Title: SAE 599 Modeling and Simulation for Systems Architecting and Engineering
1SAE 599 - Modeling and Simulation for Systems
Architecting and Engineering
- Dr. Raymond Madachy
- August 29, 2007
2Outline
- Class overview, schedule and logistics
- info at DEN website http//den.usc.edu and
http//csse.usc.edu/xx - System modeling and simulation overview
- Basic terminology
- Modeling process and heuristics
- Demonstrations
- Homework
3Instructor Contact
- Dr. Raymond Madachy
- Email madachy_at_usc.edu
- Office SAL 318 or GER 216C
- Office Hours Wednesday, 430-630 pm
- Phone 213.740.7275 (when working)
4Course Overview
- Cover modeling and simulation principles with
applications to architecting and engineering of
complex systems. You will use simulation tools
and conduct studies to address current research
issues for complex systems. - Modeling approaches focus on continuous and
discrete simulation, but other types will also be
described - We will survey applications for complex systems
across a variety of engineering domains - Some of the lectures will be supplemented with
demonstrations - Goal of the course for students is to understand
how modeling and simulation can support the
architecting process across a variety of domains,
and be able to apply the techniques.
5Course Objectives
- Review basic simulation methods and principles
applied to the architecting and engineering of
complex systems. Describe the art and science of
the modeling process, especially as applied to
complex systems, and provide access to tools and
executable models. - Cover continuous, discrete-event and other
simulation methods. Students will learn to
develop and execute their own simulation models. - Be exposed to a variety of simulation
applications for system architecting and
engineering disciplines by domain experts.
Overview current and future research in the
disciplines, and the future directions of
modeling and simulation in general. - Develop simulation term projects that address
critical research issues and/or industrial
applications in systems architecting and
engineering.
6Schedule
7Schedule (cont.)
8Course Materials
- Course text
- Law M, Kelton W, Simulation Modeling and
Analysis, 4th Edition McGraw-Hill, New York, NY,
2006 - Reference materials
- Khoshnevis B, Systems Simulation -
Implementations in EZSIM. McGraw-Hill, New York,
NY, 1992 - Madachy R. Software Process Dynamics, Wiley/IEEE
Press, 2007 - U.S. Defense and Modeling Office,
http//www.dmso.mil, 2007 - Selected papers and reading material will be
provided to students during the class. - Tools and models as-provided
9Grading
- Grading breakdown
- Midterm 15
- Homework 20
- Final examination 15
- Course project 50
- Homework assignments are announced in class.
Off-campus students must submit their assignments
in time to be received by DEN on the day they are
due. Off campus assignments must be submitted as
specified in the DEN guidelines. Assignments may
be turned in late for partial credit. Credit
decrements will increase 20 with each class
period after the due date. All assignments must
be prepared using a word processor, spreadsheet,
presentation graphics, and simulation software as
required. - Final Exam
- The university schedules the final exam date and
time. This semester the final exam is on December
TBD, 2007.
10Student Background Questions
- What is your major and status?
- What other SAE courses have you taken?
- What simulation courses have you taken?
- Describe your experience in modeling and
simulation in industry. - How frequently will you watch the DEN webcast
live?
11My ISE Background
- 1981-1988 Software development for aerospace
real-time embedded systems and
scientific programming, General Dynamics, Hughes,
TRW - 1983 M.S. Systems Science, UCSD
- 1988-1992 Software management for real-time
displays and controls, program software
metrics, Librascope - 1992-2000 Software process improvement,
metrics, risk management, SEPG management,
Litton Systems - 1994 Ph.D. Industrial and Systems
Engineering, USC - 2000-2002 E-commerce software management, ROI
and economic analysis, C-Bridge Institute - 2002-2005 Cost estimation, ROI and economic
analysis, tool development, Cost Xpert Group - 2005Now Systems and software engineering
research and project support, USC- CSE - Army Future Combat Systems
- NASA Project Constellation
12Software Process DynamicsRelevant Sections in
Course Reader
- Part 1 - Fundamentals
- Chapter 1 Introduction and Background
- Chapter 2 The Modeling Process with System
Dynamics - Chapter 3 Model Structures and Behavior for
Software Processes - Part 2 Applications and Future Directions
- Chapter 4 People Applications
- Chapter 5 Process and Product Applications
- Chapter 6 Project and Organization Applications
- Appendix A Introduction to Statistics of
Simulation
These chapters also available for students
interested in software-intensive systems
13Term Projects
- Simulation studies related to systems
architecting and engineering that address
critical research issues and/or industrial
applications. The variety of topics is flexible,
and each student will define his/her research
topic to be addressed by modeling and simulation.
In approved cases students can team up in groups
of two. - Client/mentors available for some projects
(encouraged). - Example available topics
- Resource adaptability model for disasters and
terrorist attacks (Jackson) - Motor sports simulation (Settles)
- Limits to change on large SOS projects (Boehm,
Lane) - Front-end GUI for web-based simulation tool
(Madachy) - Acceptance test development for updated EZSIM II
software (Madachy, Khoshnevis) - Carbon emissions model for China to LA cargo
transport (Madachy, Bradbury-Huang) - Major exercises from Software Process Dynamics
(Madachy)
14Modeling Homework Guidelines
- For all homeworks and projects
- always show equations
- liberally include comments in equations
- provide rationale for numeric values and
calibrations - show outputs for different simulation cases
- discuss results
15Outline
- Class overview, schedule and logistics
- info at DEN website http//den.usc.edu and
http//csse.usc.edu/xx - System modeling and simulation overview
- Basic terminology
- Modeling process and heuristics
- Demonstrations
- Homework
16Complex Systems, Modeling and Simulation
- The evaluation of strategies for the architecting
and engineering of complex systems involves many
interrelated factors. - Effective systems, software and human engineering
requires a balanced view of technology, business
or mission goals, and people. - Modeling and simulation provides a framework to
quantify the complex interactions and the
strategy tradeoffs between cost, schedule,
quality and risk.
17Systems Engineering Challenges
- What to build? Why? How well?
- Stakeholder needs balancing, business case
- Who to build it? Where?
- Staffing, organizing, outsourcing
- How to build? When in what order?
- Construction processes, methods, tools,
components, increments - How to adapt to change?
- In user needs, technology, marketplace
- How much is enough?
- Functionality, quality, specifying, prototyping,
test
18Why Model Systems?
- A system must be represented in some form in
order to analyze it and communicate about it. - The models are abstractions of real or conceptual
systems used as surrogates for low cost
experimentation and study. - Models allow us to understand systems/processes
by dividing them into parts and looking at how
the parts are related. - We resort to modeling and simulation because
there are too many interdependent factors to be
computed, and truly complex systems cannot be
solved by analytical methods.
19Architected System Types
- Hardware
- Software
- Human
- Hardware-Software, Hardware-Human,
Software-Human, Hardware-Software-Human - Living things (e.g. bio-computing)
- Other?
20Modeling Characterizations (Examples for
Software-Intensive System Processes from Madachy)
- Purposes
- Strategic management
- Planning
- Control and operational management
- Process improvement and technology adoption
- Training and learning
- Scope
- Portion of lifecycle
- Development project
- Multiple, concurrent projects
- Long-term product evolution
- Long-term organization
21Modeling Applications (Examples for Weapons
Systems Acquisition Activities per DSMC)
- Requirements definition
- Program management
- Design and engineering
- Manufacturing
- Test and evaluation
- Logistics support
- Training
- Templates provided for these applications
- Defense Systems Management College, System
Acquisition Managers Guide for the Use of Models
and Simulation, 1994
22Outline
- Class overview, schedule and logistics
- info at DEN website http//den.usc.edu and
http//csse.usc.edu/xx - System modeling and simulation overview
- Basic terminology
- Modeling process and heuristics
- Demonstrations
- Homework
23Terminology
- System a grouping of parts that operate together
for a common purpose a subset of reality that is
a focus of analysis - Open, closed
- Static, dynamic
- Characterized by 1) parameters that are
independent measures that configure system inputs
and structure, and 2) variables which depend on
parameters and other variables. The collection
of variables necessary to describe a system at
any point in time is called the state of the
system. - Model an abstract representation of reality.
- Static, dynamic
- Continuous, discrete
- Deterministic, stochastic
- Simulation the execution, or numerical
evaluation of a mathematical model.
24Terminology (cont.)
- Discrete event simulation state variables change
instantaneously at separate points in time - Continuous simulation state variables change
continuously over time - System dynamics a simulation methodology for
modeling continuous systems. Quantities are
expressed as levels, rates and information links
representing feedback loops. - Hybrid simulation contains both discrete-event
and continuous model elements - Agent-based simulation a system is modeled as a
collection of autonomous decision-making entities
called agents. Each agent individually assesses
its situation and makes decisions on the basis of
a set of rules.
25What Type of Model for What Type of System?
- All classes of systems may be represented by any
of the model types. A discrete model is not
always used to represent a discrete system and
vice-versa. The choice of model depends on the
specific objectives of a study.
26Outline
- Class overview, schedule and logistics
- info at DEN website http//den.usc.edu and
http//csse.usc.edu/xx - System modeling and simulation overview
- Basic terminology
- Modeling process and heuristics
- Demonstrations
- Homework
27Modeling Process Overview (from System Dynamics
paradigm)
policy implementation
system understandings
policy analysis
problem definition
simulation
model conceptualization
model formulation
28Modeling Stages and Concerns (from System
Dynamics paradigm)
29Like Architecting, Modeling is an Art and Science
30Model Conceptualization Heuristics
- Define a clear, operational purpose of the model.
- Dont try to model the system.
- Aggregate and abstract to the appropriate degree.
- Use a top-down iterative approach.
- KISS (keep it simple, stupid)
31Model Formulation and Development Heuristics
- Don't enumerate all factors at first.
- Iteratively refine and slowly add relationships
to model. - Normalize when possible.
- Use relative measures.
- Dont stray too far from a simulatable model.
- Don't model in isolation try to involve those
being modeled.
32Model Validation Heuristics
- Look for qualitative similarity on the first
pass. - Alter one parameter at a time at first.
- Be conscious of reality constraints.
- Model validity is a relative matter.
- The usefulness of a mathematical simulation model
should be judged in comparison with the mental
image or other abstract model which would be used
instead Forrester 68. Models are successful if
they clarify our knowledge and insights into
systems.
33Miscellaneous Heuristics
- Data Collection
- Model design should not be postponed until all
pertinent parameters have been accurately
measured. - Communication
- Use simple diagrams to communicate with others
until they seek more detail.
34General Modeling Heuristics
- No model is perfect.
- but some are useful
- All models are incomplete.
- No model is final it is possible to build many
different models of a single process. - All models contain hidden assumptions.
- Continually challenge the model.
35Outline
- Class overview, schedule and logistics
- info at DEN website http//den.usc.edu and
http//csse.usc.edu/xx - System modeling and simulation overview
- Basic terminology
- Modeling process and heuristics
- Demonstrations
- Homework
36Demonstrations
- Continuous modeling with system dynamics
37Outline
- Class overview, schedule and logistics
- info at DEN website http//den.usc.edu and
http//csse.usc.edu/xx - System modeling and simulation overview
- Basic terminology
- Modeling process and heuristics
- Demonstrations
- Homework
38Homework
- Answer questions on your background
- Read sections 1.1-1.4 and 1.9 of Law-Kelton
textbook - Do a search for free public domain simulation
software (possibly open-source or very low cost)
discrete-event, continuous, hybrid, others - Find promising alternatives and do some limited
testing - Write up your findings in 3-5 pages. List those
you checked out, and develop a comparison matrix
of features for promising candidates. Show
simple models if possible. We are particularly
interested in packages you can use for this
course. Make sure and provide the links. - You may come across simulation tools suitable for
a term project as coordinated with your company. - If no better tools are identified, you will be
provided the EZSIM discrete-event simulation
software for DOS and buy a continuous simulation
tool for 100 at student price - There is some flexibility if you have other tools
at your disposal - Lets see what our new options are today
- Some links
- Simulation tools http//www.idsia.ch/andrea/simt
ools.html - Free discrete-even simulation software
http//www.topology.org/soft/sim.html