Droplet generators are at the heart of many microfluidic devices developed for life science applications but are difficult to tailor to each specific application. The high fabrication costs, complex fluid dynamics, and incomplete understanding of multi-phase flows make engineering droplet-based platforms an iterative and resource-intensive process. First, we demonstrate the suitability of desktop micromills for low-cost rapid prototyping of thermoplastic microfluidic devices. With this method, microfluidic devices are made in 1 - 2 hours, have a minimum feature size of 75 μm, and cost less than $10. These devices are biocompatible and can accommodate integrated electrodes for sophisticated droplet manipulations, such as droplet sensing, sorting, and merging. Next, we leverage low-cost rapid prototyping to characterize the performance of microfluidic flow-focusing droplet generators. Specifically, the effect of eight design parameters on droplet diameter, generation rate, generation regime, and polydispersity are quantified. This was achieved through orthogonal design of experiments, a large-scale experimental dataset, and statistical analysis. Finally, we capitalize on the created dataset and machine learning to achieve accurate performance prediction and design automation of flow-focusing devices. The developed capabilities are captured in a software tool that converts high-level performance specifications to a device that delivers the desired droplet diameter and generation rate. This tool effectively eliminates the need for resource-intensive design iterations to achieve functional droplet generators. We also demonstrate the tool’s generalizability to new fluid combinations with transfer learning. We expect that our newly established framework on rapid prototyping, performance characterization informed by design of experiments, and machine learning guided design automation to enable extension to other microfluidic components and to facilitate widespread adoption of droplet microfluidics in the life sciences.

Today's manufacturing industry is heading more and more towards a mass customization approach. This enables customers to individually specify product characteristics and unique design features to fulfill their exact needs. A common way to accomplish this is by means of design automation often used together with knowledge-based engineering. In this thesis, the order-to-delivery process for customized floor gratings at Weland AB is used as a case. This process is currently manual and dependent on several different departments. It results in a time consuming process which is prone to human errors. The purpose is to investigate how design automation can be used and implemented to automate and improve sections of the order-to-delivery process for customized products at an industrial manufacturing company. The objective is to develop a product configurator to automatically generate 3D models and documentation for production and sales support. The configurator succeeded in demonstrating the possible advantages of using design automation. It showed the possibility to reduce the construction department's workload and achieve faster time-to-offer for the sales department. Additionally it is concluded that using a product configurator reduces the risk of human errors and opens up possibilities for other improvements, such as reducing material waste in the production.

Siemens Energy develops, manufactures, and provides service of products utilized for production of green energy. This thesis has been conducted at Siemens Energy in Finspång and the department of steam turbine design. A major part of the work at the department includes service and updates of operating steam turbines located all around the world. The tasks of updating and service are short and require quick answers as the plant is waiting to be started. In order to adapt to the rapid development time required, the department of steam turbine design has developed a CAD automation process for drawing production of steam turbine diaphragms. The automation process is developed in an older CAD system that the department long have relied on. This CAD software and thus the automation process will soon be retired and taken out of service since the company is switching to the modern CAD software NX. This thesis is aimed at investigating the current development process at the department and propose and develop a new CAD automation process in NX for steam turbine diaphragms. The work was initiated by performing an analysis of the current situation where the collection of data constituted a solid ground for the rest of the thesis. The data lay the basis for the creation of a design specification which later served as a starting point for both the search and development of solution proposals regarding CAD automation. During the concept generation, it became clear that the development process embodied the scope of concepts, a form of application programming interface to achieve design automation was considered evident. This implied a more area-focused concept generation leading up to multiple solution concepts. After the generated solutions had been sorted and ranked, the solution to proceed with was based on NX integrated tool Knowledge Fusion to achieve CAD automation in NX. The development of the automation process and associated models utilized theories such as the MOKA methodology, high level cad templates and on explicit reference modeling. Resulting in a CAD automation process with possibilities to deliver both CAD models and technical drawings within a timeframe that reduces development time. It was concluded that the developed CAD automation process and associated models assured quality and reliability of the CAD material produced. Furthermore, the developed solution fit in the existing diaphragm development process and showed potential to significantly reduce the development time of steam turbine diaphragms.

The regulations on emissions from a combustion engine vehicle are getting tougher with increasing awareness on sustainability, requiring the exhaust after-treatment systems to constantly evolve to the changes in the legislation. To establish a leading position in the competitive market, companies must adapt to these changes within a reasonable timeframe. With Scania’s extensive focus on Simulation-driven design, the product development process at Scania is highly iterative. A considerable amount of time is spent on generating a specific model for a simulation from the existing Computer-aided Design (CAD) model and pre-processing it. Thus, the purpose of this thesis is to investigate how design and simulation teams can collectively work to automatically generate a discretized model from the existing CAD model, thereby reducing repetitive work. As an outcome of this project, a method is developed comprising of two automation modules. The first module, proposed to be used by a design engineer, automatically generates a simulation-specific model from the existing CAD model. The second module, proposed to be used by a simulation engineer, automatically discretizes the model. Based on two case study assemblies, it is shown that the proposed method is significantly robust and has the potential to reduce product development time remarkably.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24748号 / 情博第836号 / 新制||情||140(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 湊 真一, 教授 橋本 昌宜, 教授 岡部 寿男 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

The use of CAD models and CFD analysis has become an essential part of fluid flow design. To reduce the time spent determining a design, optimization frameworks have been implemented to automate the process. Mesh morphing has been implemented within these frameworks to further reduce the time needed. While optimization methods have been developed to optimize a fluid flow path, the optimum design needs to be recreated in a CAD model. A method has been developed which eliminates the need to recreate the optimal results in CAD. This is accomplished by using mesh morphing, CAD and CFD together in an optimization framework. The method developed has been implemented with a significant time savings over the use of a traditional meshing optimization framework.

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The AEC-industry need to respond to multiple requirements from regulations and clients, leading to that building projects are becoming increasingly complex to handle for designers. CAD or computer aided design is a way to handle these challenges, and within CAD a new method is emerging: Computational design enables users to generate and explore design solutions automatically. The purpose of this study was to investigate how computational design can be used and what limitations architects and engineers experience with it.   A qualitative research approach was chosen to get in depth understanding. To get variation 16 semi-structured interviews were conducted as primary data collection coupled with a literature review as theoretical framework. The thesis found that computational design applies both design thinking and computational thinking, it is an iterative process that generates design by altering parameters or algorithms and affects the intended design. In this thesis it also needs to be part of the AEC design process. Computational design was found to have most potential in early stage but can be useful for engineers in later stage as well.  Computational design can be used to increase workflow efficiency through automation and rapid feedback which can improve communication and collaboration. It can also increase solution performance by generating design based on multiple objectives. Furthermore, it enables users to expand their solution space and solve complex problems too difficult to solve otherwise. Computational design can be used to analyze early building concepts, analyze floorplans, to optimize material consumption, material choices, structural elements, energy efficiency, daylight, and acoustic requirements. Challenges found were on an individual level a steep learning curve, increased complexity, collection of trustworthy data and interpretation of data. Challenges on an organizational level were fear of automation, low support from leaders, low understanding of the subject from clients and colleges, unsuitable business models, and traditional processes. Furthermore, performance was found to be limited by computers and software capabilities.  Future research should focus on investigating solutions for the many challenges identified in this thesis. Additionally, further applications should be investigated in a narrower scope; a specific type of building or a general element, preferably avoiding repetition of applications in this study. It would also be of interest to investigate challenges of participants on an international scale, experienced with generative design and textual programming languages since these were found to be difficult to learn and apply. / Byggprojekt har blivit mer komplexa för projektörer och arkitekter att hantera då AEC branschen behöver uppfylla flera lagar och regler samt krav från beställare. En teknik för att möta detta behov är med CAD eller computer-aided-design, och inom CAD har en ny metod växt fram: Computational design möjliggör att automatiskt generera och utforska design lösningar. Syftet med den här studien är att undersöka hur computational design kan användas och vilka begränsningar arkitekter och ingenjörer upplever med det.  En kvalitativ metod valdes för att få en djupare förståelse. För att öka variationen av studien genomfördes 16 semi-strukturerade intervjuer som primär data kombinerat med en litteraturstudie som teoretiskt ramverk. Det framkom att computational design applicerar både designtänkande och computational thinking, är en iterativ process som genererar design genom att ändra parametrar eller algoritmer och påverkar den avsedda designen. I den här studien är computational design också en del av branschens design process. Det framkom också att Computational design har störst potential i tidigt skede men kan också vara användbar för ingenjörer i senare skede. Computational design kan användas till att öka arbetsflödets effektivitet genom automation och snabb feedback, vilket kan förbättra kommunikation och samarbete. Det kan också öka prestandan för lösningar genom att generera design baserat på flera kriterier. Vidare så möjliggör det för användare att öka antalet möjliga designlösningar och lösa komplexa problem som är för svåra att hantera traditionellt. Computational design kan användas till att analysera byggnadskoncept, analysera planlösningar, samt till att optimera materialanvändning, materialval, konstruktioner, energieffektivitet, dagsljus, och akustik. De utmaningar som hittades var på en individuell nivå: brant inlärningskurva, ökad komplexitet, hitta tillförlitliga data och tolka data. På organisationsnivå var utmaningarna: rädsla för automatisering, lågt stöd från ledningen, låg förståelse för ämnet av kunder och kollegor, olämpliga affärsmodeller, och traditionella processer. Prestanda begränsades även av förmågan hos datorer och mjukvaror. Framtida forskning bör fokusera på att undersöka lösningar på de utmaningarna som identifierades i den här studien. Ytterligare applikationer bör också undersökas i högre detalj till exempel som en kategori av byggnader eller ett specifikt byggnadselement som förekommer generellt, företrädesvis utan repetition av denna studie. Det vore också av intresse att undersöka utmaningar för deltagare internationellt som har erfarenhet av generativ design och textuell programmering, då dessa visades ha större svårighet.

Droplet microfluidics is a high-throughput platform capable of accelerating the screening and synthesis of biological and chemical systems. However, significant challenges to microfluidic design and fabrication limit its broad use. In this dissertation, I overview and present potential solutions to challenges in droplet microfluidic fabrication and design. First, I present a method for low-cost rapid prototyping of complex droplet microfluidic devices. By combining desktop micromilling and electrode integration with conductive ink, thermoplastic microfluidic devices can be produced with features as small as 75 microns that can be connected to external sensors and actuators. Such devices can be designed, fabricated, and tested within a day and are shelf stable for months. Next, I developed a droplet microfluidic component library using micromilling and conductive ink electrodes. This library is high-throughput, biocompatible, and consists of components for droplet generation, anchoring, reinjection, coalescence, picoinjection, capacitance sensing, fluorescent sensing, and sorting. These components were combined in complex workflows, specifically, in the development of multi-color droplet pixel arrays. Finally, a series of machine learning based design automation tools for droplet microfluidics were created. These tools are capable of predicting the performance and automating the design of single emulsion and double emulsion droplet generators across any fluid combination. Furthermore, two quality metrics were developed, versatility and flow stability, that provide important context on the behaviors of the suggested designs. These tools are the first of their kind in microfluidics, and can play an important role in shifting droplet microfluidic design away from the manual and iterative process it is today. These advancements in droplet microfluidic design and fabrication can set the basis to rethink the microfluidic development cycle. Predictable and reproducible design and fabrication of sophisticated droplet microfluidic devices would provide a next-generation automation platform for the biological and chemical sciences, running experiments orders of magnitude faster and more sensitive than current methods. / 2025-01-16T00:00:00Z

The agile creation of 3D CAD platforms (3D CAD models that can be configured to obtain a family of Products) has become an important factor for increasing competitiveness of organizations that create discrete products. Design Automation (DA) is a powerful tool that can be used for speeding up and optimizing the design process of those 3D CAD platforms. Nonetheless, for effectively applying DA on the development of 3D CAD platforms it is desirable to count on tools that address the three fundamental hurdles that are also obstructing the wide adoption of DA in practice. These hurdles are the lack of identification of DA opportunities, the absence of performance metrics, and the absence of methods for continuous improvement. This dissertation contributes a set of methods and tools to incrementally improve the process for creating 3D CAD platforms towards increased automation. The tools proposed include the development of a Metrics Framework (MF) for assessing the capabilities of an organization for creating 3D CAD platforms; a method for increasing the organizational capabilities for creating 3D CAD platforms, and a method for identifying optimal improvement efforts for creating 3D CAD platforms in a multi-objective scenario