environment.The objective of the study is to answer the questions: (1) Which factors affect the systemperformance measures and to what extent? and (2) can optimal settings be identified for thesystem to perform consistently over the range of the extraneous noise variable? To do this,Taguchi experiments will be utilized, along with Signal to Noise (S/N) ratios and factorial plots,to analyze the results. The aim of this paper is to introduce the application of quality controlmethods in performance optimization for an automated electrohydraulic position control system.The system setup, hardware, software, and programming will be introduced. The researchdesign, measurements, and experimental runs will be demonstrated and explained. The impact onstudents
consistency is dependent of cycle time.RTR analysis is based on programming the robot to move during a particular path design. The programcontent is to run at different setups of speeds and terminations as follows: (1000 mm/s @ 0% CNT),(1000 mm/s @ 100% CNT), (2000 mm/s @ 0% CNT), and (2000 mm/s @ 100% CNT). This research paperarranged in the following manner that section 2 for the variables analysis and section 3 results andanalysis and section 4 is to conclude the findings and record the recommendations for the future work.2. Programming Variables AnalysisIn order to understand the problem of the correlation between cycle time and consistency with otherrobot variables it should first be realized what variables that we are analyzing. Variables
digital design experience [7]. In addition, SmartManufacturing education further requires data collection and management systems that allow forexploration of data analysis and feedback as demonstrated by [8]. In order to provide a relativelylow-cost training platform for a relatively challenging control problem, D. Kim and B. Anthonydemonstrated a benchtop fiber extrusion system for educational training [9]. This FibeRExtrusion Device, FrED, provided a process that would benefit from complex process control,while also being straightforward to analytically model and test. Recently, S. Kim et al. showedhow deep reinforcement machine learning could even be applied to the feedback control for thisdevice for improving fiber quality [10]. These
model to show therobot position within the work envelope; and 7) provide haptic feedback.AcknowledgementsThis material was supported by the National Science Foundation’s Advanced TechnologyEducation Program (award no. 1304843). Any opinions, findings, and conclusions orrecommendations expressed in this material are those of the author and do not necessarily reflectthe views of the National Science Foundation.Bibliography[1] Aburdene, M. F., Mastascusa, E. J., and Massengale, R. “A proposal for a remotely shared control systems laboratory”, In Proceedings of the Frontiers in Education 21st Annual Conference.West Lafayette, IN. 589–592, 1991.[2] Gomes, L., and Bogosyan, S., "Current Trends in Remote Laboratories," in IEEE Transactions on
, S., "Current Trends in Remote Laboratories," in IEEE Transactions on Industrial Electronics, vol. 56, no. 12, pp. 4744-4756, Dec. 2009.[3] Grodotzki, J., Ortelt, T.R. and Tekkaya, A.E., 2018. Remote and Virtual Labs for Engineering Education 4.0: Achievements of the ELLI project at the TU Dortmund University. Procedia Manufacturing, 26, pp.1349-1360, 2018.[4] Hsieh, S. “Design of Remotely Accessible Automated Systems to Enhance Industrial Automation Education,” ASEE 2017 Annual Conference, June 25 - 28, Columbus, Ohio.[5] Hsieh, S. “Development of Remote Virtual Teaching Pendant for Robot Programming: Lessons Learned,” ASEE 2019 Annual Conference, June 16-19, 2019, Tampa, FL.[6] Hsieh, S. “Lessons Learned from Remote
] Spencer, O. O., Yusuf, O. T., & Tofade, T. C. (2018). Additive manufacturing technologydevelopment: a trajectory towards Industrial Revolution. Am. J. Mech. Ind. Eng, 3(5), 80-90.[7] Sunny, S. N. A., Liu, X. F., & Shahriar, M. R. (2018). Communication method formanufacturing services in a cyber–physical manufacturing cloud. International Journal ofComputer Integrated Manufacturing, 31(7), 636-652. © American Society for Engineering Education, 2021 2021 ASEE Annual Conference & Exposition[8] Khanuja, S. S. (1996). Origin and control of anisotropy in three dimensional printing ofstructural ceramics (Doctoral dissertation, Massachusetts Institute of Technology).[9] Eyles, A., Gibbons, S
levels have been exposed to modular robots andindustrial robot configurations by possibly redesigning the configurations, rebuilding them, andprogramming them through C programming language.References[1] Hirose, S. (1993). Biologically inspired robots: snake-like locomotors and manipulators. New York, NY: Oxford Press.[2] Fukuda, T., & Kawauchi, Y. (1990). Cellular robotic system (CEBOT) as one of the realization of self- organizing intelligent universal manipulator. Paper presented at the IEEE International Conference on Robotics and Automation, Cincinnati, OH. doi: 10.1109/ROBOT. 1990.125924[3] Lund, H. H. (2013, December). Lessons learned in designing user-configurable modular robotics. Paper presented at the RiTA 2013
different states and other schools.References: 1. R.E. Stamper, D.L. Dekker, Utilizing rapid prototyping to enhance undergraduate engineering education, in: 30th Annu. Front. Educ. Conf., IEEE, Kansas City, USA, 2000: pp. 1–4. doi:10.1109/FIE.2000.896570.2. S.S. Horowitz, P.H. Schultz, Printing Space: Using 3D Printing of Digital Terrain Models in Geosciences Education and Research, J. Geosci. Educ. 62 (2014) 138–145. doi:10.5408/13‐031.1.3. L. Chong, S. Ramakrishna, S. Singh, A review of digital manufacturing‐based hybrid additive manufacturing processes, Int. J. Adv. Manuf. Technol. 95 (2018) 2281–2300.4. O. Ivanova, C. Williams, T. Campbell, Additive manufacturing (AM) and nanotechnology: promises and challenges, Rapid
,reviewstatusandprintertechnology.TheresourcesavailableonthisNIHsitehelpsusanswersomecriticalquestionsregarding: 1. Appropriateguidanceforproduction/useofPPE:Inadditiontogeneralinformation, production/assembly instructions, designer(s) name or affiliation, and appropriate documentation; the NIH exchange also provides reviewer notes to guide appropriate fabrication.Forexample,theStopgapSurgicalFaceMask(SFM)RevisionBincludesthe followingnotes: “TheFDAhasauthorizedproductionofprotectivefacemasksoutsideofthenormal clearancepathwayduringtheCOVID-19pandemic,basedonPart5,sectionEofthe “EnforcementPolicyforFaceMasksandRespiratorsDuringtheCoronavirus Disease(COVID-19)PublicHealthEmergencyGuidanceforIndustryandFoodand DrugAdministrationStaff."Thissurgicalfacemaskhasbeentestedclinicallyand
Paper ID #34468Best Practices for Attracting Young Talent to the Pennsylvania and U.S.Metalcasting IndustryC. R. Hasbrouck, Pennsylvania State University C. R. Hasbrouck is a graduate research assistant and doctoral candidate in the Department of Industrial and Manufacturing Engineering Department at Penn State. C. R. received a B.S. in Mechanical Engi- neering from Trine University, a M.S. in Mechanical Engineering from Colorado School of Mines, a M.S. in Industrial Engineering from Penn State University, and is currently finishing a Ph.D. in Indus- trial Engineering. Most of C. R.’s research is for ferrous alloy
the supply chain, digitalization of enterprise, and leanbased cost-optimization exercises, etc.b) Project on “material selection and manufacturing processes” for aircraft enginesAs shown in below Figure 1, a turbofan aircraft engine is typically composed of an air intake fan,compressors, a combustion chamber, turbines, and a nozzle. The typical material candidates in theturbofan aircraft engine are tabulated in Table 1.Students were asked to identify a component to study, and then deliver a presentation and a paperon: 1) component(s) and its function, 2) material candidates, 3) material properties (mechanical,physical, thermal properties etc.) of materials to be selected, 4) manufacturing processes tofabricate the component with selected
Forum, American Society for Engineering Education, New Orleans, LA, USA (June 2016)K. Arrow, "Economic welfare and the allocation of resources for invention," 1962.L. Lee and P.-K. Wong, "Attitude towards entrepreneurship education and new venture creation," J. Enterprising Culture, vol. 11, no. 04, pp. 339–357, Dec. 2003.M. Feldman, J. Francis, and J. Bercovitz, "Creating a Cluster While Building a Firm: Entrepreneurs and the Formation of Industrial Clusters," Regional Studies, vol. 39, no. 1. pp. 129–141, 2005, doi: 10.1080/0034340052000320888.P. Brown, "The opportunity trap: Education and employment in a global economy," European Educational Research Journal, 2003.N.Pasha-Zaidi, E., Afari, J.Mohammed, S
1Evaluation FindingsThe External Project Evaluator designed a retrospective pretest survey instrument to assessseveral aspects of the workshops including satisfaction with the overall workshop logistics,content, delivery methods, and the effectiveness of the workshops. The instruments also hadsections which assessed specific workshop objectives, and participants were asked to rate theirperceived improvement on (i) their level of understanding of AM or SM concepts, (ii)proficiency level on a number of skills demonstrated during the workshop, (iii) the extent towhich they felt the workshop objectives had been met, and (iv) the relevance of the content totheir work. The instrument(s) contained both closed-ended and open-ended questions.All workshop
-02R, 2007.[7] “COVID-19 Protocol,” NJIT Makerspace, Sep. 08, 2020.https://www.njitmakerspace.com/covid-19-protocol.[8] K. A. A. Gamage, D. I. Wijesuriya, S. Y. Ekanayake, A. E. W. Rennie, C. G. Lambert, andN. Gunawardhana, “Online Delivery of Teaching and Laboratory Practices: Continuity ofUniversity Programmes during COVID-19 Pandemic,” Education Sciences, vol. 10, no. 10, p.291, Oct. 2020, doi: 10.3390/educsci10100291.[9] J. Li, J. Ramos_Salas, and C. Li, “Experience of Teaching Introduction to ElectricalEngineering with an Online Platform,” East Lansing, Michigan, Jul. 2020, p. 8, [Online].Available: https://strategy.asee.org/35758.[10] N. Kapilan, P. Vidhya, and X.-Z. Gao, “Virtual Laboratory: A Boon to the MechanicalEngineering Education
this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.Reference[1] Chandramouli, M., & Jin, G., & Heffron, J. D., & Fidan, I., & Cossette, M., & Welsch, C. A., &Merrell, W. (2018, June), Virtual Reality Education Modules for Digital ManufacturingInstruction, Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah.10.18260/1-2—31225[2] El-Mounayri, H. (2005, June), Virtual Manufacturing Laboratory for Training andEducation, Paper presented at 2005 Annual Conference, Portland, Oregon. 10.18260/1-2--15154[3] Yingxue Yao, Jianguang Li, Changqing Liu, A Virtual Machining Based Training System ForNumerically Controlled Machining
, 19 Sept. 2019, xd.adobe.com/ideas/principles/emerging-technology/virtual-reality-will-change-learn-teach.[2] Fletcher, C., Ritchie, J. M., and Lim, T., “Virtual machining and expert knowledge capture. Paper presented at Digital Engagement 2011, Newcastle, United Kingdom.[3] Mujber, T. S., T. Szecsi, and Hashmi, M. S. J., “Virtual reality applications in manufacturing process simulation,” Journal of Materials Processing Technology, 2004, p. 1834-1838.[4] Yap, H. J., Taha, Z., and Lee, J. V., “VR-based Robot Programming and Simulation System for an Industrial Robot,” International Journal of Industrial Engineering – Theory, Application and Practice. 15 (3), 2008, pp. 314-322.[5] Engineering, Leadership
," Materials & Design, vol. 23, no. 7, pp. 651-656, 2002.[2] B. Klefsjö, H. Wiklund, and R. L. Edgeman, "Six Sigma seen as a methodology for total quality management," Measuring business excellence, 2001.[3] A. Gungor and S. M. Gupta, "Issues in environmentally conscious manufacturing and product recovery: a survey," Computers & Industrial Engineering, vol. 36, no. 4, pp. 811- 853, 1999.[4] C. Sherwin, "Design and sustainability," The Journal of Sustainable Product Design, vol. 4, no. 1, pp. 21-31, 2004.[5] M. Peruzzini and M. Germani, "Design for sustainability of product-service systems," International Journal of Agile Systems and Management 20, vol. 7, no. 3-4, pp. 206-219, 2014.[6] T
largest manufacturer, is on the verge of using 3- D printing to make jet parts. MIT Technology Review,” Available Online: https://www.technologyreview.com/s/513716/additive-manufacturing/.[5] R. Agarwala and R. A. Chin, “Facilitating additive manufacturing engagement and outreach,” ASEE Annu. Conf. Expo. Conf. Proc., vol. 122nd ASEE, no. 122nd ASEE Annual Conference and Exposition: Making Value for Society, 2015, doi: 10.18260/p.24086.