<div>This dissertation presents a two-phase multiple case study conducted to investigate the faculty</div><div>beliefs regarding the integration of labs into engineering and engineering technology education</div><div>and the relationship between such beliefs and the teaching practices adopted in the labs. In the first</div><div>phase, an exploratory study grounded on a framework of beliefs was conducted to elicit the beliefs</div><div>espoused by the participants. Interviews were used to elicit the participants’ beliefs. The</div><div>transcribed interviews were analyzed through the constant comparative method. Thirteen faculty</div><div>members from the College of Engineering and Engineering Technology participated. In the second</div><div>phase, a triangulation approach was used to investigate the relationships between the participants’</div><div>beliefs and their corresponding teaching practices. The findings from phase one were triangulated</div><div>with the data from interviews, questionnaires, and documents to elicit the relationships between</div><div>beliefs and practices.</div>

<p>To apply Industry 4.0 technologies and accelerate the modernization of continuous pharmaceutical manufacturing, digital twin (DT) and advanced process control (APC) strategies are indispensable. The DT serves as a virtual representation that mirrors the behavior of the physical process system, enabling real-time monitoring and predictive capabilities. Consequently, this facilitates the feasibility of real-time release testing (RTRT) and enhances drug product development and manufacturing efficiency by reducing the need for extensive sampling and testing. Moreover, APC strategies are required to address variations in raw material properties and process uncertainties while ensuring that desired critical quality attributes (CQAs) of in-process materials and final products are maintained. When deviations from quality targets are detected, APC must provide optimal real-time corrective actions, offering better control performance than the traditional open loop-control method. The progress in DT and APC is beneficial in shifting from the paradigm of Quality-by-Test (QbT) to that of Quality-by-Design (QbD) and Quality-by-Control (QbC), which emphasize the importance of process knowledge and real-time information to ensure product quality.</p> <p><br></p> <p>This study focuses on four key elements and their applications in a continuous dry granulation tableting process, including feeding, blending, roll compaction, ribbon milling and tableting unit operations. Firstly, the necessity of a digital infrastructure for data collection and integration is emphasized. An ISA-95-based hierarchical automation framework is implemented for continuous pharmaceutical manufacturing, with each level serving specific purposes related to production, sensing, process control, manufacturing operations, and business planning. Secondly, investigation of process analytical technology (PAT) tools for real-time measurements is highlighted as a prerequisite for effective real-time process management. For instance, the measurement of mass flow rate, a critical process parameter (CPP) in continuous manufacturing, was previously limited to loss-in-weight (LIW) feeders. To overcome this limitation, a novel capacitance-based mass flow sensor, the ECVT sensor, has been integrated into the continuous direct compaction process to capture real-time powder flow rates downstream of the LIW feeders. Additionally, the use of near-infrared (NIR)-based sensor for real-time measurement of ribbon solid fraction in dry granulation processes is explored. Proper spectra selection and pre-processing techniques are employed to transform the spectra into useful real-time information. Thirdly, the development of quantitative models that establish a link between CPPs and CQAs is addressed, enabling effective product design and process control. Mechanistic models and hybrid models are employed to describe the continuous direct compaction (DC) and dry granulation (DG) processes. Finally, applying APC strategies becomes feasible with the aid of real-time measurements and model predictions. Real-time optimization techniques are used to combine measurements and model predictions to infer unmeasured states or mitigate the impact of measurement noise. In this work, the moving horizon estimation-based nonlinear model predictive control (MHE-NMPC) framework is utilized. It leverages the capabilities of MHE for parameter updates and state estimation to enable adaptive models using data from the past time window. Simultaneously, NMPC ensures satisfactory setpoint tracking and disturbance rejection by minimizing the error between the model predictions and setpoint in the future time window. The MHE-NMPC framework has been implemented in the tableting process and demonstrated satisfactory control performance even when plant model mismatch exists. In addition, the application of MHE enables the sensor fusion framework, where at-line measurements and online measurements can be integrated if the past time window length is sufficient. The sensor fusion framework proves to be beneficial in extending the at-line measurement application from just validation to real-time decision-making.</p>

<p>  </p> <p>In the pharmaceutical industry, special care must be taken by companies to guarantee high quality medications that are free from byproducts and impurities. The development process involves various considerations including solvent selection, solubility screening, unit operation selection, environmental, and health impact evaluations. Traditionally, pharmaceutical manufacturing consisted of large, centralized facilities to meet pharmaceutical demands; however, there has been a recent shift toward distributed manufacturing. With distributed manufacturing platforms, rapidly changing supply chain needs can be met regionally in addition to supplying small-volume medications and personalized medicines to hospitals and pharmacies. To produce quality pharmaceuticals, distributed manufacturing platforms should integrate digital design, novel unit operations, and process analytical technology (PAT) tools for quality monitoring and control. In this dissertation, a process design and development framework is proposed and implemented for a small-scale pharmaceutical manufacturing platform: MiniPharm.</p> <p>Various approaches to process design are detailed in this dissertation, which include heuristic-based and digital or simulation-based design. For heuristic-based design, the knowledge of the researchers was utilized to provide unit operation evaluation and screening of process alternatives. In cases when unit operations were highly complex, digital or simulation-based design was utilized to conduct sensitivity analyses and simulation-based design of experiments. With the implementation of simulation-based design, material and time needs were reduced while gaining knowledge about the system. The integration of various unit operations comes with increased understanding of start-up dynamics and operational constraints. What was found to be the most successful approach was the combination of heuristics and digital design to combine researcher knowledge and experience with the information gained from process modeling and simulation to create process alternatives that utilized system dynamics to reach desired process outcomes. </p> <p>Additionally, MiniPharm was used for process model development at the small-scale. Various software packages have been made commercially available that focus on production scale; however, models for small-scale operations are not typically implemented in these packages. Models for unit operations were fit with collected experimental data to estimate model parameters for small-scale synthesis, liquid-liquid extraction, and crystallization unit operations. The models were implemented to better capture the heat and mass transfer of the milli-fluidic scale platform, which consist of unit operations housed within microchannels. MATLAB was utilized for estimation of parameters such as kinetic rate constants and overall mass transfer coefficients. These parameters were used for design space determination and process disturbance simulation. The exploration of the impact of various process parameters on quality attributes helps researchers gain a deeper understanding about the manufacturing process and helps to demonstrate how to control the process. </p> <p>An important aspect of MiniPharm is the process development progress that has been demonstrated. With the construction of a modular and reconfigurable platform, various process alternatives can now be experimentally validated. The integration of unit operations operated at a decreased scale makes MiniPharm an example of process intensification. The implementation of integrated unit operations decreases handling time of intermediates and reduces the overall footprint for manufacturing. Designed to allow for increased flexibility of operation, perfluoroalkoxy alkane (PFA) tubing was used for synthesis and purification. With PFA tubing clean in place procedures can be implemented using continuous solvent flow or the low cost, PFA tubing can be replaced. The modular nature of the platform also allows for the investigation of individual unit operations for performance evaluation. </p> <p>Finally, a novel continuous solvent switch distillation unit operation was designed and constructed along with customized reactor and crystallizers for process alternative screening for the synthesis and purification of two compounds: Diphenhydramine hydrochloride and Lomustine. Diphenhydramine hydrochloride is a low-value, high volume allergy medication commonly found in Benadryl and Lomustine is a high-value, low volume cancer medication used to treat glioblastoma and Hodgkin Lymphoma. The production of the compounds demonstrated the flexibility of the manufacturing platform to produce both a generic and a specialty medication. A versatile platform is needed for distributed manufacturing because of quickly changing supply chain needs. Overall, this dissertation successfully demonstrates the process design, development, and simulation for small-scale manufacturing.</p>

<p>Professional engineers think and act in distinctive ways when addressing engineering problems. Students need to develop this reasoning or engineering thinking during their education. Unfolding the undergraduate students’ thinking is a necessary step in designing experiences and teaching materials that foster not only their understanding of engineering concepts but also their learning to think as professional engineers. While there are previous studies about the students' thinking in other disciplines, more research is needed in engineering. This three-study dissertation aims to further our comprehension of undergraduate students’ engineering thinking using an adapted version of the Engineering Habits of Mind (EHoM) model. Specifically, the dissertation’s studies work together to continue the research that addresses the question:<em> What are the characteristics of undergraduate students</em>’ <em>engineering thinking?</em></p> <p><br></p> <p>The first study used naturalistic inquiry to holistically explore the cognition associated with the EHoM of senior chemical engineering students when improving a chemical plant. The analysis of students’ interactions showed that their redesign process followed an iterative co-evolution of the problem and solution spaces. Furthermore, they treated the task as a socio-technical problem considering engineering and non-engineering factors. In addition, while exploring problem and solution entities, they used multiple representations to communicate ideas but had difficulties translating symbolic representations into more physical, concrete representations. Regardless the technical issues and time constraints, the students completed the conceptual redesign and communicated their proposal to the client.</p> <p><br></p> <p>The second study used qualitative content analysis to examine first-year engineering students’ ideation as a cognitive skill associated with the EHoM of problem finding and creative problem solving. Particularly, it focused on students’ ideation of questions and recommendations when doing data analytics to help improve a client’s enterprise. The analysis of students’ reports showed that they expanded the problem space of the task by bringing additional information that was not provided. They asked questions focused on performing statistical analysis of the dataset and requesting information about the company’s business model. At the end of their data analytics, students made high- and low-quality recommendations considering their alignment with a specific problem, robust evidence, and the client’s needs. </p> <p><br></p> <p>The third study used qualitative descriptive research to investigate undergraduate participants' cognitive competencies within engineering systems thinking at the International Genetically Engineered Machine (iGEM) competition. These competencies are associated with the EHoM of problem finding, creative problem solving, systems thinking, and visualization. Mainly, the study focused on analyzing the evidence of cognitive competencies documented in the publicly available participants’ wikis where they registered their design process. Results showed that iGEM teams developed solutions with biological systems interacting with other systems and used concepts and tools from multiple disciplines. They also cooperated with stakeholders, which helped them analyze their system from multiple lenses. Moreover, depending on their upfront task, they fluidly represented their systems from structural, behavioral, and functional perspectives. </p> <p><br></p> <p>The final chapter of this dissertation presents an overarching discussion across the studies. The findings and implications will support curriculum designers, instructors, and other interested readers to prepare learning environments that promote undergraduate students’ engineering thinking. Furthermore, they may guide future efforts to continue exploring the students' thinking process when addressing engineering problems. </p>

<p>The present work is focused on the synthesis of small-scale (modular processes) to produce olefins from light alkane resources in shale gas.</p> <p>Olefins, which are widely used to produce important chemicals and everyday consumer products, can be produced from light alkanes - ethane, propane, butanes etc. Shale gas is comprised of light alkanes in significant proportion; and is available in abundance. Meanwhile, shale gas wells are small sized in nature and are distributed over many different areas or regions. In this regard, using shale gas as raw material for olefin production would require expensive transportation infrastructure to move the gas from the wells or local gas gathering stations to large central processing facilities. This is because existing technologies for natural gas conversions are particularly suited for large-scale processing. One possible way to take advantage of the abundance of shale resource for olefins production is to place small-sized or modular processing plants at the well sites or local gas gathering stations.</p> <p>In this work, new process concepts are synthesized and studied towards developing simple technologies for on-site and modular processing of light alkane resources in shale gas for olefin production. Replacing steam with methane as diluent in conventional thermal cracking processes is proposed to eliminate front-end separation of methane from the shale gas processing scheme. Results from modeling studies showed that this is a promising approach. To eliminate the huge firebox volume associated with thermal cracking furnaces and allow for a compact cracking reactor system, the use of electricity to supply heat to the cracking reactor is considered. Synthesis efforts led to the development of two electrically powered reactor configurations that have improved energy efficiency and reduced carbon footprints over and compare to conventional thermal cracking furnace configurations.</p> <p>The ideas and results in the present work are radical in nature and could lead to a transformation in the utilization of light alkanes, natural gas and shale resources for the commercial production of fuels and chemicals.</p>