Simulation, Exploration, and Understanding in Engineering G. W. Rubloff Materials Science & Engineering, and Institute for Systems Research University of Maryland How can we help people develop insight in both engineering education and practice ? Center for Engineered Learning Systems Institute for Systems Research Human-Computer Interaction Laboratory Institute for Advanced Computer Studies with special thanks to Anne Rose, HCIL

Developing Insight in Engineering Education and Practice CHALLENGES Domains are unfamiliar to the user Often no hands-on physical experience Unfamiliar length and time scales Principles are abstract Subtle until experienced Ultimately must be understood in mathematical terms Systems-level behavior enlarges complexity Multi-level metrics Heterogeneous, hierarchical models Dynamic & stochastic behavior Environments and tools for engineering insight are limited Education and training Broad engineering practice EXAMPLE: semiconductor chips Depart Leave Pick Station Arrive Stocker materials & processes transistors & chips people factory costs and operations/ logistics equipment

Developing Insight in Engineering Education and Practice CHALLENGES Domains are unfamiliar to the user Often no hands-on physical experience Unfamiliar length and time scales Principles are abstract Subtle until experienced Ultimately must be understood in mathematical terms Systems-level behavior enlarges complexity Multi-level metrics Heterogeneous, hierarchical models Dynamic & stochastic behavior Environments and tools for engineering insight are limited Education and training Broad engineering practice SOLUTIONS Simulations of physical phenomena Desired attributes of simulation environments

materials & processes circuits & chips equipment factory operations & logistics transistor devices cost of ownership Engineering Simulations EXAMPLE: semiconductor chips dynamic/stochastic discrete event static spreadsheet finite element dynamic continuous parameter Monte Carlo

materials & processes circuits & chips equipment factory operations & logistics transistor devices cost of ownership Engineering Simulations EXAMPLE: semiconductor chips dynamic/stochastic discrete event static spreadsheet finite element dynamic continuous parameter Monte Carlo While valuable to specific technical experts, how beneficial are these for education and broader practice?

Desired attributes of simulation environments Developing Insight in Engineering Education and Practice CHALLENGES Domains are unfamiliar to the user Often no hands-on physical experience Unfamiliar length and time scales Principles are abstract Subtle until experienced Ultimately must be understood in mathematical terms Systems-level behavior enlarges complexity Multi-level metrics Heterogeneous, hierarchical, dynamic, stochastic behaviors Environments and tools for engineering insight are limited Education and training Engineering practice SOLUTIONS Simulations of physical phenomena Self-directed and guided hands-on experiences Connectivity to underlying fundamentals Complexity management through Integrated, heterogeneous simulations Tools to help the user develop understanding and insight Separable authoring and rapid module development

SimPLE timer keep history communicate access background and guidance materials, locally or from Internet save & document control the simulation view dynamic results carry out experiments and annotate results operate system and see consequences in real time Demos in HCIL Demos in HCIL Simulated Processes in a Learning Environment

SimPLE Features in the SimPLE Framework Design of experiments Simulation control at system image Guidance – local & Internet Assigned exercises Condition watchdog tool Learning historian Lab notebook Timer System design configurator Process recipes Graphs & charts Visualization control Tightly-coupled guidance Change module learner Teacher kit Authoring in html teacher Domain-specific Delphi objects Domain-specific simulation models and submodels SimPLE framework Separable authoring author / developer

Tightly-Coupled Guidance

Learning Historian 1. Do a simulation 3. Replay the simulation history 2. Record and save the simulation history 4. Review, revise, & annotate the history 5. Share the history with peers & instructor Simulation History

Configuration setups Configuration setups Teacher Kit System design parameters GUI components Guidance materials Historian configuration Error messages Simulation models Teacher may create specific setups to customize educational scaffolding

SimPLE Applications WaterSim environment & manufacturing NileSim hydrology & social science Process recipe Process recipe Factory simulation Factory simulation Cluster tool scheduling Cluster tool scheduling Sensitivity analysis Sensitivity analysis Cluster tool configuration Cluster tool configuration HSE factory operation s fail pass Oxide growth temperature Oxide thickness Capacitor area Capacitance YIELD SortSim computing algorithms EquiPSim semiconductor manufacturing TrafficSim transportation management WaferMap multistep process optimization

Messages Engineering insight through SimPLE environments Free and guided exploration through simulation Powerful tools for individual and collaborative learning Also: science, computer science, math, social science, … You can use this learning systems technology now Teachers – specific topical areas & development of new areas Developers – SimPLE platform & new features to come We invite your participation Collaborations, workshops, …

Acknowledgements ENGINEERING L. Henn-Lecordier B. Levy P. Tarnoff G. B. Baecher B. Levine J. W. Herrmann Simulation software platform Commercial applications & customization Research support CEBSM Research partnership for semiconductor ESH Research partnership for tech training COMP SCI & UMIACS A. Rose B. Shneiderman C. Plaisant G. Chipman EXTERNAL F. Shadman (U. Arizona CEBSM) M. Lesiecki (MATEC) S. Braxton (Bowie State)