SIMULATION-BASED ENGINEERING OF COMPLEX SYSTEMS

SUMMARY

This course is designed to prepare individuals to:

 

·       be more effective system architects and product designers;

·       perform system design and evaluation using OpEMCSS, a state-of-the-art graphical simulation library that includes an adaptive rule-based classifier block; and

·       achieve group consensus using the OpEM way-of-thinking about systems that facilitates communication, understanding and designing CAS.

 

                A Complex System is a network of component nodes that share knowledge with each other and adapt their behavior in order to collaborate to achieve global system goals that could not be achieved alone by any individual node. The OpEMCSS concept exploration tool, used during this course, allows rapid motion through problem space to examine complex system design problems. It facilitates “out-of-the-box” thinking to discover the best system concepts that solve system design problems without focusing on a point design too soon.

In order to better understand and evaluate complex systems, an expansionist approach to systems design and evaluation is presented during this course where a system is viewed as a hierarchy of networks (network of networks). The goal of such expansionist system design and evaluation is to determine the knowledge facts and rules required for each component to collaborate to achieve global system goals. Once the knowledge flow in the network and node rules have been determined, the requirements for node communications can be specified.

The presentations are coupled with practical classroom exercises, involving group participation using an IBM PC (student must bring his/her own PC), so that attendees get hands-on experience performing system design and evaluation of complex systems using the OpEMCSS graphical discrete event simulation (DES) library.  This library works with EXTEND5+MFG (Imagine That Inc.) an inexpensive and easy to use simulation software package.  Although the behavior of complex systems may be difficult to understand, the OpEMCSS modeling and simulation building blocks are easy to understand and use.

Persons attending this course will learn to: (1) perform conceptual design, (2) develop an OpEMCSS simulation model, (3) perform functional flow and parallel process analysis using your model, and (4) gain an understanding of the basis principles of complex systems.  Each attendee will receive a copy of the course textbook “Simulation-Based Engineering of Complex Systems.”

 

COURSE OUTLINE

DAY 1

·         Definition of Complex Systems

·         Using simulation to understand complex systems

·         Bringing complex systems into being

DAY 2

·         Statistical aspects of simulation

·         OpEM parallel process graphical language

·         Overview of OpEMCSS library blocks

·         Application of OpEMCSS to CAS

DAY 3

·         Design and evaluation methodology

1.                    Inventory system

2.                    Part Production System

3.                    Seaport System

·         Advanced features of OpEMCSS

DAYS 4&5

·         Applications of the Classifier Event Action block

·         Applications of the agent motion and spatial interaction blocks

·         Application of the OpEMCSS library blocks to a team project

 

 

INSTRUCTOR BIOGRAPHY

 

JOHN R. CLYMER is a professor of electrical engineering at California State University Fullerton (CSUF) and consults in the area of systems engineering, simulation, and artificial intelligence. In addition to consulting, he presents intensive short courses at various locations around the United States and abroad. His teaching assignments have included computer engineering, system control, continuous systems simulation, operational analysis and DES simulation, optimization and mathematical programming, and artificial intelligence (fuzzy logic and control, neural networks, and expert systems).  Dr. Clymer's current research interests are focused in the area of intelligent, complex adaptive systems, applying integrated simulation, artificial intelligence, and evolutionary programming methods to study such systems. He is a founding member of the Applied Research Center for Systems Science at CSUF.   He is a member of IEEE, SCS, and INCOSE.

 

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