worked extensively in the domain of welding, specifically in the area of weld- ing technology and training. He has a deep appreciation for the importance of the welding field and plan to continue pursuing research projects that benefit the welding community.Ms. Audrey Fyock, Iowa State University Audrey Fyock is a senior in Industrial and Manufacturing Systems Engineering and first year Master of Business Administration student at Iowa State University. This is her first year doing an undergraduate research assistantship with the IMSE Department, where she is studying the impacts of undergraduate research on retention rates and graduate school.Devna Fay Popejoy-Sheriff, Iowa State University Devna Popejoy-Sheriff is
Technol- ogy and Infrastructure for the NSF Center for e-Design at the University of Central Florida. Dr. Yousef developed a strategic plan for information technology for the center. Dr. Yousef authored several refereed publications including book chapters, journal papers, and conference papers. He was also either the PI or the Co-PI in many research projects related to Cost Engineering, Cost and Quality Effectiveness, Cost Modeling, System of Systems Interoperability, Supply Chain Management, Decision Support Systems, Knowledgebase Systems, and Database Management. During his career Dr. Yousef earned the award of Excellent Service from the department of Industrial En- gineering and Management Systems in 2006, and
, distributed simulation, adaptive control systems, digital signal processing, and integrat- ing technology into engineering education. He has also been an industry consultant on modeling for strategic planning. Professor Elizandro received the University Distinguished Faculty Award, Texas A&M, Commerce and College of Engineering Brown-Henderson Award at Tennessee Tech University. He served as Governor’s Representative for Highway Safety in Arkansas and member of the National Highway Safety Advisory Commission during the Jimmy Carter presidency. He is also a member of Tau Beta Pi, Alpha Pi Mu, and Upsilon Pi Epsilon honor societies.Dr. David H. Huddleston, Tennessee Technological University David H. Huddleston is a
is presented first. Following this,approach and methods undertaken to design and develop product-based learning throughout theundergraduate curriculum are presented. Examples of course activities and the flow andintegration across the curriculum are provided. Preliminary results and lessons learned areincluded in the discussion of courses that have been reengineered to date. Other critical elementsto success, such as the project team and infrastructure needs, are also discussed. Finally, asummary is provided along with plans for future work.Related LiteratureA problem-based learning pedagogy of engagement provides a strong foundation for curriculumredesign. Smith, et al. [2], citing additional studies indicating the importance of engagement
this educational research project, game-based in-class and after-class learning activities aredeveloped to teach selected inventory control strategies to undergraduate and graduate students.Students from Supply Chain Management and System Simulation courses are targeted, who aretaught by different instructors. The activities include teaching the inventory control policies tostudents in a regular class setting, then providing an overview on a game developed on MS Excel.In the game, the lead time and customer demand variables are defined uncertain, and not given tostudents, which make the assignment an ill-structured problem. A 12-month planning andexecution period is given to students with qualitative and quantitative information about
with this Commented [DLEP1]: Would you insert accurateprimary team for the full semester. Each project requires several different reports to be submitted numbers here?throughout the semester. For example, in Senior Design, students first submit a Project Statement Commented [LAM2R1]:of Work, followed by a Project Plan, two Technical Updates, and, finally, a completed projectreport. When grading each of these preliminary project reports, instructors provided numerouscomments with the intention that students will incorporate the feedback into improved futurereports. However, experience demonstrated that students viewed these comments as punitive orjustification of a grade, with each criticism tied to a point reduction
assessment, and predictive modeling & machine learning. For more information, please visit his personal blog at https://gokhanegilmez.wordpress.com/Dr. Dusan Sormaz, Ohio University Dr. Dusan N. Sormaz is a Professor of Industrial and Systems Engineering at Ohio University, Athens, USA. Dr. Dusan N. Sormaz’s principal research interests are in Lean manufacturing, Simulation, Addi- tive Manufacturing, Process planning, and application of knowledge-based systems in manufacturing. He teaches Lean manufacturing, Simulation and Computer Integrated Manufacturing courses at Ohio Uni- versity. His student team recently received the 1st place among 220 teams from 11 countries in the Global simulation competition sponsored by
presentations using teleconferencing technologies with remote sites for both faculty and students. ● The laboratory environment utilizes virtual machines for the PC interface students use to monitor and configure the PLCs. This reduces cost by minimizing the hardware required.Conversely the design, acquisition, and implementation of the lab environment also presentedchallenges: ● Cost: The laboratory access and scheduling hardware and software cost was approximately $9995.00 with a $2,995.00 yearly license. Additionally, each pod cost was approximately $23,358 and control plane infrastructure to support four lab pods was $7178.00 with plans to scale the infrastructure to 24 lab pods total. ● Labor: After design, the
bothhomogeneous teams and heterogeneous teams [4]. The advantages of homogenous teams aretypically: less conflict, better coordination, advantage of cohesion, and higher satisfaction. Theadvantages of heterogeneous teams are typically: diverse thinking, better performance oncomplex tasks, and more creativity. The disadvantages of homogeneous teams are: groupthink,decisions are one-dimensional (i.e., no contingency planning), and limited innovation. Thedisadvantages of heterogeneous teams are: difficulty agreeing, more conflict, and hard tocoordinate/manage. It has also been shown that homogeneous teams tend to reach a conclusion(albeit an inferior one) faster than heterogeneous teams [4]. This work has been corroboratedand expanded by other studies [5-9
70 industry projects in almost every area that is recognized by theuniversities in the United States related to the Industrial Engineering field. The areas include butnot limited to Safety Engineering, Ergonomics, Facilities Planning, Logistics and Supply Chain,Quality Control, Manufacturing, Construction, Financial Decision Making, Education,Healthcare, and Project Management. He has applied different techniques including OperationsResearch, Simulation, Data Mining and Machine Learning, Lean Management, and Statistics inthese projects. The expert does not categorize the keywords based on his personal beliefs aboutIndustrial Engineering related jobs. He uses his industry and academia experience to select andcategorize the keywords. In his
the first author. Thesecond author was a visiting scholar who spent several months on our campus. He is anindustrial engineer with research interests in engineering and social justice. Consistent with thevision of introducing changemaking themes in required classes in the majors, the initial plan wasto do this in several ways including: Introducing some lecture topics in the context of changemaking Rewriting some homework problems to include themes related to changemaking Create two new cases with social justice, humanitarian, or sustainability foundationsIn the end, these goals proved to be overambitious. The first goal was met with modest success,but the last goals proved too difficult for reasons that will be discussed below
Paper ID #22477Truck-Drone Two-tier Delivery Network DesignDr. Ergin Erdem, Robert Morris University Ergin Erdem is an assistant professor of Department of Engineering at Robert Morris University. Dr. Er- dem holds BS and MS degrees in industrial engineering from Middle East Technical University, Turkey and a PhD in Industrial and Manufacturing Engineering from North Dakota State University He has previ- ously worked as a lecturer and research associate at Atilim University and North Dakota State University. His research interests include; modeling for facility planning, genetic algorithms, education of manufac- turing
-negligible. In fact, even with the best process improvement design, the solution may radically fail if not organically adopted by the people using or contributing to the process. Yet, students consider implementation and adoption to be seamless. Therefore, a realistic solution of this type will always factor in the effects of implementation and adoption to holistically measure the actual improvement that the solution could attain. For example, instead of describing the effectiveness of a solution as a comparison between the future state and the current state, a realistic solution describes at least the deployment plan, incorporating assumptions
Paper ID #23870Implementation of a Project-based Learning Approach to UndergraduateEducation: Case Study of Optimization Course in Industrial EngineeringDr. Behin Elahi, Purdue University, Fort Wayne Dr. Behin Elahi is an Assistant Professor in Industrial Engineering/Industrial Engineering Technology at Purdue University, Fort Wayne (Fort Wayne, Indiana). Previously, she was fixed-term instructor at Michigan State University (East Lansing, MI) teaching courses such a manufacturing plan and control, supply chain modeling and management. She got her Ph.D. in Industrial Engineering from the University of Toledo (Toledo, OH) in
Paper ID #22483A Steepest Edge Rule for a Column Generation Approach to the Convex Re-coloring ProblemDr. Ergin Erdem, Robert Morris University Ergin Erdem is an assistant professor of Department of Engineering at Robert Morris University. Dr. Er- dem holds BS and MS degrees in industrial engineering from Middle East Technical University, Turkey and a PhD in Industrial and Manufacturing Engineering from North Dakota State University He has previ- ously worked as a lecturer and research associate at Atilim University and North Dakota State University. His research interests include; modeling for facility planning, genetic
learning: Theory and Practice. Ed. James H. Block. New York: Holt, Rinehart and Winston.[4] Keller, F. S., Sherman, J. G., and Bori, C. M. (1974). PSI, the Keller Plan Handbook: Essays on a Personalized System of Instruction. Menlo Park, Calif.: WA Benjamin.[5] Armacost, R.L., and Pet-Armacost, J. (2003). Using Mastery-based Grading to Facilitate Learning. IEEE Frontiers in Education Conference (FIE), Boulder, Colorado.[6] Carver, R. P. (1974). Two Dimensions of Tests: Psychometric and Edumetric. American Psychologist, 29: 512-518.[7] Onipede, O., and Warley, R. (2007). Rethinking Engineering Exams to Motivate Students. 26th Annual Lilly Conference on College Teaching, Miami University, Oxford, OH.[8] Sangelkar, S., Ashour, O.M
gave advice on communication andwriting structure and integration into engineering education practices. The articulation ofscaffolding – “It should be an area of focus with planned progressions in various writing styles:project report, research paper, memo, etc.” – showed faculty conceptualize the progression ofwriting learning [19]. However, this conception focused on learning “how” to perform particularengineering documents rather than the higher level critical thinking skill of rhetoric –understanding why there are genre distinctions, and how to determine these underlying “valuesystems” to adjust writing for future unfamiliar genres. This is a far more valuable skill thanlearning how to write a memo report, because it develops a learner’s
student groups were never profitable but were able to reduce their losses significantly inthe second round. In the second round, it was observed that many of the students had learned thevalue of planning, forecasting, and managing risk when determining the size and source ofinventory replenishment orders. To this end, they applied logic and math in an effort to improvetheir decision-making. For example, one team purchased their entire inventory from California inthe first round, which helped them reduce their total material cost. However, the late arrival ofthe shipment in the third week prevented them from satisfying customer demand in weeks oneand two. As a result, at the end of the week five, the team was left with a large amount of
design of the VR teachingmodule to be more immersive and visualized. The current VR module is a semi self-paced tutorial.Concurrent research (Phase III) is being conducted to investigate how well students understand thequeuing theory concept using this updated VR teaching module versus traditional classroomlecture. Data is currently being collected using a different set of students with the same conceptualquiz but taught the topic in a traditional classroom manner (control group). Afterwards, we plan toprovide a comparative analysis of both approaches, control group versus experimental group anddisseminate the results.. The sections discussed below only reflects how well the students performusing the VR training module (experimental group