Chicago, Illinois
June 18, 2006
June 18, 2006
June 21, 2006
2153-5965
Chemical Engineering
21
11.621.1 - 11.621.21
10.18260/1-2--593
https://peer.asee.org/593
804
Milo D. Koretsky is an Associate Professor of Chemical Engineering at OSU. He received his BS and MS degrees from UCSD and Ph D from UC Berkeley, all in chemical engineering. Professor Koretsky’s research interests are in thin film materials processing including: plasma etching, chemical vapor deposition, electrochemical processes and chemical process statistics. He is author of the book, Engineering and Chemical Thermodynamics (Wiley, 2004).
Sho Kimura is a Professor of Chemical Engineering at OSU. Professor Kimura’s research interests cover high-temperature materials synthesis, nano-sized materials synthesis, surface modifications, applications of high-temperature fluidization technology, reaction kinetics, catalytic effects on gas-solid reactions, and reactor design and simulations.
Connelly Barnes is an undergraduate student in Computational Physics and Mathematics at OSU. Connelly is the programmer for the software ThermoSolver which accompanies the text Engineering and Chemical Thermodynamics.
Danielle Amatore is A PhD candidate in Chemical Engineering at OSU. Her thesis focuses on educational methods, including assessment of complex cognitive processes. Danielle received her BS in chemical engineering from OSU and her MS from the University of Washington.
Derek Meyers-Graham is an undergraduate student in Computer Science and Mathematics at OSU.
Experiential Learning of Design of Experiments Using a Virtual CVD Reactor
Abstract Presently there is a need for more effective ways to integrate statistical methodologies such as Design of Experiments (DOE) into the engineering curriculum. We have developed a virtual chemical vapor deposition (CVD) reactor based on a numerical simulation where students learn and then actually apply DOE. Associated educational materials are also being developed. The simulation of the Virtual CVD reactor is based on fundamental principles of mass transfer and chemical reaction, obscured by added “noise.” However, rather than having access to the entire output of model, the film thicknesses are given to students only at the select points within the wafer and from wafer to wafer that they have decided to “measure”. This package is all housed within a three-dimensional (3D) graphical user interface where students are placed in a simulated clean room environment. Student assessment is based not only on the ultimate reactor performance but also on the cost of experimentation.
This learning tool represents an innovative use of computers and simulation in integrating statistics into engineering education. Students are given a “capstone” experience in which they have the opportunity to synthesize engineering science and statistics principles to optimize reactor performance. Since the simulation is from first principles, students can interpret the outputs given by the DOE in terms of the chemical and physical phenomena in the system. The Virtual CVD reactor allows students a broader and more realistic experience in using the DOE methodology for process improvement - as if they were operating an actual industrial reactor.
The project scope also includes development and implementation of an assessment plan to evaluate the effectiveness of this tool in promoting higher order thinking skills. The Northwest Regional Educational Laboratory is providing support for the project evaluation and assessment. A five-member advisory committee consists of engineers and statisticians from academia (Oregon State University, University of Oregon) and industry (LSI Logic, Intel, WaferTech).
The VirtualCVD Learning Platform is available now for use in approved courses. Instructors who are interested in adopting this software into their curriculum can go to the following web page for information: http://che.oregonstate.edu/research/VirtualCVD
Motivation Proficiency with statistical methodologies such as Design of Experiments (DOE) is an increasingly essential skill for engineers. This requires not only knowledge of statistical concepts related to DOE, but also the ability to integrate this methodology with fundamental engineering principles toward designing and understanding experiments. However, current engineering curriculums have not fully adapted to this need in the engineering industry. In the 1970s and 1980s, the absence of sound statistical methods in the engineering work place led to a crisis in US industry where a large percentage of the market share went overseas. This crisis was first reflected in the manufacture of automobiles and then in the process-oriented manufacture of integrated circuits.1,2 Only with the industrial investment towards quality, largely through the systematic training and implementation of statistical methodologies, has the United States
Koretsky, M., & Kimura, S., & Barnes, C., & Amatore, D., & Meyers-Graham, D. (2006, June), Experiential Learning Of Design Of Experiments Using A Virtual Cvd Reactor Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--593
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