THE ANALYSIS AND MODELING OF THE ENGINEERING DESIGN PROCESS: FACTORS LEADING TO INNOVATIVE OUTCOMES

Engineering innovation is essential to solve many of the 21st century’s “grand challenges”, as it plays a strategic role in competitive environments. Currently, most design practices in engineering education focus on aspects of “good” technical design. However, to meet the competitive environment, elements of innovation must also be incorporated. This research has two overarching goals. The first is to determine the characteristics of teams and their design processes that lead to innovative artifacts. Regarding this, two research questions are explored. First, what attitudes and design activities do teams exhibit that are related to the innovativeness of their design artifact? Second, how do teams’ attitudes and their design activities traverse over the design process from problem definition to working prototype? To address these questions, two investigations that identify differences between innovative and non-innovative teams are performed. The first one, examining teams’ design activities, is a quantitative investigation addressing whether the engineering design process has any influence on the innovativeness of the artifact. Stepwise regression and association mining analyses are applied to determine the activities utilized, when they are utilized, and how teams navigate the process as depicted by their iterations. The second, examining teams’ attitudes about their progress, is a qualitative investigation that incorporates grounded theory and content analysis to examine the attitudes of teams and how this potentially affects the innovativeness of the artifact. The second goal of the research focuses on developing an intervention tool to increase the likelihood of innovative outcomes in design settings given engaged activities. This tool is formulized by a Bayesian network model. The results show that utilizing marketing activities in the early phase is essential; and design communication becomes critical in the late phase. Moreover, displaying a smooth iterative flow has a positive effect on the innovativeness of the artifact. This research also shows that the innovative teams act like problem solvers, as well as have the propensity to know what they do not know, and where to seek help. In close, the innovativeness of a design team is a function of both their chosen design activities and their attitudes

Technical Debt in Software Development : Examining Premises and Overcoming Implementation for Efficient Management

Software development is a unique field of engineering: all software constructs retain their modifiability — arguably, at least — until client release, no single project stakeholder has exhaustive knowledge about the project, and even this portion of the knowledge is generally acquired only at project completion. These characteristics imply that the field of software development is subject to design decisions that are known to be sub-optimal—either deliberately emphasizing interests of particular stakeholders or indeliberately harming the project due to lack of exhaustive knowledge. Technical debt is a concept that accounts for these decisions and their effects. The concept’s intention is to capture, track, and manage the decisions and their products: the affected software constructs. Reviewing the previous, it is vital for software development projects to acknowledge technical debt both as an enabler and as a hindrance. This thesis looks into facilitating efficient technical debt management for varying software development projects. In the thesis, examination of technical debt’s role in software development produces the premises on to which a management implementation approach is introduced. The thesis begins with a revision of motivations. Basing on prior research in the fields of technical debt management and software engineering in general, the five motivations establish the premises for technical debt in software development. These include notions of subjectivity in technical debt estimation, update frequency demands posed on technical debt information, and technical debt’s polymorphism. Three research questions are derived from the motivations. They ask for tooling support for technical debt management, capturing and modelling technical debt propagation, and characterizing software development environments and their technical debt instances. The questions imply consecutive completion as the first pursued tool would benefit from—possibly automatically assessable—propagation models, and finally the tool’s introduction to software development organizations could be assisted by tailoring it based on the software development environment and the technical debt instance characterizations. The thesis has seven included publications. In introducing them, the thesis maps their backgrounds to the motivations and their outcomes to the research questions. Amongst the outcomes are the DebtFlag tool for technical debt management, the procedures for retrospectively capturing technical debt from software repositories, a procedure for technical debt propagation model creation from these retrospectives, and a multi-national survey characterizing software development environments and their technical debt instances. The thesis concludes that the tooling support, the technical debt propagation modelling, and the software environment and technical debt instance characterization describe an implementation approach to further efficient technical debt management. Simultaneously, future work is implied as all previously described efforts need to be continued and extended. Challenges also remain in the introduced approach. An example of this is the combinatorial explosion of technology-development-context-combinations that technical debt propagation modelling needs to consider. All combinations have to be managed if exhaustive modelling is desired. There is, however, a great deal of motivation to pursue these efforts when one re-notes that technical debt is a permanent component of software development that, when correctly managed, is a development efficiency mechanism comparable to a financial loan investment.Ohjelmistokehitys on uniikki tekniikan ala: kaikki ohjelmistorakenteet säilyttävät muokattavuutensa — otaksuttavasti ainakin — asiakasjulkaisuun asti. Yhdenkään projektiosakkaan tietämys ei kata koko projektia ja merkittävä osa tästäkin tiedosta karttuu vasta projektin suorittamisen aikana. Nämä ominaisuudet antavat ymmärtää, että ohjelmistokehitysala on sellaisten suunnitelupäätösten kohde, joiden tiedetään olevan epätäydellisiä—joko tarkoituksella tiettyjen projektiosakkaiden intressejä painottavia tai tahattomasti projektia vahingoittavia puutteelliseen tietoon perustuvia. Tekninen velka on konsepti, joka huomioi nämä päätökset sekä niiden vaikutukset. Konseptin tarkoitus on havaita, seurata ja hallita näitä päätöksiä sekä tuloksena syntyviä teknisen velan vaikutuksen alla olevia ohjelmistorakenteita. Edellisen kuvauksen valossa ohjelmistokehitysprojekteille on erityisen tärkeää huomioida tekninen velka sekä mahdollistajana että hidasteena. Tämän vuoksi kyseinen väitöskirja perehtyy tehokkaan teknisen velan hallinnan fasilitointiin moninaisille ohjelmistokehitysprojekteille. Väitöskirjassa tarkastellaan teknisen velan roolia osana ohjelmistokehitystä. Tarkastelu tuottaa joukon premissejä, joihin perustuen esitellään lähestymistapa teknisen velan hallinnan toteuttamiselle. Viisi väitöskirjan alussa esitettyä motivaatiota kiinnittävät ne premissit,joille ratkaisu esitetään. Motivaatiot rakennetaan olemassa olevaan teknisen velan sekä ohjelmistotekniikan tutkimustietoon perustuen. Näihin lukeutuvat muun muassa subjektiivisuus teknisen velan estimoinnissa, teknisen velan informaatiolle nähdyt päivitystaajuusvaatimukset sekä teknisen velan polymorfismi. Havainnoista johdetaan kolme tutkimuskysymystä. Ne tavoittelevat työkalutukea teknisen velan hallinnalle, velan propagoitumisen havainnointia sekä mallinnusta kuin myös ohjelmistotuotantoympäristöjen ja niiden velka instanssien kuvaamista. Tutkimuskysymykset implikoivat peräkkäistä suoritusta: tavoiteltu työkalu hyötyy—mahdollisesti automaattisesti arvoitavista—teknisen velan propagaatiomalleista. Valmiin työkalun käyttöönottoa voidaan taas edistää jos kuvaukset kehitysympäristöistä sekä niiden velkainstansseista ovat käytettävissä työkalun räätälöintiin. Väitöskirjaaan sisältyy seitsemän julkaisua. Väitöskirja esittelee ne kiinnittämällä julkaisujen taustatyön aikaisemmin mainittuihin motivaatioihin sekä niiden tulokset edellisiin tutkimuskysymyksiin. Tuloksista huomioidaan esimerkiksi DebtFlag-työkalu teknisen velan hallintaan, retrospektiivinen prosessi teknisen velan kartoittamiselle versionhallintajärjestelmistä, prosessi teknisen velan mallien rakentamiselle näistä kartoituksista ja monikansallinen kyselytutkimus ohjelmistokehitysympäristöjen sekä näiden teknisen velan instanssien luonnehtimiseksi. Väitöskirjan yhteenvetona huomioidaan, että teknisen velan hallinnan työkalutuki, teknisen velan propagaatiomallinnus ja ohjelmistokehitysympäristöjen sekä niiden teknisen velan instanssien luonnehdinta muodostavat toteutustavan, jolla teknisen velan tehokasta hallintaa voidaan kehittää. Samalla implikoidaan jatkotoimia, sillä kaikkia edellä kuvattuja työn osia tulee jatkaa ja laajentaa. Toteutustavalle nähdään myös haasteita. Eräs näistä on kombinatorinen räjähdys teknologia- ja kehityskontekstikombinaatioille. Kaikki kombinaatiot tulee huomioida mikäli teknisen velan propagaatiomallinnuksesta halutaan kattavaa. Motivaatio väitöskirjassa esitetyn työn jatkamiselle on huomattavaa ja sitä kasvattaa entuudestaan edellä tehty huomio siitä, että tekninen velka on pysyvä komponentti ohjelmistokehityksessä, joka oikein hallittuna on kehitystehokkuutta edistävänä komponenttina verrattavissa finanssialan lainainvestointiin.Siirretty Doriast

Predicting and managing system interactions at early phase of the product development process

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2002.Includes bibliographical references (p. 285-293).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.The activity of designing and developing large, complex, discrete, physical, and engineered products faces the challenges in the physical product system, the organization of people, and the larger systems in which the product resides-the natural and societal systems. This thesis defines system interactions as the interactions amongst design variables within the physical product. Knowing system interactions early in the product development process is critical for project management, design concept selection, and system architecture decisions. However, existing methods that address the system interactions issues, such as the Design Structure Matrix (DSM), are good analysis tools, but cannot be used during conceptual synthesis when the most important decisions about the system designs are made. System level knowledge is defined as the knowledge concerning system interactions. System level knowledge is organizational knowledge that resides in the collective minds of members in the organization. System level knowledge is critical to the success of the design of large systems, yet is often missing due to its empirical nature. A knowledge management framework was proposed in this thesis and tested in industry cases from Ford and CVC. This thesis developed a method to predict and analyze system interactions at early phase of the design process. The method transforms an Axiomatic Design's Design Matrix (DM) into a DSM based on solving systems of linear equations using substitution. Since a DM is more easily constructed during early design phases, we can use this method to obtain a DSM during concept design.Consequently, the advantages of the DSM system analysis tools and methods can be applied to make better decisions on system design, system architecture, and project management. The method was tested using two industry cases at CVC and Johnson and Johnson Ortho-clinical Diagnostics. Both case studies showed that the method was effective in real engineering projects. Further observations in the case studies also revealed that a DSM could also be easily converted back into a DM. The interchangeability between DSM and DM allows engineering organizations to predict system interactions early on in a project, while capturing and managing system level knowledge throughout the product lifecycle.by Qi Dong.Ph.D

A Synthesized Methodology for Eliciting Expert Judgment for Addressing Uncertainty in Decision Analysis

This dissertation describes the development, refinement, and demonstration of an expert judgment elicitation methodology. The methodology has been developed by synthesizing the literature across several social science and scientific fields. The foremost consideration in the methodology development has been to incorporate elements that are based on reasonable expectations for the human capabilities of the user, the expert in this case. Many methodologies exist for eliciting assessments for uncertain events. These are frequently elicited in probability form. This methodology differs by incorporating a qualitative element as a beginning step for the elicitation process. The qualitative assessment is a more reasonable way to begin the task when compared to a subjective probability judgment. The procedure progresses to a quantitative evaluation of the qualitative uncertainty statement. In combination, the qualitative and quantitative assessments serve as information elicited from the expert that is in a subsequent step to develop a data set. The resulting data can be specified as probability distributions for use in a Monte Carlo simulation. A conceptual design weight estimation problem for a simplified launch vehicle model is used as an initial test case. Additional refinements to the methodology are made as the result of this test case and as the result of ongoing feedback from the expert. The refined methodology is demonstrated for a more complex full size launch vehicle model. The results of the full size launch vehicle model suggest that the methodology is a practical and useful approach for addressing uncertainty in decision analysis. As presented here, the methodology is well-suited for a decision domain that encompasses the conceptual design of a complex system. The generic nature of the methodology makes it readily adaptable to other decision domains. A follow-up evaluation is conducted utilizing multiple experts which serves as a validation of the methodology. The results of the follow-up evaluation suggest that the methodology is useful and that there is consistency and external validity in the definitions and methodology features

Recovery of forest canopy parameters by inversion of multispectral LiDAR data

We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC) and reversible jump MCMC (RJMCMC) methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging) data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI), which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI) which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion

Implications of an Iterative Design Experiment in Transcendental and Polynomial Functions Within a Flipped Classroom

This study explores an iterative design research experiment of a flipped mathematics classroom over the span of five curricular units involving big ideas of transcendental and polynomial functions. Transcendental and polynomial functions involve an algebraic, analytic, and graphical approach to the concepts and procedures of exponential, logarithmic, power, cubic, quadratic, linear, and rational functions. The Compleat design research methodology (Middleton, Gorard, Taylor, & Bannan-Ritland, 2008) was used to explore a series of instructional sequences that an instructor implemented in a flipped classroom while teaching big ideas of transcendental and polynomial functions. The experiment occurred over the course of a sixteen-week semester. Data analysis was constructed from a triangulation of relevant data from student constructions in the form of written documents, whole-group and small-group discussions from the video recordings, and the instructor’s personal reflective notes. The hypothetical learning trajectory served as the empirical basis upon which reflections occurred and meaningful modifications were made to the original prototype. Segmenting the content helped decrease the extraneous cognitive load by reducing the burden on students’ working memory in order to make instructional activities more meaningful and effective. More time was allocated in class for basic algorithmic processes prior to the implementation of the higher-order instructional tasks in phase five to account for the increasing intrinsic cognitive load in the instructional tasks. Micro-level practice-based concerns and improvements to the prototype as well as the creation of a theoretical and empirically-based instructional model were natural consequences to the design experiment