Paper ID #49271Enhancing K-14 Education through the Study of Additive Manufactured BioinspiredLattice StructuresDr. Md B. Sarder, Bowling Green State University Dr. Sarder is a professor & director of the School of Engineering at Bowling Green State University (BGSU). Prior to joining BGSU, he worked at the U.S. Air Force Academy as a distinguished research fellow. He served as an associate professor, and graduate director of the logistics, trade, and transportation program at the University of Southern Mississippi (USM). Dr. Sarder has a record of excellence in research, teaching, and services as evidenced by the
geographic limitations [17]. This promotes accessibility andscalability, making it feasible for learners to engage with AM technology regardless of theirproximity to a physical lab facility. Consequently, innovative AM laboratories and remotelearning environments play a crucial role in teaching students’ practical skills and understandingAM processes and technologies. Some of the remote labs are shown in Figure 1. B) A) C) Figure 1: Three Innovative AM labs, A) Network camera accessible AM laboratory [18], B) Remotely accessible AM laboratory [19], C) Remote laboratory with 3D printers and
teams usethe same procedure to measure parallelism and flatness. The TA then demonstrates the use of laser displacement sensor (Fig. 1-l). He/shecompares the measured data using this non-contact technique against the data from a studentteam using contact-device such as dial indicator. Both advantages and disadvantages for eachtechnique are discussed among all teams. When time permits, students may use the laser systemfor their objects and compare the new measurement data against their previous data. a) Height gage b) Height gage with dial c) Indicator with flat base d) Dial indicator indicator with magnetic basee) T-bubble level f) Bulls-eye surface
conclusions sections of the study.There are no other conflicts of interest.Bibliography[1] L. C. Harrison, H. B. Congdon, and J. T. DiPiro, “The Status of US Multi-campus Colleges and Schools of Pharmacy,” American Journal of Pharmaceutical Education, vol. 74, no. 7, p. 124, Sep. 2010, doi: 10.5688/aj7407124.[2] C. Keulen and C. Sielmann, “Manufacturing Engineering as a Multi-Campus Program,” in Proceedings of the American Society for Engineering Education (ASEE), Minneapolis, MN, 2022.[3] S. L. Groenwald, “The challenges and opportunities in leading a multi-campus university,” Journal of Professional Nursing, vol. 34, no. 2, pp. 134–141, Mar. 2018, doi: 10.1016/j.profnurs.2017.12.005.[4] C. Sielmann, V. Chiu, and C. Keulen, “An
Paper ID #38110Development of a Product Pipeline System to Teach IndustrialManufacturing AutomationMr. Mina Morcos, Vaughn College of Aeronautics and Technology Mina Morcos is a senior student in Mechatronic Engineering at Vaughn College of Aeronautics and Tech- nology. He is an active member of multiple clubs such as Robotics, IEEE, SHPE, and NSBE. Also, he is A supplementary instructor for the course Microprocessors to assist students to understand how Micropro- cessors and Microcontroller work, also, assist students to Compile and Troubleshooting the pseudo-code on Arduino UNO boards.Dr. Shouling He, Vaughn College of
Paper ID #47802Improving Employer Engagement in a Manufacturing Professional WorkforceDevelopment ProgramDr. Zhen Zhao, Massachusetts Institute of Technology Zhen Zhao is a Postdoctoral Associate at the Massachusetts Institute of Technology. His research interests include developing scalable, collaborative, hands-on engineering curricula, skilling up manufacturing workforces, and growing engineering student competencies in mentorship and leadership.Dr. John Liu, Massachusetts Institute of Technology Dr. John Liu is the Director and Principal Investigator of the MIT Learning Engineering and Practice (LEAP) Group, which
focusing on an industrial press process. Case studies were developed usingAdobe Animate.Figure 1 shows the Problem Statement screens for both systems. The problem statementdescribes how the system should work and provides an illustration of the system with relevantparts labeled. (a) (b)Figure 1. Case study problem statement for (a) Widget Assembly Line; and (b) Industrial Press Figure 2. Setup Screen showing sequence of operations for industrial press Figure 3. Animation of industrial press in actionThe Problem Statement is followed by a Setup Screen that shows the sequence of operations.Figure 2 shows the Setup screen for the
. Display of angle measurements and equationsAs shown in Figure 5, learners can interact with the diagram by dragging points B, C, and Daround the circle, while point A remains fixed. As the points move, the application calculates anddisplays the angles in real-time. Manipulating points on the circle allows students to instantly seehow angles change and relate to each other.Students were provided links to the Interactive Angle Addition Simulator in Geogebra (Figure 4)and the Angle Simulator (Figure 5). Students explored and engaged with the simulators tofamiliarize themselves with the configurations. They used the simulators to answer the oddnumbered questions from the class worksheet (Figure 6). Figure 4: Angle Addition
) Provide instructions for Internet access, confirm access to part files Safety reminders Closed toe shoes and safety glasses should be worn at all times in the machining laboratory Long hair/loose clothing should be tied back/tucked in Machined parts and cutting tools can be sharp; handle with care Foundry safety Compressed air warning Safety walk of the lab and foundry Safety training signature form (CANVAS) Leather boot casting video (CANVAS) Sneaker casting video (CANVAS) Distribute binders IACMI photo release form (CANVAS)10:00 am – Group sessions Group A-A1 Casting design (Solidification modeling and flow modeling) Group B-A5 CAD/CAM, Fusion
Paper ID #38816Design and Evaluation of Modules to Teach PLC Interfacing ConceptsDr. Sheng-Jen Hsieh, Texas A&M University Dr. Sheng-Jen (”Tony”) Hsieh is a Professor in the Department of Engineering Technology and Industrial Distribution and a member of the Graduate Faculty at Texas A&M University, College Station, TX. His research interests include automation, robotics, cyber-manufacturing and Industry 4.0; optical/infrared imaging and instrumentation; micro/nano manufacturing; and design of technology for engineering ed- ucation. He is also the Director of the Rockwell Automation Laboratory at Texas A&M
Mechanical and Aerospace Engineering at the Old Dominion University. Dr. Kaipa received his BE (Hons.) ©American Society for Engineering Education, 2023 Development of a SimEvents Model for Printed Circuit Board (PCB) Assembly ProcessAbstractIndustry 4.0 creates numerous opportunities while at the same time it imposes challenges toworkforce development to take full advantage of emerging technologies and processes that areenabling new era of manufacturing. One of the key enabling technologies is Digital Twin,which is a foundation of smart and flexible manufacturing. Digital twin provides severalcapabilities to engineers: (a) what-if analysis during design process, (b) predictive
real-world projects in the engineering classroom. • Limited approaches to connect theory and practiceIn addition to above problematic areas, during several SWOT analysis sessions of the EngineeringTechnology curriculum, conducted with Engineering Technology Curriculum Committee members andET faculty plenum, several curricular and competencies gaps have been identified. The gaps related tothis investigation are as follows: a) Students’ ability to formulate clear problem statements and to select solutions to meet specifications is poor. b) Students’ lack the sufficient depth of understanding in upper-level courses. c) Students’ ability to communicate and justify engineering decisions is poor.Students in the Mechanical
setsTto analyse and discuss. All datasets show the same distribution “A” which represents the idealized distribution of the mass of midsoles produced over a six month time frame about a year in the past. This type of data is representative of actual inspection processes where weight is monitored for process control. Each graph has a unique data set “B” which represents a newer set of data for the student to compare and discuss.The following competencies were emphasized in this oral assessment: ● Manufacturing processes: Identifying the manufacturing processes and providing observations or reasoning to support conclusions. Articulating how key features of the object would change if it were made
the MET3060 course for Spring 2022 and Fall 2022AcknowledgmentsService Learning practices held at the CNC Machining Practices course were funded by theESCL@Te Program. This support is greatly appreciated.References[1] M. Salam, D. N. Awang Iskandar, D. H. A. Ibrahim, and M. S. Farooq, “Service learning in higher education: a systematic literature review,” Asia Pacific Educ. Rev., vol. 20, no. 4, pp. 573–593, Feb. 2019, doi: 10.1007/s12564-019-09580-6.[2] I. Fidan, B. Barger, E. Obuz, S. M. Bagdatli, I. Anitsal, and M. Anitsal, “Integrating manufacturing, management and marketing into international service learning,” 2013 ASEE Annu. Conf. Expo. Conf. Proc., doi: 10.18260/1-2--19791.[3] M. M. Anitsal, I. Anitsal
, SD = 2.83 years) participated in the study (see Figure 16a). Participants wereengineering students with no or varied levels of prior VR experience (see Figure 16b). The studywas approved by the University of Louisville Institutional Review Board (IRB) #22.1089.Participants worked in the virtual factory in groups of three. Participants were provided with abrief introduction about the study, the VR environment, the use of VR headsets and controllers,the eye tracker, and wearable sensors. Participants read and signed an informed consent form andfilled out the demographic survey and pre-experiment surveys. a) b) Figure 16. a) Age distribution of participants and b) distribution of VR familiarity
). This trigger causes the conveyor to stop, and the vision camera to take Figure 2: Work Cell Layout a picture of the part. The camera then sends a signal to the robot, if the part is acceptable, to pick up the part (Figure 3, b). The robot then puts the part in the already open CNC enclosure and thealready open clamping mechanism (Figure 3, c). Once the robot closes the sliding door, theclamp tightens, and the CNC program begins (Figure 3, d). When the CNC program is complete,it activates a limit switch to send the signal that the program is done. The robot then opens thedoor (Figure 3, e), the clamp loosens, the robot picks the part (Figure 3, f) and performs the finalstep of placing it in the finished part
instructional method. The results could possibly contribute tothe body of research in this area and be of potential significance to industries that rely on remoteor virtualized training programs.References[1] V. Román-Ibáñez, F. Pujol-López, H. Mora-Mora, M. Pertegal-Felices, and A. Jimeno- Morenilla, “A low-cost immersive virtual reality system for teaching robotic manipulators programming,” Sustainability, vol. 10, no. 4, Apr. 2018. doi:10.3390/su10041102[2] I. Verner, D. Cuperman, H. Perez-Villalobos, A. Polishuk, and S. Gamer, “Augmented and virtual reality experiences for learning robotics and training integrative thinking skills,” Robotics, vol. 11, no. 5, Sep. 2022. doi:10.3390/robotics11050090[3] B. Thormundsson, “Average
for manufacturing training. Quantitative data are analyzed usingstatistical methods, while qualitative data are examined through LDA topic modeling, an NLPapproach.3. XR Environments for Manufacturing TrainingTwo immersive environments, VR and MR, are designed with an interactive module centered onthe assembly tasks of a hydrostatic bike. This bike was chosen for its complex mechanical designand hydraulic circuit, making it suitable for teaching assembly practices. Its mechanicalstructure, shown in Figure 1, consists of highly coupled subsystems: (A) Front-Lower Assembly,(B) Back-Upper Assembly, (C) Back-Lower Assembly, and (D) the Bike Frame. Thecomprehensive nature of the bike system allows for the exploration of various UI controls
adolescents. Otolaryngology—Head and Neck Surgery, 140(4), 461-472.[4] Smith, A. (2003, October). Preventing deafness—an achievable challenge. The WHO perspective. In International Congress Series (Vol. 1240, pp. 183-191). Elsevier.[5] WHO, WHO calls on private sector to provide affordable hearing aids in developing world, WHO/34, 11 July 2001.[6] Olusanya, B. O., Neumann, K. J., & Saunders, J. E. (2014). The global burden of disabling hearing impairment: a call to action. Bulletin of the World Health Organization, 92, 367-373.[7] Chia, E. M., Wang, J. J., Rochtchina, E., Cumming, R. R., Newall, P., & Mitchell, P. (2007). Hearing impairment and health-related quality of life: the Blue Mountains Hearing Study. Ear and hearing
machine a part. The first example were two diameters on a turned partwhich needed to be concentric to each other within .002 of an inch, as seen in Figure 5 below.Students were then asked to pick all applicable answers to how the part might be manufacturedto help meet the concentricity requirements; a - use the first 2.000in diameter machined as areference for a second diameter, b - use the same tool and machine both diameters, c- machineboth 2.000in diameters in the same setup, d - does not matter because diameters are on the samecenter axis, or e - all of the above. Answers a and c would be correct, as the concentricity calloutcontrols where the center axis of each diameter is relative to each other, not how the diameters ofeach feature turned
1 $45.99 Hosyond 7 Inch IPS LCD Touch Screen Display Panel 1024×600 Capacitive Screen HDMI Monitor for Raspberry Pi, BB Black, Windows 10 8 7 Cable 1 $8.99 USB-C to USB A Cable 3.1A Fast Charging [2-Pack 6.6ft], JSAUX USB Type C Charger Cord Screen case holder 1 $13.99 Longruner 7-inch Raspberry Pi Touch Screen Case Holder for Raspberry Pi 3 2 Model B and RPi 1 B+ A BB Black PC Various Systems LSC7B-1Computer Vision Application DesignRoboflow, a tool for building computer vision applications that utilizes open-source computervision models, was used to recognize the color of candy [6]. The Python
fed into a manufacturing process. The manufacturing processtransforms the inputs into a completed workpiece, along with scrap and waste, using theinstructions programmed into its control system. Figure 2(a) illustrates the relationship of thesecomponents. For example, sheets of metal (input) fastened by fixtures (input), feed into awelding process, during which an industrial robot welds the sheets to form an automobile bodyframe based on the instructions from a control system. Outputs include completed auto bodyframes and scraps.A cyber-physical system (CPS) is comprised of physical, cyber, and control systems. Figure 2(b)shows these concepts as applied to manufacturing. The physical system refers to the machine andthe wireless sensors used
Paper ID #38093A New Course in Defense Manufacturing – An Introduction to ShipbuildingDr. Alley C. Butler, University of Texas Rio Grande Valley Alley C. Butler received his BS degree in Mechanical Engineering and was commissioned into the US Navy in 1973. After serving as a Naval Officer in the Pacific Fleet for five years, he worked in industry for eight years, and earned an MBA degree. He earned his MS and PhD degree from Purdue University in 1988 and 1992 respectively. He has been a faculty member in engineering since that time. He is presently a Professor of Manufacturing and Industrial Engineering at the University of
Paper ID #42042Design of a Monitoring System for CNC-Machining ProcessesDr. Zhenhua Wu, Virginia State University Dr. Zhenhua Wu, is currently an Associate Professor in Manufacturing Engineering at Virginia State University. He received his PhD in Mechanical Engineering from Texas A&M University. His current research interests focus on cybermanufacturing, friction stir welding.Dr. Pamela Leigh-Mack, Virginia State University Dr. Pamela Leigh-Mack is Professor of Computer Engineering, and Director of Assessment for the College of Engineering and Technology at Virginia State University. She received the B.S. degree in
Paper ID #48131Maker: Design an Application Software for a 3D printer Based on MTConnectOluwadamilola Daniel Afe, Virginia State UniversityDr. Zhenhua Wu, Virginia State University Dr. Zhenhua Wu, is currently an Associate Professor in Manufacturing Engineering at Virginia State University. He received his PhD in Mechanical Engineering from Texas A&M University. His current research interests focus on cybermanufacturing, friction stir welding. ©American Society for Engineering Education, 2025 MAKER: Design an Application Software for a 3D printer Based on MTConnect