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A Framework for Stakeholder-responsive Agile Simulations (SAS)

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Copyright © 2006 Intelligent Systems Technology, Inc.

Dr. Azad M. MadniChief Executive Officer

Intelligent Systems Technology, Inc.

USC-CSE Executive WorkshopMarch 15, 2006

Copyright © 2006 Intelligent Systems Technology, Inc.Information in this document is the property of Intelligent Systems Technology, Inc. Disclosure is made in confidence.

Unless otherwise permitted, use or further disclosure of the depicted information by persons outside Intelligent Systems Technology, Inc. is prohibited.

Madni/2

Outline

Problem

Approaches To Date

Stakeholder Concerns

Stakeholder-centric Agile Simulations (SAS)

Illustrative Example

Findings

Benefits and Payoffs

References



Madni/3

Problem

Complex systems engineering initiatives frequently over-run their schedule and budget last minute discovery of integration problems

Need a means to continually “test-drive” the evolving system design during development to: avoid last minute surprises reduce integration risks maximize user acceptance make time-to-market goals



Madni/4

Approaches To-Date Hardware-Software Co-Design

Accelerate product development by creating a timing-accurate hardware simula-tion to debug hardware-software integration before actual hardware availability

Principal focus: embedded systems

Virtual Prototyping Create a model of system to evaluate functionality and behavior relative to

system requirements prior to undertaking detailed design/manufacturing Principal focus: mechanical CAD, aerospace, automotive

Virtual Reality A synthetic environment to evaluate virtual prototypes prior to physical design Principal focus: defense, aerospace, shipbuilding

Concurrent Engineering and Integrated Product-Process Development (IPPD)

Simultaneously address product life cycle concerns from technical and management perspectives while in the early stages of development and thereafter

Principal focus: defense, aerospace, automotive, shipbuilding



Madni/5

What’s Missing?

Current approaches are “inward focused” they do not explicitly address the needs of the external stakeholders

They lack an overarching framework to assemble the necessary models and simulations to answer stakeholder questions

They do not provide a plan for refining their models with incrementally available information



Madni/6

Who are the Stakeholders?

Operator/End User

Marketing Head

Engineering/Product Development Manager

Development Team Manager

Customer/Acquisition Manager



Madni/7

Stakeholder Concerns

End User/Operator: “Can I work with this system effectively?”

Marketing Head: “Does it do all the right things that the market wants?”

Engineering Manager: “Does it do all the right things right?”

Customer/Acquisition Manager: “Does it do all the right things right in the right time and with

the right amount of resources?”

(Madni, 1997)



Madni/8

Stakeholder-responsive Agile Simulation (SAS) Framework

A multiperspective approach to simulation-based integration that is driven by the needs of the different stakeholders

employs “separation of concerns” to simplify the integration problem

uses stakeholder concerns to determine what needs to be simulated and from what perspective

exploits the fact that most complex systems can be deconstructed into simpler subsystems that can be analyzed with appropriate subsets of others

Requires a range of modeling, simulation, and analyses techniques

Different techniques…different combination of subsystems…to answer stakeholder questions

Different techniques…different combination of subsystems…to answer stakeholder questions

(Madni et al, 2006, Madni, 1997)



Madni/9

SAS Characteristics

Stakeholder perspective-driven

Incremental model refinement with availability of additional data

Rapidly reconfigurable to stakeholder perspectives

Focused on answering stakeholder questions as early as feasible to accelerate product development decisions

Implementable with COTS and open source technologies



Madni/10

SAS Taxonomy

moderate fidelity process models; moderate fidelity simulations

program manager GUI; systems engineering process models; process simulation; “what-if” program management scenarios

cycle time analysis, cost analysis, risk analysis, “what-if” contingency analysis

• Program Manager

• Customer• Acquisition Mgr

Program Prototype

high fidelity process representation and visualization interface

OSI for process monitoring and visualization; status database

IPPD process monitoring and visualization

• Product Development Manager

Process Prototype

low fidelity OSI; high computational fidelity (i.e., algorithms, criteria)

OSI, algorithm definitions, evaluation criteria

comparative evaluation of algorithms (e.g., fusion algorithm) performance evaluation

• Designers• Testers

Algorithmic/ Analytic Prototype

low fidelity OSI; high fidelity specification and interface definition

OSI, component specification and interface definitions, database of logical components

architecture definition, processor sizing, HW/SW interface

• System Architect

• Systems Engineer

Logical Prototype

high fidelity operator system interface, low fidelity database

operator-system interface (OSI); database, table-driven

convey CONOPS, access, operability, usability

• System Operator• Human Factors

Specialist• Marketing Mgr

Concept Prototype

Fidelity RequirementsRequired ComponentsPurposeUsersType of

SAS

moderate fidelity process models; moderate fidelity simulations

program manager GUI; systems engineering process models; process simulation; “what-if” program management scenarios

cycle time analysis, cost analysis, risk analysis, “what-if” contingency analysis

• Program Manager

• Customer• Acquisition Mgr

Program Prototype

high fidelity process representation and visualization interface

OSI for process monitoring and visualization; status database

IPPD process monitoring and visualization

• Product Development Manager

Process Prototype

low fidelity OSI; high computational fidelity (i.e., algorithms, criteria)

OSI, algorithm definitions, evaluation criteria

comparative evaluation of algorithms (e.g., fusion algorithm) performance evaluation

• Designers• Testers

Algorithmic/ Analytic Prototype

low fidelity OSI; high fidelity specification and interface definition

OSI, component specification and interface definitions, database of logical components

architecture definition, processor sizing, HW/SW interface

• System Architect

• Systems Engineer

Logical Prototype

high fidelity operator system interface, low fidelity database

operator-system interface (OSI); database, table-driven

convey CONOPS, access, operability, usability

• System Operator• Human Factors

Specialist• Marketing Mgr

Concept Prototype

Fidelity RequirementsRequired ComponentsPurposeUsersType of

SAS

(Madni, 1997)



Madni/11

I llustrative Example:Crisis Management

Information System (CMIS)

A computer-based system that provides facilities for data collection, aggregation, portrayal, and analysis, as well as management and control of collection assets (including human resources)

Applications include: disaster management crisis action planning and execution



Madni/12

Stakeholders

CMIS user (e.g., crisis manager, resource owner, …)

Acquisition manager

System development manager

Human factors specialist

System architect

Subsystem engineer



Madni/13

CMIS Subsystems Interconnections

HSI

FASS

STORE

SENSORS

ENVIR

HUMAN

: human-system interface

: external environment in which the first 4 are embedded

: sensor suite

: local data storage (repo, db, cache)

: functional or algorithmic subsystem

SENSORS

SENSORS

HSI

HSI

STORE

STORE

FASSFASSHUMAN

HUMAN

ENVIR

: operator, maintainer, tester; could be simulated as well

(Adapted from Madni, 1997)



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Concept Prototype

— HSI

— STORE

— ENVIR

+ Use Cases

SENSORS

HSI

STORE

FASS

ENVIR

HUMAN

Purpose: Design, communicate, refine CONOPS*, operator-system interaction, user acceptance testing (interaction level), human error analysis (“can the user work with it effectively”)

* CONOPS: Concept of Operations

What is needed:

Stakeholders: CMIS user, human factors specialist

— HSI

— STORE

— ENVIR

+ Use Cases

SENSORS

HSI

STORE

FASS

ENVIR

HUMAN

HUMAN

Purpose: Design, communicate, refine CONOPS*, operator-system interaction, user acceptance testing (interaction level), human error analysis (“can the user work with it effectively”)

* CONOPS: Concept of Operations

What is needed:

Stakeholders: CMIS user, human factors specialist



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Functional Prototype

— FASS programmer I/F

— FASS

— STORE

— ENVIR

SENSORS

HSI

STORE

FASS

ENVIR

HUMAN

HUMAN

Purpose: Evaluate adequacy and completeness of functional coverage (“does it do all the right things”)

What is needed:

Stakeholders: acquisition manager, system architect, systems engineer, system development manager



Madni/16

Engineering Prototype


— FASS

— STORE

— SENSORS

— ENVIR

SENSORS

HSI

STORE

FASS

ENVIR

HUMAN

Purpose: Comparative evaluation of competing algorithms in the face of different environmental factors (“does it do all the right things right”)

What is needed:

Stakeholders: subsystem engineers, system architect, system development manager


— FASS

— STORE

— SENSORS

— ENVIR

SENSORS

HSI

STORE

FASS

ENVIR

HUMAN

HUMAN

Purpose: Comparative evaluation of competing algorithms in the face of different environmental factors (“does it do all the right things right”)

What is needed:

Stakeholders: subsystem engineers, system architect, system development manager



Madni/17

Operational Prototype

— HSI

— FASS

— STORE

— SENSORS

— ENVIR

SENSORS

HSI

STORE

FASS

ENVIR

HUMAN

HUMAN

Purpose: Performance testing (“does it do all the right things right in the right time and with the right amount of resources”)

What is needed:

Stakeholders: CMIS user, acquisition manager, system development manager



Madni/18

Web-based SAS (examples)

Web client, server, intranet with server programmed for additional functionality (e.g., data visualization, touch-sensitive forms processing, data base management, and “web cams”)

HSI + FASS + STORE + SENSORS

Operational prototype

Web browser client and web server operating on an Intranet

HSI + STORE

Operator acceptance evaluation

Web-based ImplementationCMIS SubsystemsSAS Class

Web client, server, intranet with server programmed for additional functionality (e.g., data visualization, touch-sensitive forms processing, data base management, and “web cams”)

HSI + FASS + STORE + SENSORS

Operational prototype

Web browser client and web server operating on an Intranet

HSI + STORE

Operator acceptance evaluation

Web-based ImplementationCMIS SubsystemsSAS Class



Madni/19

SAS Solution Strategy

CMIS Component Architectural ElementsSAS

(Java Solution)

HSI, STORE

HSI, FASS, STORE,

SENSORS

Generic Components

Component Assembly

Web browser (client), web server operating on intranet

web client, server, intranet; server programmed with additional functionality (e.g., data visualization, touch-sensitive forms processing, data base management, “web cams”

coded with “plug and play” interfaces (not hand coded for each SAIS design)

rule-based component configuration system (e.g., telephone switching system configuration)

Applet

Servlets, EJB

JavaBeans sets

Bean “wiring” applications; servletconfiguration utilities



Madni/20

Findings The concepts underlying the SAS framework were found to

improve both comprehension and team collaboration

Our R&D and prototyping activities based on SAS concepts proved the feasibility of the overall approach in Combat Information Systems (CIS) development

We were able to answer specific stakeholder questions much earlier in design and thereby mitigate specific integration risks

Technologies for implementing SAS are available today (e.g., Flash MX, Java, simulation languages)



Madni/21

SAS Benefits and Payoffs Circumvent last minute surprises in system (hardware,

software, human) integration

Maximize stakeholder acceptance

Achieve timely launch of the right product

Dramatically shorten product development timeline

Achieve cost savings through elimination of “rework” and waiting times in hardware-software integration

Mitigate risks throughout product development lifecycle

From “design-build-test-fix…” to “design, test in simulation, build right the first time”

From “design-build-test-fix…” to “design, test in simulation, build right the first time”



Madni/22

References Madni, A.M., Moini, A., Madni, C.C. Modeling and Simulation-driven

Approaches for Analyzing DoDAF Architectures, Proceedings of the 2006Ninth World Conference on Integrated Design and Process Technology, (IDPT-2006), San Diego, CA, June 25-30, 2006.

Madni, A.M., Lin, W., and Madni, C.C. “IDEON™: An Extensible Ontology for Designing, Integrating, and Managing Collaborative Distributed Enterprises” in Systems Engineering: The Journal of the International Council on Systems Engineering, Vol. 4, No. 1, 2001.

Madni, A.M. and McCoy, W.L. “Bringing ANSI/EIA-632 to Life through ProcessIPPD,” Proceedings of the Thirteenth International Conference on Systems Engineering, Las Vegas, Nevada, August 10-12, 1999, pp. SE211-SE216.

Madni, A.M., Madni, C.C., and Lin, W. “IDEON™/IPPD: An Ontology for Systems Engineering Process Design and Management,” (Invited Paper) Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, California, October 11-14, 1998, pp. 2597-2602.

Madni, A.M. “Modeling and Simulation Toolkit for Virtual Prototyping of SC-21 Ship Information System Architecture,” Final Technical Report, ISTI-523-11/97-F, November 1997.

We welcome the opportunity to conduct collaborative R&D with USC Faculty and research staff.

Thank you for your kind attention.

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