Nancy Diaz-Elsayed

The preservation and continuous monitoring of cutting tools in a computer numerical control (CNC) machine is essential for ensuring seamless transitions in the manufacturing workflow, as well as maintaining adequate part quality. The implementation of tool condition monitoring (TCM) when milling can provide the user with necessary data regarding tool life, wear, and part quality. However, it is important to broaden the application of the TCM process across a much broader class of workpiece materials to understand the effects of material properties on the condition of the tool. The aim of this paper is to investigate the efficacy of tool condition monitoring techniques while milling low- and high-yield-strength materials across varied process parameters. A Fast Fourier Transform (FFT) analysis was conducted in this research. Vibration data were acquired from both uniaxial and triaxial accelerometers to investigate irregularities in vibrational amplitudes between new and worn milling tools. The experimental results show that there is a significant increase in vibrational amplitudes for the worn tool when compared to the new tool across various frequencies, which affirms the expected increase in vibrations and cutting forces at the tool–workpiece interface from using a worn tool. The F-values and p-values calculated using an F-test with a 95% confidence interval indicated statistically significant differences in vibration data between new and worn tools across various materials, including polyurethane foam, aluminum 6061, mild steel, and stainless steel, under different cutting conditions (low, medium, and high). These results further validate the findings obtained from the FFT analysis and highlight the effectiveness of vibration-based monitoring in distinguishing tool wear under varying material characteristics and machining conditions.

In 2016, only 7 percent of African American and Hispanic students earned research doctorates in the critical disciplines of engineering, computing, and the physical sciences. In academia, diversity fairs even worse as historically underrepresented minorities represented just 6.1 percent of tenured and tenure-track faculty in engineering. The aim of this effort is to understand the “best practices” for the recruitment and mentoring of minority doctoral students in science and engineering disciplines. This was achieved through a literature review, surveys and focus groups with members of the University of South Florida’s (USF’s) Sloan University Center of Exemplary Mentoring (UCEM), and interviews with faculty champions. Between 2005 and 2020, 136 graduate students have been supported (43% African American, 56.2% Hispanic, 0.8% Native American), of which 87 percent are expected to earn doctorate degrees. Results indicate that the decision to apply and enroll at USF was largely driven by the alignment of research interests with potential advisors, the quality of funding, and positive interactions with mentors, enrolled students, and alumni who provide evidence of a welcoming climate. Ten practices for mentoring doctoral students are provided, which include creating and promoting an inclusive environment and providing a student-centered approach to mentoring. Our effort to build inclusive excellence and foster social justice in graduate education for African American and Hispanic doctoral students in science, technology, engineering, and mathematics (STEM) is one that can be modeled and adapted by other institutions to align with their institutional culture and values.

The availability of sufficient water supply is a challenge many municipalities have faced in recent decades and a challenge that is expected to intensify with time. While several choices remain for selecting alternatives to freshwater sources, water reclamation offers an opportunity for sustainable resource recovery. Nonetheless, tradeoffs exist in the selection of the most sustainable technology for recovering resources from wastewater when long-term impacts are taken into consideration. This article investigates the factors influencing the environmental and economic impacts of resource recovery technologies through the analysis of life cycle environmental and economic impact case studies. Key characteristics were extracted from life cycle assessment and life cycle cost case studies to evaluate the factors influencing the sustainability of the resource recovery systems. The specific design parameters include the type of resources to be recovered, technology utilized, scale of implementation, location, and end users. The design of sustainable resource recovery systems was found to be largely driven by scale, location (e.g., as it pertains to the energy mix and water quality restrictions), and the scope of the system considered. From this analysis, a decision framework for resource recovery-oriented wastewater management was developed and then applied to an existing case study to demonstrate its usability.