, and discussed regularly along the course.
RESULTS
Analysis of numerous student projects allows to compare and to select the tools most appropriate for finding cross-industry solutions, such as thinking in analogies, web monitoring, function-oriented search, databases of technological effects and processes, special creativity techniques and others. The utilization of learned skills in practical innovation work strengthens the motivation of students and enhances their entrepreneurial competences. Suggested learning course and given recommendations help facilitate sustainable education of ambitious specialists.
CONCLUSIONS
The structured cross-industry innovation can be successfully run as a systematic process and learned in one semester course. The choice of the preferred working teqniques made by the students is affected by their prior knowledge in science, practical experience, and cultural contexts. Major outcomes of the students’ innovation projects such as feasibility, novelty and customer value of the concepts are primarily influenced by students’ engineering design skills, prior knowledge of the technologies, and industrial or business experience.
VDI Standard 4521: Status
(2016)
VDI Guideline 4521 Part 1: “Inventive problem solving with TRIZ: Part 1 – Fundamentals and definitions” has been published on 2015-04-01. The standard will sharpen the image of TRIZ, facilitate cooperation, and support studying and teaching. It is not a textbook but concisely summarizes basic assumptions of TRIZ and its terminology. It gives an overview on specific methods and tools which will be described in the following parts.
In der Wertanalyse ist die Methodik TRIZ (Theorie der Lösung erfinderischer Problemstellungen) seit vielen Jahren als Werkzeug zur Kostensenkung oder zur Steigerung der Funktionalität von Produkten bekannt. Seit ihrem ersten Bekanntwerden in Westeuropa hat sich auch TRIZ weiterentwickelt. So wurden Methoden zur Modellierung von Systemen inzwischen erweitert und um Werkzeuge zur schnellen Lösungsfindung, zur Fehlervoraussage und zur Produktplanung neu entwickelt. Durch den weltweiten wissenschaftlichen Fortschritt, die Verwendung unterschiedlicher Sprachen und neue Literatur ist andererseits auch die verwendete Terminologie angewachsen und nicht mehr eindeutig. Die neue VDI-Richtlinie 4521, von deren erstem Teil nun der Gründruck vorliegt, zielt deswegen auf eine Standardisierung der Terminologie und eine vereinheitlichte Beschreibung der Methoden ab. Mit ihrer Hilfe sollen das Studium der Methodik erleichtert, die Benutzung von Literatur vereinfacht und Inhalte der TRIZ klarer darstellbar werden.
Systemic Constellations are a phenomenological approach to resolving personal, professional and organizational issues. They offer a way of mapping a present reality, working at the source of the hidden dynamics and moving to a resolution. This systemic approach often delivers surprising and unexpected insights while also offering the possibility to analyze and solve organizational problems. Rational analysis provides the whole picture of the problem which often turns out to be too complex for a decision making. Systemic constellations can help to simplify and clarify the situation and inform what has to happen next [8], [17]. The outcomes of systemic constellations as an additional resource for solving comprehensive technical problems have not yet been sufficiently investigated. In structural constellation work dealing with technical problems, the individuals who are involved in the problem situation are used to represent different system components, substances or fields. A moderator voices the feedback from the representatives concerning their feelings or intuitive movements, and points to possible solutions. For example, a moderator places the representatives somewhere in the room, develops a three-dimensional picture of the constellation of the analyzed situation and tries to expose the factors empowering or blocking the way towards constructive solutions [13]. This paper explores the theoretical background and practical outcomes of the systemic constellation method for technical problem solving. It presents some case study work which has been conducted in recent years, and then discusses its findings and implications. The research outlined in this paper demonstrates that the noteworthy contribution of structural constellation work for problem solving is typically the result of a combination of functional analysis and the feeling-as-information principle. The constellation work helps, at first, to reveal the subjective experiences, such as feelings, moods, emotions, and bodily sensations, and then to accept them as a source of objective information relevant to the decision making process. In accordance with the latest research [19], the use of feelings as a source of information follows the same principles as the use of any other information. This paper provides the structures of some standard templates and types of constellation work for technical problems, and discusses the preconditions for their application.
The effective executing innovation projects requires multiple estimation of market success of new product features in the early stages of customer-centered innovation process such as strategy formulation, evaluation of ideas and concepts and also at a stage close to the market launch. The attempts to integrate customers for estimation of the market success often result in time-consuming customer interviews or lengthy field research. For this reason, industrial companies usually try to skip customer surveys even if they risk that their innovations will fail to bring the anticipated economic outcomes. In many practical cases, the customer surveys are simply not feasible or too expensive. As a result, the internal assessments within companies are frequently the only resource available in innovation process in the industrial environment. The paper discusses the possibilities of the fast identification of promising innovation opportunities and new product features based on the internal competences of companies. It compares the results of customer surveys with the estimation of internal company-experts and analyses the accuracy and validity of the expert assessments. The presented case studies demonstrate the accuracy rate between 43% and 77% for prediction of new product features with high market potential by company-internal experts. The paper proposes the evaluation methods to increase the accuracy rate and outlines that one of the essential requirements for reliable forecasting by the experts is their profound understanding of the customer working process, the ability to estimate the importance of customer needs and to assess the level of customer satisfaction with current products on the market.
The Advanced Innovation Design Approach is a holistic methodology for enhancing innovative and competitive capability of industrial companies. AIDA can be considered as an open mindset, an individually adaptable range of strongest innovation techniques such as comprehensive front-end innovation process, advanced innovation methods, best tools and methods of the TRIZ methodology, organizational measures for accelerating innovation, IT-solutions for Computer-Aided Innovation, and other innovation methods, elaborated in the recent decade in the industry and academia
The European TRIZ Association ETRIA acts as a connecting link between scientific institutions, universities and other educational organizations, industrial companies and individuals concerned with conceptual and practical questions relating to organization of innovation process, invention methods, and innovation knowledge. In the meantime, more than TFC 1000 papers or presentation of scientists, educators, and practitioners from all over the world are available at the official ETRIA website. Numerous research projects were supported or funded by the European Commission.
Process engineering focuses on the design, operation, control and optimization of chemical, physical and biological processes and has applications in many industries. Process Intensification is the key development approach in the modern process engineering. The proposed Advanced Innovation Design Approach (AIDA) combines the holistic innovation process with the systematic analytical and problem solving tools of the theory of inventive problem solving TRIZ. The present paper conceptualizes the AIDA application in the field of process engineering and especially in combination with the Process Intensification. It defines the AIDA innovation algorithm for process engineering and describes process mapping, problem ranking, and concept design techniques. The approach has been validated in several industrial case studies. The presented research work is a part of the European project “Intensified by Design® platform for the intensification of processes involving solids handling”.
The paper is addressing the needs of the universities regarding qualification of students as future R&D specialists in efficient techniques for successfully running innovation process. In comparison with the engineers, the students often demonstrate lower motivation in learning systematic inventive techniques, like for example TRIZ methodology, and prefer random brainstorming for idea generation. The quality of obtained solutions also depends on the level of completeness of the problem analysis, which is more complex and time consuming in the case of interdisciplinary systems. The paper briefly describes one-semester-course of 60 hours in new product development with the Advanced Innovation Design Approach and TRIZ methodology, in which a typical industrial innovation process for one selected interdisciplinary mechatronic product is modelled.
The paper conceptualizes the systemic approach for enhancing innovative and competitive capacity of industrial companies (named as Advanced Innovation Design Approach – AIDA) including analysis, optimizations and further development of the innovation process and promoting the innovation climate in industrial companies. The innovation process is understood as a holistic stage-gate system comprising following typical phases with feedback loops and simultaneous auxiliary or follow-up processes: uncovering of solution-neutral customer needs, technology and market trends, identification of the needs and problems with high market potential and formulation of the innovation tasks and strategy, idea generation and problem solving, evaluation and enhancement of solution ideas, creation of innovation concepts based on solution ideas, evaluation of the innovation concepts as well as implementation, validation and market launch of chosen innovation concepts. The article presents the current state of innovation research and discusses the actual status of innovation process in the industrial environment. It defines the future research tasks for amplification of the innovation process with self-configuration, self-optimization, self-diagnostics and intelligent information processing and communication.
This paper presents the results of the idea generation experiment that repeats the study originally conducted at RMIT. In order to establish the influence that the experimental treatments make on the number and the breadth of solution ideas proposed by problem solvers with different knowledge levels, students from different years of study were recruited. Ninety students from the Offenburg University of Applied Sciences, Germany were divided into three groups. All students were asked to generate ideas on cleaning lime deposits from the inside of a water pipe and were given 16 minutes to record their individual ideas. Students of two experimental groups were shown some words for two minuted each. The Su-Field group was exposed to the eight fields of MATCEMIB. The Random Word group was shown eight random words every two minutes. The Su-Field group outperformed both the Control group and the Random Word group in the number of ideas generated. It was also found that the students from the Su-Field group proposed significantly broader solutions than the students from the Control and Random Word groups. The overall results of the experiment support the conclusions made by the RMIT researchers that simple ideation techniques can significantly improve idea generation and that the systematised Substance-Field Analysis is a suitable heuristic for engineering students.
The process of establishing an industry standard for TRIZ has been initiated: VDI Guideline 4521 will cover TRIZ. Work is going on on the first part of the standard which will define and explain basic TRIZ vocabulary and notions. A first draft of a list of terms has been compiled by V. Souchkov and is currently being discussed at MATRIZ. The standardization committee consists of TRIZ specialists of various degrees together with TRIZ users from industry. It is working in close connection with MATRIZ. In parallel, translations for the elements of TRIZ terminology into several languages are being sought. According to schedule, work on the first part of the standard may be finished by July 2014 and may go into print by the end of the year.
The paper is addressing the needs of the universities regarding qualification of students as future R&D specialists in efficient techniques for successfully running innovation process. It briefly describes the program of a novel one-semester-course of 150 hours in new product development and inventive problem solving with TRIZ methodology, offered for the master students at the Beuth University of Applied Sciences in Berlin. The paper outlines multi-source educational approach, which includes a new product development project (about 50% of the complete course), theory, practical work, self-learning with the software tools for computer-aided innovation, and demonstrates examples of the students work. The research part analyses the learning experience, identifies the factors that impact the innovation and problem solving performance of the students, and underlines the main difficulties faced by the students in the course. It describes a method for measurement of education efficiency and compares the results with educational experience in the industry. The presented results can help universities to establish the education in new product development or to improve its performance.