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Toward A Framework for Implementing Systems Engineering Development for Complex Systems Karl L. Brunson, GWU Thomas A. Mazzuchi, D.Sc., GWU Shahram Sarhani , Ph.D., GWU Jeffrey Beach, D.Sc., GWU. Outline. What is the purpose Development of ICM Framework Life-cycle Risks

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Outline

Toward A Framework for Implementing Systems Engineering Development for Complex SystemsKarl L. Brunson, GWUThomas A. Mazzuchi, D.Sc., GWUShahram Sarhani, Ph.D., GWUJeffrey Beach, D.Sc., GWU


Outline

Outline

  • What is the purpose

  • Development of ICM Framework

  • Life-cycle Risks

  • Acquisition Life-cycle

  • Complex System Work Breakdown Structure

  • Framework Schedule Development

  • Risk Assessment of Complex System


What is the purpose

What is the Purpose?

  • Provide a Comprehensive and Flexible Systems Engineering Development Framework for Complex Systems

    • Builds on the strengths and principles of proven process models such as1:

      • Waterfall, V

      • Iterative

      • Spiral Development

      • Agile

      • Rapid Unified Process

    • Applies key principles that are used throughout an acquisition life-cycle1:

      • Performs risk driven process tailoring throughout life-cycle phases

    • Incremental Commitment Model

    • Boehm, Barry and Lane, Jo Ann, Using the Incremental Commitment Model

      to Integrate System Acquisition, Systems Engineering and Software Engineering, USC, CSSE


Goal to achieve with the framework

Goal to achieve with the Framework

Complex System


Schedule and cost risks

Schedule and Cost Risks


Life cycle phases and activities

Life-Cycle Phases and Activities

Verification & Validation Loop

Preliminary & Detail Design Loop

Requirement Loop

Concept Design Loop


Define work breakdown structure of complex system

Define Work Breakdown Structure of Complex System


Develop baseline schedule for complex system

ID

Name

Duration

3rd Quarter

4th Quarter

1st Quarter

10/4

1

Start Milestone

0 d

2

Payload

125 d

10/3

11/22

3

Design Component A

50 d

11/23

2/5

4

Develop Component A

75 d

5

Bus

125 d

10/3

11/23

6

Design Component B

50 d

11/28

2/5

7

Develop Component B

70 d

2/5

8

Finish Milestone

0 d

Develop Baseline Schedule for Complex System


Develop schedule for each framework

Develop Schedule for each Framework


Map risk drivers to schedule tasks

Risk ID

Risk Driver

Task ID

001

Design issues

002

Resource Availability

003

Resource Complexity

004

Requirement Creep

005

Late Deliveries

006

Duration Underestimation

007

Task Definition Changes

008

Budget Changes

Map Risk Drivers to Schedule Tasks

1

2

3

4

5

6

7

8

  • Risk drivers can be mapped to more than one task

  • Risk assessments will be translated with triangular

  • probability distributions for consequence/impact

  • and with binomial distributions for the likelihood


Model schedule behavior with risk drivers

Risk ID

Risk Driver

Task ID

001

Design issues

002

Resource Availability

003

Resource Complexity

004

Requirement Creep

005

Late Deliveries

006

Duration Underestimation

007

Task Definition Changes

008

Budget Changes

Model Schedule Behavior with Risk Drivers

1

2

3

4

5

6

7

8

  • Run Monte Carlo Simulations for each framework

  • Outputs produce probability density distributions and

  • binomial distributions that associates risk drivers to tasks

  • via likelihood and consequence

  • Indentifies critical path of each framework

  • Quantifies the impacts and consequence of risk drivers

  • Risk dependencies modeled via correlation


Risk assessment of complex system

Risk Assessment of Complex System

  • Cumulative distributions for schedule and costs

  • Impact of risks on specific tasks

  • Probabilistic critical paths for each framework

    identify tasks/activities that will most likely delay

    project

    • Depends on risk

    • Monte Carlo shows whether task was critical per iteration

  • Correlation between tasks when risk driver

    affects durations

  • Task durations can be negatively or positively correlated

  • Framework selection based upon results of schedule and cost

    risk analysis of probability distributions

  • Reveals optimal paths to risk reduction


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