<p>  </p> <p>The integration of Industry 4.0 technologies such as cyber-physical systems, the internet of things, and artificial intelligence has revolutionized the traditional manufacturing systems, making them smart and digital. Maintenance, a critical component of manufacturing, has been incorporated with data-driven strategies such as prognostic and health management (PHM) to improve production efficiency and reliability. This is achieved by real-time sensing and AI-based modeling, which monitor the health condition of operational equipment for fault detection or failure prediction. The results generated by these models provide crucial support for decision-making processes in manufacturing, ranging from maintenance scheduling to production management.</p> <p>This research focuses on data-driven machine health models based on deep learning in manufacturing systems and explores three directions towards the practical implementation of PHM: model interpretation, model adaptability and robustness enhancement, and cost-benefit analysis of maintenance strategies. In terms of model interpretation, the RNN-LSTM-based model prediction on bearing health estimation was analyzed, and the relationship between the model input and output was investigated. The adoption of the LRP technique improved the explainability of the LSTM model beyond predictive maintenance applications. To enhance model adaptability and robustness, a Transformer-based method was developed for fault diagnosis and novel fault detection, which achieved superior performance compared to conventional fault classification AI-based models. The decision-making aspect of PHM was addressed by conducting a cost-benefit analysis on different maintenance strategies, which provided a new perspective for decision-makers in maintenance management.</p>

<p dir="ltr">Improving environmental sustainability in energy production and waste management are of critical importance. Anaerobic digestion (AD) uses microbes to biologically decompose organic waste and produce biogas, which can be used for various forms of sustainable energy. It can be particularly valuable for livestock facilities considering AD of their manure, and potentially other feedstocks as well, a process known as co-digestion. Improved understanding of co-digestion of agro-industrial feedstocks is critical for these facilities. Understanding the macromolecular composition (carbohydrate, protein, and lipid portions) of potential AD feedstocks has the potential to provide important information for predicting important parameters of AD behavior. However, the stability of these macromolecules in AD samples during long-term storage must be confirmed. Furthermore, synergistic and antagonistic impacts of co-digestion on methane production and digestate composition need to be more thoroughly explored.</p><p dir="ltr">This dissertation investigates the impact of storage at refrigeration temperatures (4°C) for up to one-year on the macromolecular composition of various agro-industrial feedstocks (beef manure, starch, slaughterhouse waste, soap stock, and filter press slurry) and anaerobic co-digestion samples. These same feedstocks were co-digested with manure in batch digesters at different proportions, using two or three feedstocks to determine possible synergistic effects.</p><p dir="ltr">The findings show that minimal macromolecular degradation occurred in AD samples during storage at refrigeration temperatures for up to one-year. A major exception was samples containing high concentrations of readily biodegradable starches, which did experience >50% carbohydrate degradation. This indicates a need for methodological rigor during sample storage and reporting experimental design.</p><p dir="ltr">Furthermore, the co-digestion experiments demonstrated frequent improvements or synergy in specific methane yield, methane production rate, and a wide variety of physical and chemical parameters in the digester effluent. Specific methane yield was shown to be at least additive, with improvement ranging from 3-168%. Some improvements in kinetic performance were also observed and quantified. Statistical results suggest that influent characteristics could be useful as predictors for methane production. This research could catalyze additional work needed to optimize co-digestion feeding strategies for full-scale digesters.</p>

<p>Biodegradation of untreated cotton, linen, and hemp textiles as three substrates – measured through biogas production – was studied to compare digestion yield and the ability of anaerobic sludge as inoculum to utilize the sugars in these textiles without pretreatment. Digestion of these textile substrates was carried out over a 26-day study, with daily sampling of biogas production, to measure biogas production rate and accumulation. The flasks were maintained at 37 °C and 150 RPM with a substrate to inoculum ratio (SIR) of 0.5 g sugars from substrate g-1 VSinoculum from anaerobic sludge. Biogas samples were analyzed through gas chromatography (GC) to determine general biogas composition produced by each textile. Biogas production was notable after the four-day mark; with first peaks occurring on day five (hemp, cellulose), day seven (cotton), and day nine (linen). Production of biogas in the control largely outperformed trials with no added substrate, but overall the methane fractions of the gas was lower than expected, indicating that pretreatment is likely necessary for more complete biodegradation of natural textiles. </p>

<p>Biomass liquefaction is a nascent field within biorefinery research and has arisen in response to the bottleneck created from materials handling at the front end of the biorefinery. The basic concept is that if the biomass were to be converted into a flowable slurry at the front-end of the process, then the material could smoothly flow into the biorefinery pretreatment and down time due to the material forming a plug would be minimized or eliminated. Three liquefaction routes were studied in this work. These routes were: enzyme route, enzyme mimetic route, and a combined route of enzyme and enzyme mimetic. Through a Techno-economic assessment (TEA), it is possible to determine which route is most-economical to scale up and also to understand the extent to which liquefaction increases/decreases of the price of the biorefinery product.</p> <p>Gasification is a bio-based technology that has recently acquired more attention as it is an efficient conversion process for a variety of feedstocks. As new techniques and process routes are discovered, it is important to analyze which process technique is feasible for commercial scale up, as the highest performing technique may not be the most economical option to pursue. Along the same philosophy, a process concept was developed on Aspen Plus® to treat syn-gas impurities and also recycle the spent solvents. A TEA study was performed to determine the unit cost of treatment and to explore avenues of cost saving.</p>

<p dir="ltr">There has been an increased urgency toward mitigating climate change in the past several years. Global warming is causing a climate crisis, affecting ecosystems' ability to reduce extreme events. There is a need for rapid decarbonization while still maintaining healthy economic growth and development. Several nations have adopted various policies and set goals to minimize the impact on human society and mitigate the effects of climate change. While this is a step in the right direction, the rate at which these policies are implemented needs to be accelerated to reach the decarbonization goals that have been set. The prime pillars of decarbonization include adopting renewable energy systems, increasing energy efficiency, industrial electrification, low carbon feedstock, and carbon capture, utilization, and storage.</p><p dir="ltr">There is a pressing need for technological improvements in these areas. Renewable energy sources are not only inexhaustible but also reduce the dependence on fossil-based feedstock and lower air pollution, decreasing the risk of climate change. One of the more significant challenges of adopting renewable energy is the upfront investment required to set up the necessary infrastructure. The first objective of this research is to provide well-researched information on the impacts of the planned renewable energy projects. This research evaluates the effects of expanding offshore wind energy and adopting biobased plastics within the U.S. economy. Using industrial ecology methods, including macroeconomic Input-Output models and Material Flow Analysis through Physical Input-Output Tables, this study assesses the broader economic and environmental impacts of these renewable solutions. A multiregional macroeconomic Input-Output (MRIO) model for the U.S. was developed using the U.S. Industrial Ecology Virtual Laboratory, enhanced with a regional GHG emissions database. This enabled a spatial analysis of economic and emissions impacts from offshore wind energy expansion. Findings show an economic payback period similar to other renewables, with a notably short carbon payback period of less than 6 months. Another objective of this research emphasizes the need for and the effect of implementing circular economy opportunities to boost resource efficiency. It is explicitly designed around the manufacturing of bioplastics from agricultural residue that have the potential to combat the critical environmental issue of plastic pollution. This report elucidates the likely impact of manufacturing these materials on the economy and the environment. Process systems engineering models for polylactic acid (PLA) bioplastics manufacturing were integrated into a national-scale Input-Output model to restructure the U.S. economic model for bioplastics expansion. Results show a potential emissions reduction of up to 35%. It also seeks to evaluate the impacts of replacing different types of plastic packaging with bio-based alternatives using PIOT Hub. This tool demonstrates the potential of replacing pharmaceutical packaging with agro-residue-based bioplastics, supporting a circular economy to mitigate environmental impacts in these sectors. This research highlights bio-based packaging's role in reducing pollution and promoting resource efficiency, showing both environmental and economic benefits of these sustainable materials.</p><p><br></p>

<p dir="ltr">The transportation sector accounts for the most greenhouse gas emissions among all economic sectors. Thus, making our transportation systems sustainable is crucial for achieving the national 2050 net-zero emission goal. This thesis aims to explore the application of cutting-edge technologies for advancing sustainable transportation. A framework that analyzes technologies and their potential applications across different transportation modes and scales is proposed and demonstrated through two case studies.</p><p dir="ltr">The first case study focuses on developing a digital twin-based cooperative driving system for Connected and Automated Vehicles (CAVs) at roundabouts. An experiment conducted in a digital twin simulation environment shows that the cooperative driving system reduces emissions and energy consumption significantly while enhancing safety and maintaining efficiency.</p><p dir="ltr">The second case study proposed a Multi-Layer Perceptron (MLP)-based prediction structure to iteratively predict future flight demand with historical data and future population and personal income data. Compared with Terminal Area Forecasting (TAF) projection data, the difference in the year 2050 is only around 8%. Ultimately, the applications of future aviation fuel demand estimation and future Sustainable Aviation Fuel (SAF) distribution strategy exploration are showcased, leveraging the prediction result of the flight demand in 2050.</p><p dir="ltr">Through the two case studies, the thesis demonstrates the effectiveness of the proposed framework and reveals the significant potential of cutting-edge technologies, such as digital twin, CAVs, and SAF, in achieving sustainability in the transportation sector. These findings provide valuable insights for policymakers, industry stakeholders, and researchers to promote innovation and application of sustainable transportation technologies and ultimately achieve the net-zero emission goal.</p>

<p dir="ltr">In recent years, the world has witnessed a growing trend of record high temperatures, heat waves, and extreme weather events due to climate change. Thus, there is an urgent need to develop technologies that enhance quality of life while mitigating further contributions to climate change. Radiative cooling, a passive cooling technique, offers a promising solution to this challenge. Nature serves as a vast, largely unexplored source of inspiration, with various biological systems utilizing radiative cooling to thrive in extreme environments. This work looks at what can be learned from nature to better develop radiative cooling technologies.</p><p dir="ltr">While nanoparticle-based coatings and biologically-inspired nanocellulose-based structures have shown promise in radiative cooling, each has its limitations. Nanocellulose-based structures exhibit high mechanical strength but lower solar reflectance due to UV absorption. On the other hand, nanoparticle-based coatings require a high volume of nanoparticles, resulting in brittleness. This work introduces a dual-layer system comprising a cellulose-based substrate and a thin nanoparticle-based radiative cooling paint, maximizing both radiative cooling potential and mechanical strength. The relationship is studied between thickness and reflectance of the top coating layer with a consistent thickness of the bottom layer. The saturation point is identified and used to determine the optimal thickness for the top-layer. With the use of cotton paper painted with a 125 microns BaSO⁴-based layer, the cooling performance is enhanced to 149.6 W/m² achieved by the improved total solar reflectance from 80% to 93%.</p><p dir="ltr">Looking at another source of biological inspiration, radiative cooling potential of the white shell of the <a href="" target="_blank"><i>Sphincterochila</i></a><i> zonata</i> desert snail is investigated through experimental techniques, revealing a remarkable 90.8% total solar reflectance and 0.88 sky window emissivity, which is achieved through nanoscale features and layered platelet-like morphologies. This is a record high for a biological system. The porosity, nanostructure, and material composition are analyzed, and compared to relative biological systems in other white shells, including those living in the same Negev desert and highly contrasting ocean dwellers. Structural analysis demonstrates layered platelet-like morphologies that optimize for light scattering in solar wavelengths. We investigate the shell's porosity, nanostructure, and material composition through comparison with other species’ shells in the Negev desert and marine environments. Through this, we gain inspiration from <i>Sphincterochila zonata</i> to develop our own radiative cooling technologies.</p><p dir="ltr">In weight-sensitive applications, thin and lightweight radiative cooling paints are crucial, but achieving high solar reflectance remains a challenge. Using inspiration of the layered structure seen in desert snails, this research introduces ultrawhite <a href="" target="_blank">hBN</a>-Acrylic paints that achieve a remarkable solar reflectance of 97.9% with only 150 µm thickness and 0.029 g/cm² weight. The unique properties of hexagonal boron nitride (hBN), including a high refractive index and nanoplatelet morphology, enable a combination of Mie and Rayleigh scattering, while a 44.3% porosity enhances refractive index contrast. Field tests demonstrate that hBN-Acrylic paints provide full daytime cooling under direct sunlight, reducing temperatures by 5-6℃ below ambient.</p><p dir="ltr">Furthermore, biodegradable chitosan-hBN films are introduced as a promising advancement in sustainable cooling technology. These films, composed of up to 60% hBN nanoplatelets within a chitosan matrix, offer flexibility, mechanical robustness, and significant cooling potential. Preliminary results show that these films achieve high solar reflectance and maintain structural integrity, with further potential for optimization through nanoplatelet alignment techniques like hot pressing. By integrating bio-inspired and synthetic approaches, this work contributes to the broader goal of developing sustainable, high-performance materials for passive cooling.</p>

Current life cycle assessment tools are often deficient in assisting design for sustainable manufacturing efforts. Integrating an improved assessment method into a decision support framework will provide a means for designers and engineers to better understand the impacts of their decisions. A unit process modeling-based sustainability assessment method is presented to assist design decision making by accounting for and quantifying economic, environmental, and social attributes. A set of these sustainability metrics is defined as a basis for comparison of component design alternatives. The method is demonstrated using two titanium component production alternatives that represent typical design for manufacturing scenarios. The modeling method significantly increases the resolution of sustainable manufacturing metrics over conventional assessment techniques, and is one aspect of the overall decision support framework developed. Additionally, fixed sum importance weighting, weighted sum modeling, and scenario analysis were selected as easily employed and transparent design decision techniques to provide the remaining elements of the framework. The demonstration of the decision support framework for titanium component manufacturing illustrates that the sequential approach developed can assist engineers in developing more sustainable components and products. / Graduation date: 2012

Interest in accounting for environmental impacts of products, processes, and systems during the design phase is increasing. Numerous studies have undertaken investigations for reducing environmental impacts across the product life cycle. Efforts have also been launched to quantify such impacts more accurately. Life cycle energy consumption and carbon footprint are among the most frequently adopted and investigated environmental performance metrics. As efforts continue to incorporate environmental sustainability into product design, struggles persist in concurrent consideration of environmental impacts resulting from the manufacturing processes and supply chain network design. Thus, the objective of this research is to present a framework for reducing product cradle-to-gate energy consumption and carbon footprint through simultaneous consideration of manufacturing processes and supply chain activities. The framework developed in this thesis relies on unit process modeling, and is demonstrated for production of a bicycle pedal. It is shown that simultaneous consideration of manufacturing and supply chain processes can impact decision-making and improve product environmental sustainability at the design stage. The work presented contributes to the state of the science in sustainable design and manufacturing research. In addition, a point of departure is established for the research community to move current efforts forward for concurrent consideration of multiple stages of the product life cycle in pursuit of environmental, economic, and social sustainability. / Graduation date: 2012

Inúmeras alterações vêm acontecendo na sociedade contemporânea devido ao surgimento de novas tecnologias, fato esse que tem influenciado várias áreas do conhecimento e alterado de forma significativa o estilo de vida da sociedade. Um dos impactos que a comunidade vem experimentando devido ao seu atual modo de vida é um contínuo e vertiginoso uso dos recursos naturais, que consecutivamente produzem abalos ambientais. Em vista disso, está crescendo o grau de conscientização da sociedade, e as empresas estão sendo impelidas a responder e se responsabilizar pelos impactos negativos gerados por suas atividades, mudando assim, paulatinamente o cenário social e ambiental. Para sanar tal situação, uma nova ferramenta com base em serviços veio proporcionar um desenvolvimento econômico apoiado na desmaterialização do crescimento, conhecido como Sistema Produto-Serviço Sustentável (SPSS). Algumas das características deste sistema se alteram em virtude das necessidades do cliente ou de acordo com a solução, priorizando o atendimento de componentes tangíveis ou intangíveis. O objetivo do estudo é propor um Mapa Visual para categorização de Modelos de Negócio de Sistemas Produto-Serviço Sustentáveis. Em relação ao caminho metodológico para atingir o objetivo proposto, foi desenvolvida uma pesquisa de natureza aplicada, com abordagem qualitativa do problema, descritiva e se valendo de técnicas bibliográfica e documental, e estudo de caso de um mobiliário escolar informatizado. Como resultado da pesquisa, propõe-se um Mapa Visual, composto por 3 categorias, 9 sub-categorias e 45 critérios para categorização de Modelos de Negócio (MN) de SPSS. / Several changes occur in the contemporaneous society, in several areas of knowledge. The impacts produced generated in the last years due to technologies recently appeared, provoked significantly the society’s way of life. These impacts generate effects such the relationship between the current way of life and the increasing use of the natural resources. Therefore, increases gradually the enterprises’ awareness, the last ones responding for these impacts. In order to solve this situation, these enterprises developed a new tool based in services, to proportionate an economic development based in knowledge’s dematerialization, well known as Sustainable Product-Service System (SPSS). Some of the characteristics of this system can be changes, in virtue of the client’s needings or according to solution, prioritizing the attendance of the material and unmaterial components. Thus, it is intended through this study propose a categorization process for Business Models related to SPSS. Concernin the methodological way to achive the proposed goal, it was developed a research of applied nature, with a qualitative approach of the problem, being descriptive and using bibliographic and documental techniques, and being the case of study, an informatized scholar furniture. As a result of this research, it proposes a Visual Map, composed by three categories, 9 subcategories and 45 categorization creiteria of the SPSS Business Models.