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Research Experience for Undergraduates (REU) programs have been credited for attracting and retaining students in science and engineering who otherwise may not have considered disciplines in science and engineering as their career choices. In addition to core research activities, REU programs generally provide multiple enrichment and professional development activities for participants. While the nature and the number of professional development activities vary from one REU program to another, the most common activities include ethics and safety training, research and industry seminars, GRE workshops, writing workshops, graduate school application preparation, and industry visits. Furthermore, some of these professional development activities are also conducted in large group settings with students from other research programs beyond the REU cohort. The rationale behind combining REU students with other researchers is to create a community of learners and provide them with an opportunity to build/extend their professional network. Although professional development activities are an integral part of the REU sites, there is often very limited coverage of such activities in the existing literature on REU projects. This paper presents the impact of professional development activities on the experience of REU participants in a manufacturing REU site at a major research university in the southwestern United States. For this study, data was collected from participants by an external evaluator by using both qualitative and quantitative methods. This paper presents and describes the cumulative data from three REU cohorts. The analysis and results of the data are disaggregated by the student academic level (sophomore, junior, senior), gender, ethnicity, the type of their home institutions (research or teaching institution), and desired career paths in the future (graduate school or industry). The paper also provides a detailed discussion and implications of these findings. 

In many modern enterprises, factory managers monitor their machinery and processes to prevent faults and product defects, and maximize the productivity and efficiency. Asset condition, product quality and system productivity monitoring consume some 40-70% of the production costs. Oftentimes, resource constraints have prevented the adoption and implementation of these practices in small businesses. Recent evolution of manufacturing-as-a-service and increased digitalization opens opportunities for small and medium scale companies to adopt smart manufacturing practices, and thereby surmount these constraints. Specifically, sensor wrappers that delineate the specifications of sensor integration into manufacturing machinery, with appropriate edge-cloud computing and communication architecture can provide even small businesses with a real-time data pipeline to monitor their manufacturing machines. However, the data in itself is difficult to interpret locally. Additionally, proprietary standards and products of the various components of a sensor wrapper make it difficult to implement a sensor wrapper schema. In this paper, we report an open-source method to integrate sensors into legacy manufacturing equipment and hardware. We had implemented this pipeline with off-the-shelf sensors to a polisher (from Buehler), a shaft grinding machine (from Micromatic), and a hybrid manufacturing machine (from Optomec), and used hardware and software components such as a National Instruments Data Acquisition (NI-DAQ) module to collect and stream live data. We evaluate the performance of the data pipeline as it connects to the Smart Manufacturing Innovation Platform (SMIP)—web-based data ingestion platform part of the Clean Energy Smart Manufacturing Innovation Institute (CESMII), a U.S. Department of Energy-sponsored initiative—in terms of data volume versus latency tradeoffs. We demonstrate a viable implementation of Smart Manufacturing by creating a vendor-agnostic web dashboard that fuses multiple sensors to perform real-time performance analysis with lossless data integrity. 

Elastomers often exhibit large stretchability but are not typically designed with robust energy dissipating mechanisms. As such, many elastomers are sensitive to the presence of flaws: cracks, notches, or any other features that cause inhomogeneous deformation significantly decrease the effective stretchability. To address this issue, we have dispersed voids into a silicone elastomer matrix, thereby creating a “negative” composite that provides increased fracture resistance and stretchability in pre-cut specimens while simultaneously decreasing the weight. Experiments and simulations show that the voids locally weaken the specimen, guiding the crack along a tortuous path that ultimately dissipates more energy. We investigate two geometries in pre-cut specimens (interconnected patterns of voids and randomly distributed discrete voids), each of which more than double the energy dissipated prior to complete rupture, as compared to that of the pristine elastomer. We also demonstrate that the energy dissipated during fracture increases with the volume fraction of the voids. Overall, this work demonstrates that voids can impart increased resistance to rupture in elastomers with flaws. Since additive manufacturing processes can readily introduce/pattern voids, we expect that applications of these elastomer–void​ “composites” will only increase going forward, as will the need to understand their mechanics. 

Advancements in information technology and computational intelligence have transformed the manufacturing landscape, allowing firms to produce highly complex and customized product in a relatively short amount of time. However, our research shows that the lack of a skilled workforce remains a challenge in the manufacturing industry. To that end, providing research experience to undergraduates has been widely reported as a very effective approach to attract students to industry or graduate education in engineering and other STEM-based majors. This paper presents assessment results of two cohorts of Cybermanufacturing REU at a major university. Students were recruited from across the United States majoring in multiple engineering fields, such as industrial engineering, mechanical engineering, chemical engineering, mechatronics, manufacturing, and computer science. Several of the participants were rising sophomores or juniors who did not have any industry internship or prior research experience. In total 20 students (ten per year) participated in the program and worked on individual project topics under the guidance of faculty and graduate student mentors. Unlike a typical REU program, the Cybermanufacturing REU involved a few unique activities, such as a 48-hour intense design and prototype build experience (also known as Aggies Invent), industry seminars, and industry visits. Overall, the REU students demonstrated significant gains in all of the twelve research-related competencies that were assessed as a part of formative and summative evaluation process. While almost all of them wanted to pursue a career in advanced manufacturing, including Cybermanufacturing, the majority of the participants preferred industry over graduate school. The paper provides an in-depth discussion on the findings of the REU program evaluation and its impact on undergraduate students with respect to their future plans and career choice. The analysis is also done by gender, ethnicity, academic level (sophomore, junior, senior), and type of home institution (e.g., large research universities, rural and small schools) to explore if there was any significant difference in mean research competency scores based on these attributes. 

Recent advancements in sensors, device manufacturing, and big data technologies have enabled the design and manufacturing of smart wearables for a wide array of applications in healthcare. These devices can be used to remotely monitor and diagnose various diseases and aid in the rehabilitation of patients. Smart wearables are an unobtrusive and affordable alternative to costly and time-consuming health care efforts such as hospitalization and late diagnosis. Developments in micro- and nanotechnologies have led to the miniaturization of sensors, hybrid 3D printing of flexible plastics, embedded electronics, and intelligent fabrics, as well as wireless communication mediums that permit the processing, storage, and communication of data between patients and healthcare facilities. Due to these complex component architectures that comprise smart wearables, manufacturers have faced a number of problems, including minimum sensor configuration, data security, battery life, appropriate user interfaces, user acceptance, proper diagnosis, and many more. There has been a significant increase in interest from both the academic and industrial communities in research and innovation related to smart wearables. However, since smart wearables integrate several different aspects such as design, manufacturing, and analytics, the existing literature is quite widespread, making it less accessible for researchers and practitioners. The purpose of this study is to narrow this gap by providing a state-of-the-art review of the extant design, manufacturing, and analytics literature on smart wearables-all in one place- thereby facilitating future work in this rapidly growing field of research and application. Lastly, it also provides an in-depth discussion on two very important challenges facing the smart wearable devices, which include barriers to user adoption and the manufacturing technologies of the wearable devices. 

Abstract Nanocomposites have been widely used to improve material properties. Nanoscale reinforcement materials in vat photopolymerization resins improve the hardness, tensile strength, impact strength, elongation, and electrical conductivity of the printed products. This paper presents a literature review on the effects of reinforcement materials on nanocomposite properties. Additionally, preprocessing techniques, printing processes, and postprocessing techniques of nanocomposites are discussed. The nanocomposite properties are summarized based on their applications in the mechanical, electrical and magnetic, and biomedical industries. Future research directions are proposed to improve the material properties of printed nanocomposites. 

Recent advancements in information, wire¬less sensing, data analysis, and 3-D printing technologies are transforming manufacturing into a highly customized process, with a short time to market, and a competitive cost structure to sustain businesses in a highly globalized market. Central to this emerging paradigm is cybermanufacturing which is a critical technology that combines the above-mentioned recent advances in technologies to transform manufacturing into essentially a commoditized "cloud-based service". Likewise, it has the poten¬tial to evoke creativity of the general population to design and create personalized products. To that end, one of the key enablers of this paradigm is the recruitment and training of a new class of manufacturing workforce that can (1) combine engineering product design capabilities with information technology tools to convert ideas into components and (2) transform a wide range of precursor materials into products to meet advanced functional requirements by using cyber-enabled machine tools. However, many students, particularly those at predominantly undergraduate institutions (UGI) and minority-serving institutions (MSI), have not been exposed to advanced or cyber-based manufacturing research and education. This paper presents a case study of NSF-funded summer research experience for undergraduates (REU) site in cybermanufacturing. The paper describes the student recruitment process, demographic information of the most recent cohort, sample student projects, and other enrichment activities that were organized during the 10-week summer REU program. As a part of program evaluation, the participants were surveyed before and after the REU experience. The survey questions covered a wide range of topics including their scientific research knowledge and skills, career knowledge and interest, and professional skills. Survey results from 2018 cohort shows that REU experience was not only very helpful for students in deciding the manufacturing as their career path but it also improved their research competency.