Kiassat, C., & Buyurgan, N., & Leeds, J. (2015, June), Interactive Simulation for Introducing Industrial Engineering  Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24345

\bibitem{asee_peer_24345}
  Kiassat, C., \& Buyurgan, N., \& Leeds, J. (2015, June), \emph{Interactive Simulation for Introducing Industrial Engineering}
  Paper presented at 2015 ASEE Annual Conference \& Exposition, Seattle, Washington.
  10.18260/p.24345

Corey Kiassat, Nebil Buyurgan, and Julia Leeds.  "Interactive Simulation for Introducing Industrial Engineering".  2015 ASEE Annual Conference & Exposition, Seattle, Washington, 2015, June.  ASEE Conferences, 2015.  https://peer.asee.org/24345 Internet.  01 May, 2024

\bibitem{asee_peer_24345}
  Corey Kiassat, Nebil Buyurgan, and Julia Leeds.
  "Interactive Simulation for Introducing Industrial Engineering".
  \emph{2015 ASEE Annual Conference \& Exposition, Seattle, Washington, 2015, June}.
  ASEE Conferences, 2015.
  https://peer.asee.org/24345 Internet.  01 May, 2024

@INPROCEEDINGS{asee_peer_24345
author = "Corey Kiassat, Nebil Buyurgan, and Julia Leeds"
title = "Interactive Simulation for Introducing Industrial Engineering"
booktitle = "2015 ASEE Annual Conference \& Exposition"
year = "2015"
month = "June"
address = "Seattle, Washington"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/24345}
number = {10.18260/p.24345}
}

TY  - CPAPER
AB  -           Interactive Simulation for Introducing Industrial EngineeringABSTRACT       This study represents a simulation-based Industrial Engineering (IE) challenge activity inan introduction to engineering course. The course is developed for incoming freshman studentsin their first semester to provide an understanding of IE and the other three engineeringdisciplines offered at X University, a medium-sized, traditionally liberal arts oriented, mainlyundergraduate, private university in northeastern United States. The engineering program at XUniversity has a strong focus on experiential learning, with the goal of better preparing thegraduates for employment.       In the IE component of the course, students are introduced to the nature of the disciplineand its wide applications through four introductory sessions, including Operations Research(OR) and Human Factors (HF). This is followed by an “IE Challenge” which incorporatestechniques in OR and HF to make the students aware of a real life problem requiringoptimization, while considering human physical variations. Student teams are in charge ofoptimizing the operations of a passenger airplane, specifically the seat design and routing of theairplane, with a revenue maximization goal. There is a reward associated with each of severalglobal destinations, with farther cities having a higher reward. But not all cities can be on thetravel route due to a limited fuel capacity. Passenger sizes and body types are different based ongender and global region. There is a revenue per carried passenger, but a penalty associated withthe degree of passenger discomfort. Students are faced with many trade-off decisions, a conceptgenerally present in many IE contexts. An example of a trade-off decision encountered duringthe seat design phase is maximizing the number of seats for revenue versus maximizing seatwidths for passenger comfort. HF trade-off decisions on seat design are intertwined with the ORtrade-off decisions in travel route because the choice of destination affects the anthropometricdata of passengers from that region.       Upon completion, the students become familiar with the Travelling Salesman Problem,Knapsack Problem, as well as the usage of anthropometric data for genders and ethnic groups.The information about students’ perception, knowledge, and preference on IE is collectedthrough a survey at the beginning and the end of the semester to investigate an increase inknowledge of IE. The survey included questions with answers directly on a five-point Likertscale, as well as open-ended questions that required responses to be mapped onto a five-pointLikert scale. In order to analyze student responses and interpret the results, responses are mappedto four quadrants on a graph, with knowledge of IE on the x-axis and confidence in answer onthe y-axis. Each axis is turned into a low and high category. Before the IE module, a significantmajority of the students (84%) were in the Low-Low category. After the IE module, a significantmajority of the students (91%) have moved to the High-High category, indicating the majority ofthe 73 students know what an industrial engineer does and are confident in their answer.
AU  - Corey Kiassat
AU  - Nebil Buyurgan
AU  - Julia Leeds
CY  - Seattle, Washington
DA  - 2015/06/14
PB  - ASEE Conferences
TI  - Interactive Simulation for Introducing Industrial Engineering
UR  - https://peer.asee.org/24345
DO  - 10.18260/p.24345
ER  -