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When developing domain-specific modeling languages (DSMLs), software engineers have to make a number of important design decisions on the DSML itself, or on the software-development process that is applied to develop the DSML. Thus, making well-informed design decisions is a critical factor in developing DSMLs. To support this decision-making process, the model-driven development community has started to collect established design practices in terms of patterns, guidelines, story-telling, and procedural models. However, most of these documentation practices do not capture the details necessary to reuse the rationale behind these decisions in other DSML projects. In this paper, we report on a three-year research effort to compile and to empirically validate a catalog of structured decision descriptions (decision records) for UML-based DSMLs. This catalog is based on design decisions extracted from 90 DSML projects. These projects were identified - among others - via an extensive systematic literature review (SLR) for the years 2005 - 2012. Based on more than 8,000 candidate publications, we finally selected 84 publications for extracting design-decision data. The extracted data were evaluated quantitatively using a frequent-item-set analysis to obtain characteristic combinations of design decisions and qualitatively to document recurring documentation issues for UML-based DSMLs. We revised the collected decision records based on this evidence and made the decision-record catalog for developing UML-based DSMLs publicly available. Furthermore, our study offers insights into UML usage (e.g. diagram types) and into the adoption of UML extension techniques (e.g. metamodel extensions, profiles).

Previous works suggest that 80% to 90% of failures observed in the rotary machines are accounted to fatigue failure. And it is observed that cyclic stresses are more critical than steady stresses when the failure occurred is due to fatigue. One of the most expensive industries involving rotary machines is the Oil and Gas industry. The large drilling tools are used for oil extracts on-shore and off-shore. There are several forces that act on a drilling tool while operating below the earth surface. Those forces are namely pressure, bending moment and torque. The tool is designed from the baseline model of the former tool in Solidworks and Design Molder. Here load acting due to pressure and torque accounts for steady stress i.e., Mean Stress and loading acting due to bending moment account for fluctuating stress i.e., Alternating Stress. The loading and boundary conditions have been adapted from Halliburton’s previous works for LWD drill tool to better estimate the size of the largest possible transducer. The fatigue analysis of static load cases is carried out in Ansys Mechanical Workbench 19.0 using static structural analysis. The simulation is run to obtain results for total deformation, equivalent stress, and user-defined results. The component is designed for infinite life to calculate the endurance limit. Shigley guideline and FKM guideline are compared as a part of a study to select the best possible approach in the current application. The width of the imaging pocket is varied from 1.25 inches to 2.0 inches to accommodate the largest possible transducer with compromising the structural integrity of the tool. The optimum design is chosen based on the stress life theory criteria namely Gerber theory and Goodman Theory.<br>

abstract: This research is aimed at studying the impact of building design parameters in terms of their importance and mutual interaction, and how these aspects vary across climates and HVAC system types. A methodology is proposed for such a study, by examining the feasibility and use of two different statistical methods to derive all realistic ‘near-optimum’ solutions which might be lost using a simple optimization technique. DOE prototype medium office building compliant with ASHRAE 90.1-2010 was selected for the analysis and four different HVAC systems in three US climates were simulated. The interaction between building design parameters related to envelope characteristics and geometry (total of seven variables) has been studied using two different statistical methods, namely the ‘Morris method’ and ‘Predictive Learning via Rule Ensembles’. Subsequently, a simple graphical tool based on sensitivity analysis has been developed and demonstrated to present the results from parametric simulations. This tool would be useful to better inform design decisions since it allows imposition of constraints on various parameters and visualize their interaction with other parameters. It was observed that the Radiant system performed best in all three climates, followed by displacement ventilation system. However, it should be noted that this study did not deal with performance optimization of HVAC systems while there have been several studies which concluded that a VAV system with better controls can perform better than some of the newer HVAC technologies. In terms of building design parameters, it was observed that ‘Ceiling Height’, ‘Window-Wall Ratio’ and ‘Window Properties’ showed highest importance as well as interaction as compared to other parameters considered in this study, for all HVAC systems and climates. Based on the results of this study, it is suggested to extend such analysis using statistical methods such as the ‘Morris method’, which require much fewer simulations to categorize parameters based on their importance and interaction strength. Usage of statistical methods like ‘Rule Ensembles’ or other simple visual tools to analyze simulation results for all combinations of parameters that show interaction would allow designers to make informed and superior design decisions while benefiting from large reduction in computational time. / Dissertation/Thesis / Masters Thesis Built Environment 2015

The relatively new utilization of learning management system (LMS) facilitated blended learning in secondary public schools has grown in popularity, but there is a void in research at this level. Teachers learned how to use the LMS features and honed their blended learning design skills through their own experiences, and in observation of their students' experiences. In this study, the knowledge teachers built and the decisions they made while designing blended learning were explored. In this mixed-methods study, the quantitative and qualitative results aligned, indicating that teachers design courses using a variety of components, often in different ways. Six themes emerged. The relationships between themes were used to create a theoretical visual of the factors impacting secondary teachers' decisions in the design of LMS-facilitated blended learning. Teacher design decisions were focused on the impact their choices would have on students. Variation in course design was purposely used by teachers to differentiate for students individually; however, variation was also the result of design challenges blocking teachers from a specific design choice. The implications for practice primarily focus on removing the design challenges. The results of this study add to other foundational studies to begin to fill the research gap in the area of LMS-facilitated blended learning design in secondary schools.

Context: A software project’s success; involvinga larger group of individuals, relies on efficient teamcommunication. Part of efficient communication is avoidingmiscommunication, misunderstandings, and losingknowledge. These consequences of poor communication canlead to negative repercussions such as loss of time, money,and customer approval. Much effort has been put intocreating tools and systems to aid software engineers inretaining knowledge and decisions made during meetings,but many existing solutions require additional manualintervention on the part of software meeting participants.The objective of this thesis is to explore and develop a toolcalled Design Extractor (DE) which creates concisesummaries of design meetings from recorded voiceconversations. These summaries include both the designdecisions made during a meeting as well as the rationalebehind them. This thesis used readily available Pythonframeworks for machine learning to train two transformermodels based on DistilBert and Google’s BERT. Fine-tuningthese models with data sourcedfrom six different softwaredesign meetings found that the best base model wasDistilBert, which resulted in a fine-tuned model reporting anF1 score of 82.63%. This study created a simple Python tool,built upon many publicly available Python frameworks andthe fine-tuned transformer model, that takes in voicerecordings and outputs labeled sentence-label pairs that canbe used to quickly notate a design meeting. Short summariesare also provided by the tool through the use of pre-existingtext summarisation machine learning models such as BART.Design extractor therefore provides a simple quick way toreview longer meeting recordings in the context of softwareengineering decisions.

This research integrates a multi-attribute decision-support tool, the Analytic Hierarchy Process (AHP), with a customer-focused design methodology, Quality Function Deployment (QFD). The result is a hybrid methodology more complete than either of the two alone, involving synthesis, analysis, and evaluation activities necessary for completing conceptual system design. An indicator was developed for the overall performance of an organization's product and its competitors’ products using the information in a QFD matrix. In addition, a methodology was developed to determine if essential customer requirements and design-dependent parameters (DDPs) have been adequately identified in the QFD matrix. A mathematical relationship was developed which relates technical and competitive assessments in the QFD matrix and helps test for inconsistencies. Finally, an indicator was developed to assess a new product concept for viability in the marketplace and to be used for accomplishing trade-off analyses. Examples are presented throughout this document to further illustrate the concepts. This research is unique in its application. It adds to the body of knowledge for decision-making in the conceptual design phase of the systems engineering process. / Master of Science

During product development, most of the customer value, as well as the cost and the quality of a product are defined. This key role of development in industry has led to an intense search for better ways to develop products, software, services and systems. One development methodology that has received positive attention is Set-Based Concurrent Engineering (SBCE). Some authors claim that SBCE and related practices from Lean Development are four times more productive than traditional development models. Unfortunately, SBCE is also described as hard to implement. This thesis presents the results of a three year research project aimed at implementing and describing the effects of Set-Based Concurrent Engineering in industry. The scope of the research is to use the principles of SBCE as a means to improve the productivity of industrial product development processes and its resulting products. The contribution of this work is a better understanding of Set-Based Concurrent Engineering and a support to implement its principles. The results show that SBCE gives positive effects on many aspects of product development performance and on the resulting products. The improvements are especially dominant on product performance, product cost and the level of innovation Moreover, a comparison between a Set-based decision process and a traditional matrix for design evaluation is presented, showing that these two approaches generate different results. The matrix evaluation promoted the development of new technology and the Set-based process promoted a thorough understanding of the important design parameters of the current designs. Finally, this work presents a structured design process and computer tool for implementing the principles of SBCE. The process was demonstrated by using information from an industrial development project, showing how the proposed process could implement the three principles of SBCE in a traditional Point-based development environment.

abstract: Schools all around the country are improving the performance of their buildings by adopting high performance design principles. Higher levels of energy efficiency can pave the way for K-12 Schools to achieve net zero energy (NZE) conditions, a state where the energy generated by on-site renewable sources are sufficient to meet the cumulative annual energy demands of the facility. A key capability for the proliferation of Net Zero Energy Buildings (NZEB) is the need for a design methodology that identifies the optimum mix of energy efficient design features to be incorporated into the building. The design methodology should take into account the interaction effects of various energy efficiency measures as well as their associated costs so that life cycle cost can be minimized for the entire life span of the building. This research aims at developing such a methodology for generating cost effective net zero energy solutions for school buildings. The Department of Energy (DOE) prototype primary school, meant to serve as the starting baseline, was modeled in the building energy simulation software eQUEST and made compliant with the requirement of ASHRAE 90.1-2007. Commonly used efficiency measures, for which credible initial cost and maintenance data were available, were selected as the parametric design set. An initial sensitivity analysis was conducted by using the Morris Method to rank the efficiency measures in terms of their importance and interaction strengths. A sequential search technique was adopted to search the solution space and identify combinations that lie near the Pareto-optimal front; this allowed various minimum cost design solutions to be identified corresponding to different energy savings levels. Based on the results of this study, it was found that the cost optimal combination of measures over the 30 year analysis span resulted in an annual energy cost reduction of 47%, while net zero site energy conditions were achieved by the addition of a 435 kW photovoltaic generation system that covered 73% of the roof area. The simple payback period for the additional technology required to achieve NZE conditions was calculated to be 26.3 years and carried a 37.4% premium over the initial building construction cost. The study identifies future work in how to automate this computationally conservative search technique so that it can provide practical feedback to the building designer during all stages of the design process. / Dissertation/Thesis / Masters Thesis Built Environment 2016

Entscheidungen im Industrial Design werden vorrangig auf Basis vorab gestalteter Designentwürfe auf der gehobenen Management- und auf Geschäftsführerebene getroffen. In diesen Unternehmensebenen finden sich nur wenige im gestalterischen Bereich ausgebildete Führungskräfte (Schoenberger 2011). Die Entscheidungen über kreative Bereiche der Produktentwicklung werden daher meist von Personen designferner Disziplinen getroffen. Dieser Umstand beinhaltet zum einen eine große Unsicherheit in Bezug auf die richtige Designentscheidung im unternehmerischen Sinne und zum anderen führt es zu zögerlichen und weniger abgesicherten Entscheidungen bei gestalterischen Fragestellungen. Die Subjektivität, die bei diesen Entscheidungen eine nicht zu unterschätzende Rolle spielt, erschwert eine sachliche Bewertung und Folgenabschätzung einer Designentscheidung. Diese haben jedoch im weiteren Produktentwicklungsprozess (PEP) und vor allem bei dessen Endergebnis einen großen Einfluss auf die Wirtschaftlichkeit eines Produkts und dessen möglichen Erfolg auf dem Markt. Im klassischen Innovationsmanagement werden die Designkriterien nicht oder nur unzureichend berücksichtigt. So weist beispielsweise die Innovationscheckliste nach Hauschildt/Salomo kein einziges Designkriterium auf, wenn es um die Bewertung einer möglichen Innovation geht (Hauschildt und Salomo 2011).