Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 139-146). Also available on the World Wide Web.

‘Lean’ or ‘lean thinking’ refers to an improvement philosophy which focuses on the fulfilment of customer value and the reduction of waste. This philosophy is credited with the extraordinary rise of Toyota, one of the largest and most profitable automotive companies in the world. This thesis presents a pioneering study investigating how lean thinking should be applied to product development (PD). The aim of the research was to construct an innovative model which supports the implementation of lean thinking in PD. This was achieved through progressive collaboration with practitioners from European manufacturing companies. The model provides a process for the conceptual development of an engineering project, and is composed of phases and activities for which methodologies have been defined. The construction of the lean PD model was preceded by a systematic literature review and an industrial field study, wherein 36 semi-structured interviews were conducted in five manufacturing companies in Europe. The constructed model was later implemented on two real-life case studies via action research. The two conducted case studies involved the product architecture design for a car audio head unit and the development of a helicopter engine. It was concluded that the lean PD model addresses various industrial challenges including customer value, communication, and innovation. Furthermore, by focusing on conceptual design, the lean PD model is expected to reduce design rework. As a result of the positive effects of the model, one of the companies involved intends to implement the lean PD model further, and wishes to extend the model to the rest of the organisation. This research makes four main contributions: (1) a novel lean PD model; (2) a number of tools developed to support the model; (3) a framework for lean PD enablers; and (4) a categorisation of challenges faced by PD in industry used to verify the relevance of the lean PD model.

Energy models are optimisation tools which aid in the formulation of energy policies. Built on mathematics, the strength of these models lie in their ability to process numerical data which in turn allows for the generation of an electricity generation mix that incorporates economic and the environmental aspects. Nevertheless, a comprehensive formulation of an electricity generation mix should include aspects associated with politics and society, an evaluation of which requires the consideration of non-numerical qualitative information. Unfortunately, the use of energy models for optimisation coupled with the evaluation of information other than numerical data is a complicated task. Two prerequisites must be fulfilled for energy models to consider political and societal aspects. First, the information associated with politics and society in the context of energy policies must be identified and defined. Second, a software tool which automatically converts both quantitative and qualitative data into mathematical expressions for optimisation is required. We propose a software framework which uses a semantic representation based on ontologies. Our semantic representation contains both qualitative and quantitative data. The semantic representation is integrated into an Optimisation Modelling System which outputs a model consisting of a set of mathematical expressions. The system uses ontologies, engineering models, logic inference and linear programming. To demonstrate our framework, a Prototype Energy Modelling System which accepts energy policy goals and targets as inputs and outputs an optimised electricity generation mix has been developed. To validate the capabilities of our prototype, a case study has been conducted. This thesis discusses the framework, prototype and case study.

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Les orthèses cognitives peuvent améliorer l'autonomie des traumatisés craniocérébraux (TCC) sévères, tout en intégrant en continu le processus de réadaptation cognitive aux AIVQ au sein de leur domicile. Dans une démarche de conception participative interdisciplinaire, nos travaux ont permis de passer de la pratique des ergothérapeutes à la spécification formelle de plans d'intervention et à l'implémentation de cette pratique dans des orthèses cognitives. Dans cette thèse, une approche reposant sur les personae illustre d'abord les dysfonctionnements chez les TCC, leurs besoins d'assistance, ainsi que les besoins de leurs aidants. Ensuite, deux modèles sont élaborés. Le premier « Gestion dynamique de la réadaptation cognitive » s'intéresse en particulier au choix, à l'adaptation et à l'application d'interventions cognitives fondées sur les données probantes. Le second modèle « Assistance préventive » permet, en situation de danger potentiel, d'assister un TCC de manière progressive et adaptée pour écarter ce danger. Ces modèles sont utilisés de deux manières. D'une part, leur implémentation sous forme d'ontologie OWL illustre comment l'assistance peut être rendue sensible au contexte, dynamique et personnalisée. D'autre part, ils guident la conception et l'implémentation de COOK, une orthèse cognitive pour la préparation de repas, et d'un système de sécurité autonome (SSA) dédié à la prévention et à la sécurité des TCC lors de la préparation de repas. Finalement, une architecture logicielle pour la construction d'orthèses cognitives et dérivée.COOK et SSA ont été déployés au sein d'une résidence pour TCC. Trois résidents peuvent maintenant cuisiner de manière autonome. / Severe traumatic Brain Injury (TBI) is considered a public health problem. ; Indeed, severe TBI causes significant cognitive, emotional and behavioral repercussions that impact the lives of these individuals, particularly their independence in Instrumental Activities of Daily Living (IADLs). Individuals who have experienced severe TBI frequently return to live in their homes despite the severe difficulties associated with their condition, though the need for assistance to perform IADLs frequently persists. The objective of this thesis is to design, represent, formalize and implement a context-aware and adaptive structure of cognitive assistance. This assistance is created according to the general needs of individuals with severe TBI for IADL performance. The proposed assistance will promote their independence to perform IADL in a home environment. The design of this cognitive assistance technology involves an interdisciplinary collaboration between occupational therapy and computer science, to evolve from the assistance provided by the clinicians to a formal computer science formulation and implementation. This design is based on a participative design approach that mainly involves TBI residents of a smart alternative housing unit.A prototype of a cognitive orthotic for meal preparation (COOK) was created and deployed within an alternative housing unit. Implementation of this cognitive orthotic lifted the prohibition on use of a stove for meal preparation that had previously been place on their residents. By allowing these residents to cook independently, COOK has contributed to helping them become more independent in cooking and more confident in their ability to do so.

Knowledge Management Systems are deployed in organisations of all sizes to support the coordination and control of a range of intellectual assets, and the low cost infrastructures made available by the shift to ‘cloud computing’ looks to only increase the speed and pervasiveness of this move. However, their implementation has not been without its problems, and the development of novel interventions capable of supporting the mundane work of everyday organisational settings has ultimately been limited. A common source of trouble for those formulating such systems is said to be that some proportion of the knowledge held by a setting’s members is hidden from the undirected view of both The Organisation and its analysts - typically characterised as a tacit knowledge - and can therefore go unnoticed during the design and deployment of new technologies. Notwithstanding its utility, overuse of this characterisation has resulted in the inappropriate labelling of a disparate assortment of phenomena, some of which might be more appropriately re-specified as ‘hidden knowledges’: a standpoint which seeks to acknowledge their unspoken character without making any unwarranted claims regarding their cognitive status. Approaches which focus on the situated and contingent properties of the actual work carried out by a setting’s members - such as ethnomethodologically informed ethnography - have shown significant promise as a mechanism for transforming the role played by members’ practices into an explicit topic of study. Specifically they have proven particularly adept at noticing those aspects of members’ work that might ordinarily be hidden from an undirected view, such as the methodic procedures through which we can sometimes mean more than we can say in-just-so-many-words. Here - within the context of gathering the requirements for new Knowledge Management Systems to support the reuse of existing knowledge - the findings from the application of just such an approach are presented in the form of a Pattern Language for Knowledge Management Systems: a descriptive device that lends itself to articulating the role that such hidden knowledges are playing in everyday work settings. By combining these three facets, this work shows that it is possible to take a more meaningful approach towards noticing those knowledges which might ordinarily be hidden from view, and apply our new understanding of them to the design of Knowledge Management Systems that actively engage with the knowledgeable work of a setting’s members.

<p>The primary research question of this dissertation is, \textit{How do contestants make sequential design decisions under the influence of competition?} To address this question, I study the influence of three factors, that can be controlled by the contest organizers, on the contestants' sequential information acquisition and decision-making behaviors. These factors are (i) a contestant's domain knowledge, (ii) framing of a design problem, and (iii) information about historical contests. The \textit{central hypothesis} is that by conducting controlled behavioral experiments we can acquire data of contestant behaviors that can be used to calibrate computational models of contestants' sequential decision-making behaviors, thereby, enabling predictions about the design outcomes. The behavioral results suggest that (i) contestants better understand problem constraints and generate more feasible design solutions when a design problem is framed in a domain-specific context as compared to a domain-independent context, (ii) contestants' efforts to acquire information about a design artifact to make design improvements are significantly affected by the information provided to them about their opponent who is competing to achieve the same objectives, and (iii) contestants make information acquisition decisions such as when to stop acquiring information, based on various criteria such as the number of resources, the target objective value, and the observed amount of improvement in their design quality. Moreover, the threshold values of such criteria are influenced by the information the contestants have about their opponent. The results imply that (i) by understanding the influence of an individual's domain knowledge and framing of a problem we can provide decision-support tools to the contestants in engineering design contexts to better acquire problem-specific information (ii) we can enable contest designers to decide what information to share to improve the quality of the design outcomes of design contest, and (iii) from an educational standpoint, we can enable instructors to provide students with accurate assessments of their domain knowledge by understanding students' information acquisition and decision making behaviors in their design projects. The \textit{primary contribution} of this dissertation is the computational models of an individual's sequential decision-making process that incorporate the behavioral results discussed above in competitive design scenarios. Moreover, a framework to conduct factorial investigations of human decision making through a combination of theory and behavioral experimentation is illustrated. <br></p>

In this knowledge economy, organizations are leveraging their competence through the knowledge they possess. Managing knowledge will potentially retain the competence held by the organization if knowledge generated across its projects and units is captured, structured and reused. Even though many tools and techniques are proposed in the literature to support these activities, their adoption in industry has been meagre. This may be due to development of tools without basing them on substantial and careful descriptive studies. This raises the following research issues: the knowledge processes and knowledge sources available in organizations and their characteristics need to be understood better. To address these gaps, following objectives are addressed in this research: ♦ To understand the specific needs and capability of the organization for capture and reuse of product development knowledge and ♦ To evaluate various alternative supports for capture and structure of relevant, evolving product development knowledge for reuse. To address these objectives, two observational studies were conducted in the organizations. To get a broader picture about the knowledge processes occurring in the organization, a KRIT model is proposed which is an acronym for Knowledge of solutions-Requirements-Interactions-Tasks, in which interactions of the designers with people and tools play the central role in processing knowledge during design. The KRIT model is validated through the demonstration of the existence of its nodes and links. From the observations it has been found that interactions ‘designer working with computer’, ‘two designers working with a computer’ and ‘two designers interacting with each other’ are most frequently occurred, and occupied most of the time during designing. Any tools to support knowledge capture and reuse should support these interactions such that capture and reuse can be intuitive and in-built in a natural way into a designer’s work habits. It is emphasized that there is a substantial need to increase the percentage of time spent by designers on capturing knowledge during the design process. This increase in time would lead to decrease in a designers’ time spent on knowledge acquisition and dissemination provided designers are capturing reusable knowledge. To answer capture and reuse of knowledge in detail in the observational studies, a new taxonomy of knowledge is proposed. By linking the representations of argumentation, designer’s activities, and the artefact being designed, we argued that the expressiveness of this taxonomy is high compared to the others proposed in the literature. The taxonomy has three broad categories of knowledge: topics, classes, and activities. Based on the definitions of the factors used in the taxonomy and the analysis of the protocols, the factors in each group under each category are argued to be mutually exclusive. In order to study the links between the proposed categories and factors in the taxonomy of knowledge, a method for converting the questions and answers (from the protocol data) into a generic format is framed. The taxonomy is validated comprehensively, and is able to cover various stages of design. Most of the designers’ time was spent working with a CAD package, in which most of the kinds of knowledge mentioned in the proposed taxonomy of knowledge was neither captured not reused. The important observations noted by comparing the knowledge captured in the preliminary study and the main study are as follows: Compared to the preliminary study, process related information and knowledge are captured higher in the main study. In the main study behavioural related content is captured more; whereas in the preliminary study structural content is captured more. The factors organization, usage, maintenance and sales captured in the preliminary study are not at all captured in the main study. In order to assess the usefulness of the knowledge captured, the kinds of knowledge needs of designers were compared with the kinds of knowledge captured. The important observations about the knowledge needs are: Irrespective of the design stages, in almost 50% of the questions, designers interacted with others to know about old issues or proposals in both the studies. A designer’s time for designing would benefit considerably if the answers for these 50% of the old questions were captured and made available for retrieval in formal documents. In both the studies, proposals based questions played a vital role in the questions analyzed. It shows that considerable proportion of time was spent by the designers on validating, by asking questions, the answers known to them. In contrast to the preliminary study, the designers’ needs for process-related information or knowledge were much higher than that for product-related information or knowledge. Comparing the generic questions obtained from the knowledge needs and knowledge captured reveals that only 14% and 26% with product related content and only 10% and 11.3% of the process based content asked by designers during designing were captured in the preliminary and the main study. These results show that there is a mismatch between knowledge captured and knowledge needed by the designers. This may be one of the primary reasons for the poor usage of documents in the organization. The generic questions generated from the questions asked by the designers and various documents will act as a guideline to the designers for what knowledge and information should and should not to be captured. Due to restrictions in the observations, a questionnaire survey was conducted to achieve the objective to collect 10% of total number of employees’ perspectives about the issues considered in this research. The important observations from the analyses of the collected questionnaire are: Designers’ perceive all types of interactions as important and frequent for information generation and sharing. These results are contradictory to the personal observations in which only interactions ‘designer working with computer’ and ‘two designers working with a computer’ occurred frequently. This shows that designers are unable to identify the kinds of interaction which they perform in their daily activities. Due to this, the information processes occurring within these interactions are not perceptible to the designers. Designers perceive that they get the right information at the right time in only 4 or more out of 10 for most of the times. This perception illustrates there is substantial need for the development of support to satisfy the information needs of designers. Analyses of the types of questions reveal that the question asking behavior of the designers is not static; the major share of questions falling under the category ‘question from answer given’ could be interpreted as: designers often do not frame exact questions to fulfil their requirements; they grab the opportunity to take as much as knowledge as possible during an interaction. Analyses of the types of answers reveal that designers gave more inferences on their answers in order to give a better response, which in turn should help reduce the number of questions subsequently asked especially in the protocol coded as ‘new answer’. Two studies have been used to assess the effectiveness of seven tools for supporting knowledge capture and reuse. The important observations from the initial study are: Mobile E-Notes TakerTM is ranked higher because this equipment provides a blend of properties between the paper and computer. These observations stress the importance of features provided for knowledge generation, modification, capture and reuse in the system. The observations from analyzing the three top rated tools (Mobile E-Notes TakerTM, Tablet with viewing facility and Computer with RhinocerosTM CAD package) to understand influence of these tools on knowledge capture and reuse during conceptual designing are: The differences observed in the percentage of capture between the usage of the three tools demonstrate that tools have an influence on the knowledge capture activity. Even though none of the three tools capture adequate knowledge during designing, Mobile e-Notes TakerTM seems to be the best tool for capture compared to the other two tools, both in the original and redesign experiments. These results suggest that some other mechanisms should be added to these tools so that their effectiveness of capturing could be increased. One mechanism is to incorporate the proposed KRIT model and the taxonomy of knowledge during designing. This integration will be one of the good mechanisms to aid knowledge capture and reuse, because the knowledge capture will occur along with the knowledge creation process. We believe that through this integration the purpose to enhance the knowledge capture and reuse during the design process will be achieved.

<div>Although design is part of everyday experience, increased proficiency in managing and reflecting while designing signify greater proficiency as a designer. This capacity for regulation in design is crucial for learning, including from failure experiences, while designing. Failure and iteration are integral parts of design, with potential cognitive and psychological ramifications. On the one hand, failure can be framed as a learning experience that interrupts thinking and evokes reflection. On the other hand, it can be detrimental for confidence and motivation or derail the design process. Based on similarities between design and self-regulation, I articulate a framework whereby responses to failure might be regulated by beginning designers. Then, this case study applies the framework to describe the experiences and perspectives of beginning designers as they work and fail, illuminating issues of failure in design and the extent of their self-regulation.</div><div><br></div><div>The in situ design processes of four teams was examined to describe self-regulation strategies among student designers. Analysis was conducted with two methods: linkography and typological thematic analysis. Linkography, based on think-aloud data, provided a visual representation of the design process and tools to identify reflection, planning, and critical moments in the design process. Typological analysis, based on think-aloud data, follow-up interviews, and design journals, was used to investigate specific strategies of self-regulation. The complementary methods contribute to understanding beginning designers’ self-regulation from multiple perspectives.</div><div><br></div><div>Results portray varied trajectories in design, ranging from repeated failure and determination to fleeting success and satisfaction. Class structures emerge in designers’ patterns of planning and reflection. These highlight the contextualized and evolutionary nature of design and self-regulation. Furthermore, linkographic evidence showed a beginning sense-making process, followed by oscillating phases of forward and backward thinking, to various degrees. Moments of testing, both successes and failure, were critically connected in the design process.</div><div><br></div><div>Thematic analysis identified 10 themes, aligning with the self-regulatory phases of forethought, performance, and reflection. The themes highlight how regulation in forethought is used to shape performance based on past iterations; meanwhile, the identification and attribution of failures relays information on how, and whether to iterate. Collectively, thematic findings reinforce the cyclical nature of design and self-regulation.</div><div><br></div><div>Design and self-regulation are compatible ways of thinking; for designers, the juxtaposition of these concepts may be useful to inform patterns of navigating the problem-solving process. For educators, the imposition of classroom structures in design and self-regulatory thinking draws attention to instructional design and assessment for supporting student thinking. And for researchers of design or self-regulation, these methods can give confidence for further exploration.</div>

Engineering designers commonly make sequential information acquisition decisions such as selecting designs for performance evaluation, selecting information sources, deciding whom to communicate with in design teams, and deciding when to stop design exploration. There is significant literature on normative decision making for engineering design, however, there is a lack of descriptive modeling of how designers actually make information acquisition decisions. Such descriptive modeling is important for accurately modeling design decisions, identifying sources of inefficiencies, and improving the design process. To that end, the research objective of the dissertation is to understand how designers make sequential information acquisition decisions and identify models that provide the best description of a designer’s decisions strategies. For gaining this understanding, the research approach consists of a synthesis of descriptive theories from psychological and cognitive sciences, along with empirical evidence from behavioral experiments under different design situations. Statistical Bayesian inference is used to determine how well alternate descriptive decision models describe the experimental data. This approach quantifies a designer's decision strategies through posterior parameter estimation and Bayesian model comparison. <br><br>Two research studies, presented in this dissertation, focus on assessing the effects of monetary incentives, fixed budget, type of design space exploration, and the availability of system-wide information on information acquisition decisions. The first study presented in this dissertation investigates information acquisition by an individual designer when multiple information sources are available and the total budget is limited. The results suggest that the student subjects' decisions are better represented by the heuristic-based models than the expected utility(EU)-based models. <br>While the EU-based models result in better net payoff, the heuristic models used by the subjects generate better design performance. The results also indicate the potential for nudging designers' decisions towards maximizing the net payoff by setting the fixed budget at low values and providing monetary incentives proportional to the saved budget.<br><br>The second study investigates information acquisition through communication. The focus is on designers’ decisions about whom to communicate with, and how much to communicate when there is interdependence between subsystems being designed. This study analyzes team communication of NASA engineers at a mission design laboratory (MDL) as well as of engineering students designing a simplified automotive engine in an undergraduate classroom environment. The results indicate that the rate of interactions increases in response to the reduce in system-level design performance in both settings. Additionally, the following factors seem to positively influence communication decisions: the pairwise design interdependence, node-wise popularity (significant with NASA MDL engineers due to large team size), and pairwise reciprocity.<br><br>The dissertation work increases the knowledge about engineering design decision making in following aspects. First, individuals make information acquisition decisions using simple heuristics based on in-situ information such as available budget amount and present system performance.<br>The proposed multi-discipline approach proves helpful for describing heuristics analytically and inferring context-specific decision strategies using statistical Bayesian inference. This work has potential application in developing decision support tools for engineering design. Second, the comparison of communication patterns between student design teams and NASA MDL teams reveals that the engine experiment preserves some but not all of the communication patterns of interest. We find that the representativeness depends not on matching subjects, tasks, and context separately, but rather on the behavior that results from the interactions of these three dimensions. This work provides lessons for designing representative experiments in the future.