The study challenges current literature, which views the notion of problem-finding as the initial identification of a problem to be solved. The concept of problem-finding in this study is that problem-finding continues throughout the problem-solving process and is not distinct from it. This thesis aims to develop a better understanding of problem-finding by examining high school students using problem-finding to solve industrial design problems. The study seeks to find out what types of problem-finding exist and what roles they play in solving design problems. To explore problem-finding, this study uses a Think Aloud methodology to examine the thinking of three high school industrial design students and one high school industrial design teacher solving an authentic industrial design problem. Protocol data was gathered from the subjects and then transcribed, segmented and analysed in three ways, each of which became progressively more specific: Firstly, a macroscopic examination which identified problem-finding episodes occurring throughout the design process; secondly, a microscopic examination which identified four categories of problem-finding; and lastly, a microscopic examination which looked at the role played by the different problem-finding categories in solving design problems. The findings of this study are fourfold. Firstly, problem-finding was found to be used throughout the entire design process. Secondly, there were four categories of problemfinding. Thirdly, each category played an important role predominantly through interaction with other categories. Lastly, the more experienced a person was, the more able they were to use problem-finding effectively to solve design problems. Many current practices use trial and error methods to solve design problems. The importance of this study is that through a better understanding of problem-finding, designers may be able to use metacognitive strategies more efficiently in the process. Similarly, in educational practice, high school design students may be able to learn to think about the methods they use to solve design problems, and this may result in more creative designs.

Thesis (M. Ed.)--University of Hong Kong, 1989. / Includes bibliographical references (leaf 48-51).

Thesis (M.Ed.)--University of Hong Kong, 1989. / Includes bibliographical references (leaves 48-51). Also available in print.

学位授与大学：京都大学 ; 取得学位: 博士(工学) ; 学位授与年月日: 2007-09-25 ; 学位の種類: 新制・課程博士 ; 学位記番号: 工博第2855号 ; 請求記号: 新制/工/1420 ; 整理番号: 25540 / Design problem solving behavior refers to the way in which people solve their creative problem of design in their mind. It is one of the basic problems in the area of design methodology, which varies greatly by cases and designers. On the other hand, there are still some general ways or commonness as the core. Because of the complexity of design problem solving behavior, it is still not understood very well. This dissertation dives into the problem of design problem solving behavior too and tried to provide a general view of it, including both the general strategies and the temporary tactics. But differs from many other researches, it employed a confined and well-structured simulation of manual design process by employing the method of interactive evolutionary computation (IEC) to extract design problem solving behavior objectively. The simulated design process provided a comparable and statistically analyzable model for exploring design problem solving behavior of people, and made the findings of this dissertation more reliable. The design problem of interior works of Chinese residents, which need little special knowledge to solve, was selected as the design problem in this dissertation. The method of IEC was applied in interior works design for helping the Chinese residents to solve the practical interior works design problems, and inducing the design problem solving behavior of them. The dissertation contains 6 chapters, including the general introduction (chapter 1), the main body (chapter 2 to 5), and the conclusion (chapter 6). The main body can be further divided into two parts. In the first part (chapter 2 and 3) the IEC interior works (IECIW) design system was developed, and evaluated by a large amount of Chinese residents on its usability and disadvantage. After the preparation of method in the first part, the second part (chapter 4 and 5) presented two parallel researches on participants’ design problem solving behavior in design process using IEC in order to approach the design problem solving behavior in common design processes. Chapter 1 introduces the background and purpose of the research, reviewed related literatures, and the frame work of the dissertation. In chapter 2, IEC method was tentatively applied in the problem of interior works design. 7 color and texture related factors of the living room of a typical apartment in Beijing were selected as design factors in the IEC IW design system. Through 3 experiments, the IEC IW design system was found effective in interior works design and heuristic for the two tested Chinese students. The effect of increasing population size was also found significantly increasing the efficiency of the system. In chapter 3, the developed IEC IW design system was tentatively used by 231 Chinese residents to evaluate its usability and disadvantage in real design problems of interior works. It was concluded that the IEC IW design system is useful for the residents, and it was also found that older participants, and those with lower education and family income levels, gave the system better evaluations. Chapter 4 started to explore problem solving behavior of people in design tasks through simulated design process for interior works using IEC. Data of design process employing IEC of 8 Chinese participants were collected. Through analysis of design problem solving process, it was revealed that people tend to do what they are certain of firstly, and make harder decisions later. It was also found that people did not tend to move their eyes to a faraway image in the interface constantly, which was considered more convenient for them. Chapter 5 continued to explore problem solving behavior of the 8 participants' interior works design process employing IEC. The method of protocol analysis was employed to analyze verbal reports of the participants. It was revealed that different parts of the interior scene have different influence on people's evaluation, and people tended to use same evaluation criterion continuously on several images, then switch to another evaluation criterion. 3 stages of design problem solving behavior along the process were also explained. Chapter 6 summarizes the findings in the dissertation, presents the general discussion and perspective, and proposed some research in the future. / Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第13384号 / 工博第2855号 / 新制||工||1420(附属図書館) / 25540 / UT51-2007-Q785 / 京都大学大学院工学研究科建築学専攻 / (主査)教授 宗本 順三, 教授 上谷 宏二, 教授 加藤 直樹 / 学位規則第4条第1項該当

The containership design problem involves optimizing a nonconvex objective function over a design space that is restricted by a set of constraints defined in terms of nonconvex functions. An application of standard nonlinear optimization methods to such a problem can at best attain a local optimum that need not be a global optimum. This thesis investigates the application of alternative modeling, approximation, and global optimization techniques for developing a multidisciplinary approach to the containership design problem. The problem involves five design variables, which prioritized according to their relative importance in the model are: design draft, depth at side, speed, overall length, and maximum beam. Five constraints are imposed on the design, viz., an equality constraint to enforce the balance between the weight and the displacement, a linear inequality constraint on the length to depth ratio that is implied by the lightship weight formulation for the design to be acceptable, an inequality constraint on the metacentric height to ensure that the design satisfies the Coast Guard wind heel criterion, an inequality on the freeboard to ensure the minimum required freeboard governed by the code of federal regulations for freeboard (46 CFR 42), and an inequality constraint on the rolling period to ensure that the design satisfies the minimum required rolling period criterion. The objective function employed is the required freight rate, expressed in dollars per metric ton per nautical mile in order to recover annualized construction and operational costs. The model also accommodates various practical issues in a manner suitable to improve its representability. For example, it takes into account the discrete container stowage issue. The carrying capacity (number of containers) is expressed as a continuous function of the principal dimensions by using a linear response surface fit that in turn makes the objective function continuous. The weight-displacement balance is maintained by including draft as a design variable and imposing an equality constraint on the weight and displacement rather than introducing an internal loop to calculate draft at each iteration. This speeds up the optimization process. Also, the weight is formulated independent of the draft to ensure independence of the weight and the displacement, which simplifies the optimization process. The time for loading and unloading containers at a given port is a function of the number of cranes available. The number of cranes is formulated as a function of the length of the ship, and the resulting expression is made continuous through a linear response surface fit. To solve this problem, we design two approaches based on employing a sequence of polynomial programming approximations, each within two alternative branch-and-bound frameworks. In the first approach, we construct a polynomial programming approximation to the containership design problem using the Response Surface Methodology (RSM) and solve this model to global optimality using the software package BARON (Branch-and-Reduce Optimization Navigator - see Sahinidis, 1996), although the Reformulation-Linearization Technique (RLT)-based procedure of Sherali and Tuncbilek (1992, 1997) offers a viable alternative (BARON itself incorporates some elements of the latter approach). The resulting solution is refined by the application of a local search method. This procedure is integrated into two alternative branch-and-bound frameworks. The motivation is that the solution of the nonconvex polynomial approximations is likely to yield solutions in the near vicinity of the true underlying global optimum, and hence, the application of a local search method initiated at such a solution has a greater prospect of detecting such a global optimum. In the second approach, we utilize a continuous-space branch-and-bound procedure based on linear programming (LP) relaxations. These relaxations are generated through an approximation scheme that first utilizes RSM to derive polynomial approximations to the objective function and the constraints, and then applies the RLT to obtain an LP relaxation. The initial stage of this lower bounding step generates a tight, nonconvex polynomial programming relaxation for the problem, and the subsequent step constructs an LP relaxation to the resulting polynomial program via a suitable RLT procedure. The underlying motivation for these two steps is to generate a tight outer approximation of the convex envelope of the objective function over the convex hull of the feasible region. The solution obtained using the polynomial approximations is treated as a lower bound. A local search method is applied to this solution to compute an upper bound. This bounding step is then integrated into two alternative branch-and-bound frameworks. The node partitioning schemes are especially designed so that the gaps resulting from these two levels of approximations are induced to approach zero in the limit, thereby ensuring convergence to a (near) global optimum. A comparison of the containership design obtained from the designed algorithmic approaches with that obtained from the application of the nonlinear optimization methods as in previous research, exhibits a significant improvement in the design parameters translating to a significant amount of annual cost savings. For a typical containership of the size pertaining to a test case addressed in this work, having a gross weight of 90,000 metric tons, an annual transportation capacity of 99,000 containers corresponding to an annual deadweight of 1,188,000 metric tons, and logging 119,000 nautical miles annually, the improvement in the prescribed design translates to an annual estimated savings of $ 1,862,784 (or approximately $ 1.86 million) and an estimated 27 % increase in the return on investment over the life of the ship. The main contribution of this research is that it develops a detailed formulation and a more precise model of the containership design problem, along with suitable response surface and global optimization methodologies for prescribing an improved modeling and algorithmic approach for the highly nonconvex containership design problem. / Master of Science

In the last ten years or so, many interactive aircraft design software packages have been released into the market. One drawback of these packages is that they assume prior knowledge in the field of aircraft design. Also, their main purpose being the preliminary aircraft design in a commercial environment, and are not intended for instructional use. Aircraft Design is an iterative process, and the students in the formative years of training must realise that one year of study is not enough to embrace all the necessary underlying concepts in this field. Most universities present the aircraft design as a classical Problem-Based Learning scenario, where students work in groups, with the group size varying between 5 and 8 students., each with a designated role, to carry out a specific task. The students work through the classical process of preliminary design based largely on textbook methods. Therefore, the need for a preliminary design tool (software) that helps the students to understand, analyse, and evaluate their aircraft design process exists. The developed software does everything that is needed in the preliminary design environment. Students are interactively guided through the design process, in a manner that facilitates lifelong learning. Comprehensive output is provided to highlight the “what if scenarios”. The software consists of many modules such as input (user interface), weight estimation, flight performance, cost estimation, take-off analysis, parametric studies, optimisation, and dynamic stability. Due to the large number of input design variables, a full interactive Graphical-User-Interface (GUI) is developed to enable students to evaluate their designs quickly. Object-Oriented-Programming (OOP) is used to create the GUI environment. The stability and control derivatives computed in this work are largely based on analytical techniques. However, a facility is provided in the software to create the data input file required to run a software package produced by USAF, called DATCOM, that enables computation of the dynamic stability and control derivatives that can be ultimately used in flight simulation work. Amongst all the variables used in aircraft design, aircraft weight is the most significant. A new weight estimation module has been developed to increase the accuracy of estimation to better than 5%. Its output results agree very favourably with the published data of current commercial aircraft such as Airbus and Boeing. Also, a new formula is proposed to estimate the engine weight based on its thrust in the absence of the data available with high degree of accuracy. In order to evaluate the effectiveness of the design under consideration, a comprehensive methodology has been developed that can predict the aircraft price as a function of aircraft weight. The Direct Operating Cost (DOC) is also calculated using methods proposed by ATA, NASA, and AEA. Finally, a walk-through of two case studies are presented, one for large transport aircraft and other for small business jet, to show how typical undergraduate students will proceed with the design and to demonstrate the effectiveness of the developed software.

Historicamente, os concursos públicos de projetos de Arquitetura e Urbanismo produzem material que apresentam diferentes soluções a um mesmo problema. Do edital até a seleção de projetos, o concurso é um processo que permite oportunidades de investigação por meio de vários enfoques. Cientes da importância da produção intelectual resultante desses concursos, pesquisadores da UNIRITTER e UFRGS, em parceria com o Instituto de Arquitetos do Brasil – Departamento do Rio Grande do Sul (IAB/RS), formataram um Acervo que contém o material de concursos realizados no Rio Grande do Sul. Esta pesquisa é inspirada em parte do conteúdo desse Acervo. O foco desta pesquisa está sobre resultados de análises que investigam a influência da formulação do problema em soluções projetuais das propostas classificadas em Concursos de Projetos Urbanos no RS, selecionados entre 2006 e 2016. Para desenvolver a metodologia da pesquisa, utilizou fundamentos do Design Thinking, uma abordagem que permite focar tanto no usuário quanto no problema em si, objetivando soluções mais precisas. Assim, esta pesquisa analisou o problema e a solução para Projetos Urbanos, propondo uma Matriz de Análise a partir de fundamentos da abordagem do Design Thinking. As bases dos concursos foram consideradas a proposição do problema, enquanto os resultados dos concursos, ou seja, os projetos classificados, foram utilizados como o valor gerado pelo concurso. O processo de comparação entre bases dos concursos (proposição do problema) e solução (projetos classificados/atas de julgamento) foi determinado como a incógnita da equação. Desse modo, se estabeleceu a questão de pesquisa que questionou a influência da proposição do problema sobre a resposta em Projetos Urbanos resultantes de concursos. Por meio do uso de ferramentas de análise da retórica da linguagem verbal e visual, aplicadas tanto sobre as bases dos concursos selecionados, quanto nas propostas projetuais classificadas, a pesquisa comparou o problema (bases dos concursos), as soluções propostas (projetos) e a seleção do júri (classificação). A investigação foi dividida em quatro etapas principais, na qual a primeira se concentrou em explorar o Acervo e desenvolver critérios de seleção de amostra, além de fundamentar a pesquisa por meio de revisão de literatura; a segunda etapa teve o foco voltado para o desenvolvimento da Matriz de Análise e seleção e aplicação de ferramentas de retórica verbal e visual; a terceira etapa foi o momento de tabulação e análise de dados; a quarta e última etapa da pesquisa foi a base para a consolidação dos dados e análise dos resultados. A principal contribuição da pesquisa foi misturar métodos de diferentes abordagens para entender a relação entre problema e solução em Projeto Urbano, o que pode revelar meios para uma melhor elaboração do problema de projeto em concursos futuros. Além disso, fomenta o debate sobre a formulação dos problemas em Projetos Urbanos de concursos públicos. O estudo também apresentou recomendações para melhoria da composição de acervo existente e estudos futuros. / Historically, public tendering for Architecture and Urbanism projects produce material that show different solutions to the same problem. From the public notice to the project selection, public tendering is a process that permits investigation opportunities via plenty of approaches. Aware of the importance of the intellectual production that results from these public tenderings, UNIRITTER and UFRGS researchers, along with the Brazilian Architects’ Institute – Rio Grande do Sul section (IAB/RS), formulated a archive that contains the material made in public tenderings in Rio Grande do Sul. This research is inspired in part of this archive. The focus of this research is about the results of analysis that investigate the influence the formulation of the problem in projectual solutions of the classified propositions classified in urban project public tenderings in Rio Grande do Sul, selected between 2006 and 2016. To develop the research methodology, we used fundamentals of Design Thinking, an approach that allows to focus on the user and also on the proble itself, aiming for more precise solutions. So, this research analyzed the problem and solution for Urban Projects, proposing a matrix of analysis on the basis of Design Thinking Approach. The public tendering bases were considered as the proposition of the problem, while the results of the exams, that is, the classified projects, were used as the value generated by the tendering. The comparative process between tendering basis (proposition of the problem) and solution (classified projects/adjudgment acts) was determine as the unknown element of the equation. In that way, it was established that the research question that questioned the proposition of the problem’s influence over the answer in Urban Project that resulted from public exams. Through the use of tools of analysis of rhetoric of verbal and visual language, applied over the bases of the selected tendering, and also on the classified projectual propositions, this research compares the problem (public tendering basis), the proposed solutions (projects) and the jury selection (classification). The investigation was divided in four main stages, in which the first focused on exploring the archive and develop sample selection criteria, also fundamenting the research by means of literature revision; the second stage focused on the development of the matrix of analysis, selection and application of tools of analysis of rhetoric of verbal and visual language; the third stage was the tabulation and data analysis; the fourth and last research stage was the basis of the data consolidation and analysis of the results. The main contribution of the research was to show methods of different approaches to understand the relation between problem and solution in Urban Projects, something that can reveal means to a better elaboration of the project’s problem in future public tenderings. Also, it stimulates the debate about the formulation of problems in Urban Projects public tenderings. This research also shows recommendations to improve the composition of the existing archive and its future studies.

This research is in three parts with different although related objectives. The first part developed an efficient, modified simulated annealing algorithm to solve the D-optimal (determinant maximization) design problem for 2-way polynomial regression with correlated observations. Much of the previous work in D-optimal design for regression models with correlated errors focused on polynomial models with a single predictor variable, in large part because of the intractability of an analytic solution. In this research, we present an improved simulated annealing algorithm, providing practical approaches to specifications of the annealing cooling parameters, thresholds and search neighborhoods for the perturbation scheme, which finds approximate D-optimal designs for 2-way polynomial regression for a variety of specific correlation structures with a given correlation coefficient. Results in each correlated-errors case are compared with the best design selected from the class of designs that are known to be D-optimal in the uncorrelated case: annealing results had generally higher D-efficiency than the best comparison design, especially when the correlation parameter was well away from 0. The second research objective, using Balanced Incomplete Block Designs (BIBDs), wasto construct weakly universal optimal block designs for the nearest neighbor correlation structure and multiple block sizes, for the hub correlation structure with any block size, and for circulant correlation with odd block size. We also constructed approximately weakly universal optimal block designs for the block-structured correlation. Lastly, we developed an improved Particle Swarm Optimization(PSO) algorithm with time varying parameters, and solved D-optimal design for linear regression with it. Then based on that improved algorithm, we combined the non-linear regression problem and decision making, and developed a nested PSO algorithm that finds (nearly) optimal experimental designs with each of the pessimistic criterion, index of optimism criterion, and regret criterion for the Michaelis-Menten model and logistic regression model.

This research is in three parts with different although related objectives. The first part developed an efficient, modified simulated annealing algorithm to solve the D-optimal (determinant maximization) design problem for 2-way polynomial regression with correlated observations. Much of the previous work in D-optimal design for regression models with correlated errors focused on polynomial models with a single predictor variable, in large part because of the intractability of an analytic solution. In this research, we present an improved simulated annealing algorithm, providing practical approaches to specifications of the annealing cooling parameters, thresholds and search neighborhoods for the perturbation scheme, which finds approximate D-optimal designs for 2-way polynomial regression for a variety of specific correlation structures with a given correlation coefficient. Results in each correlated-errors case are compared with the best design selected from the class of designs that are known to be D-optimal in the uncorrelated case: annealing results had generally higher D-efficiency than the best comparison design, especially when the correlation parameter was well away from 0. The second research objective, using Balanced Incomplete Block Designs (BIBDs), wasto construct weakly universal optimal block designs for the nearest neighbor correlation structure and multiple block sizes, for the hub correlation structure with any block size, and for circulant correlation with odd block size. We also constructed approximately weakly universal optimal block designs for the block-structured correlation. Lastly, we developed an improved Particle Swarm Optimization(PSO) algorithm with time varying parameters, and solved D-optimal design for linear regression with it. Then based on that improved algorithm, we combined the non-linear regression problem and decision making, and developed a nested PSO algorithm that finds (nearly) optimal experimental designs with each of the pessimistic criterion, index of optimism criterion, and regret criterion for the Michaelis-Menten model and logistic regression model.

This research project aims to develop a novel A3 thinking approach to support knowledge driven design that aids the generation of decision making within a Lean Product and Process Development (LeanPPD) environment. This research comprises the development of a new A3 template as a technique of problem solving in product design, the adoption of a reflection practice structured in a new A3 template for knowledge capture and sharing, and the generation of the process of using the A3 thinking approach for effective implementation. Providing useful knowledge as a design reference to generate decision making at the initial stages of product development in product design helps the designers to prevent recurrence of the same problem, eliminate design mistakes and enhance design decision. In order to achieve a novel A3 thinking approach, a research methodology consisting of four phases was developed. The first phase synthesises the A3 best practice through literature and documentation reviews. The gap analysis and results from the reviews have identified several problem-solving approaches and learning cycles that have to be considered in the research. The second phase is to evaluate the approaches and their impacts and applications in product design. In order to complete this, several research methods are selected and performed (e.g. focus group and semistructured interview) within the collaborative companies. The third phase is to develop the A3 thinking approach by utilising the LAMDA learning cycle, developing a new A3 template or so-called A3LAMDA, adopting the reflection practice and generating the process of using the new A3 thinking approach. Finally, the validation of the new A3 thinking approach through industrial case studies and expert judgements have been performed. This approach has been implemented in the automotive sector and was applied to four industrial case studies and six A3LAMDA reports were collected. As a result of the findings of this research, the utilisation of the A3 thinking approach aided the generation of knowledge driven design in product design by integrating the knowledge management capabilities; knowledge creation, capture and sharing.