Model-Based Trades Implementation Framework

By Clark Kingsford, Associate Technical Fellow; James M. Milstead, Associate Technical Fellow; Theron E. Ruff, Associate Technical Fellow; Elise R. Haley; and Maxwell T. Yavarski

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With the expansion of model-based engineering (MBE) capabilities in system development and design, a developmental program can establish a system architecture model (SAM) to readily manage system requirements, engineering information and design products. In an MBE framework, engineering artifacts are readily captured in a “digital thread” for more effective communication within the engineering team and among stakeholders during product development and for reference throughout the product life cycle. Trade studies are among these artifacts and are used to develop requirements, to choose between potential solutions that meet those requirements, and to help make decisions related to those solutions throughout a program’s life cycle. Model-Based Trades Implementation Framework (MBTIF) represents a significant advancement in the conduct of trade studies in an integrated MBE environment.

Utilizing MBTIF, design engineers can easily conduct trades studies from within a SAM that captures other system design artifacts. In particular, MBTIF:

  • Implements a uniform process for conducting trades.
  • Streamlines trade study review and approval.
  • Provides easy selection of requirements to be traded.
  • Provides a standard set of evaluation criteria to select from.
  • Facilitates use of a single source of truth in the trade studies and integrates trades and trade artifacts with other design artifacts.
  • Applies a standard set of trade computations to all trades.
  • Provides a persistent environment where trades are easily revisited.
  • Captures trades data and results for the life of the program and beyond.

The main innovation of MBTIF is the highly integrated linkage of the trade input data in an MBE environment to the trade math engine through ModelCenter, as shown in Figure 1. This linkage of the data to the math engine is accomplished through a custom-developed analysis execution plug-in. There are existing solutions on the market that can integrate modelbased systems engineering tools (such as Cameo) with analytical tools (such as Excel, Matlab, or ModelCenter) — Phoenix Integration’s MBSEPak1 is an example. However, none of these solutions support the features necessary to address the multiplicity of trade study input or the ability to ingest diagrams and visualization (such as criteria-weighting sensitivity plots) necessary to help the trade study user fully capture and effectively convey the results in an MBE environment.

We implemented the Boeing nine-step trade study process in MBTIF, shown in Table 1.

A uniform process and a standard tool set for conducting design trade studies based on Analytical Hierarchy Process (AHP) 2 is implemented in MBTIF.

The user (typically a design engineer or design team conducting a trade study) is guided by MBTIF-embedded instructions to conduct the trade in an easy-to-use standards-based systems modeling language (SysML) layout diagram in Cameo, referred to as the MBTIF Dashboard. Figure 2 shows the Cameo Dashboard that serves as the interface for loading and viewing trade study data.

Each dashboard element links to a separate Cameo diagram used to enter trade data, execute computations or display trade data. Substeps are included in some cases in order to execute automated MBTIF functions.

After the user defines the trade study objectives, selects evaluation criteria and completes pairwise criteria comparison using MBTIF, the user invokes the math engine to calculate the criteria weighting based on the pairwise comparison inputs from within MBTIF.

In addition to the actual criteria weighting, the math engine returns a consistency ratio. The consistency ratio logic applies the transitive law (if A is greater than B and if B is greater than C, then A must be greater than C) to assess how consistent the design team has been in pairwise comparison of the criteria.

When scoring the trade alternatives, MBTIF supports three scoring methods:

  1. Subjective scoring
  2. Objective scoring
  3. Combined scoring

The subjective scoring method, also referred to as the qualitative scoring method, is based on the subjective judgment of the trade study team.

An entire trade can be completed in MBTIF using only the subjective scoring method. This method can be particularly useful early in a developmental program, when design details have not be defined.

The objective scoring method can be used if all the evaluation criteria can be populated with raw data. In some cases, raw data is not available for one or more of the criteria for a given trade. In this case, MBTIF supports combined scoring logic. MBTIF automatically determines which scoring logic to apply based on the data entered into the scoring diagram, and the math engine then combines the raw data scores and the subjective scores to calculate the composite scores for each design alternative. While combined data scoring retains some subjectivity, it is still a preferred method to the subjective scoring method when raw data for one or more criteria is available.

After the alternative scores are entered by the user, the math engine calculates the trade study composite scores for each alternative by criterion. Figure 3 shows the trade study results. The highest total (final) score indicates the “best” design alternative.

For cases where design alternative scoring results are close, it is important to examine the sensitivity analysis of the trade results. The analysis shows the impact of the criteria weightings on the outcome of the trade. The basic sensitivity analysis logic varies the weighting of the subject criterion across the range from 0.0 to 1.0 while the other criteria weighting is held constant. In this way, the trade team can see how much of a change in a given criterion weight would change the outcome of a trade. An example of a sensitivity analysis curve from the example trade is shown in Figure 4.


  1. MBSEPak.
  2. Robert A. Smith, PhD, Boeing Technical Fellow. “Use of the Analytical Hierarchy Process (AHP) for Concept Definition and Trade Analysis.” March 8, 2017.

Clark Kingsford is a Ground-based Midcourse Defense chief systems engineer.

Jim Milstead is a Boeing Associate Technical Fellow in software engineering and integration.

Theron Ruff is a Boeing Associate Technical Fellow who provides technical leadership for programs and projects related to space, defense and commercial platforms and products.

Elise Haley is lead analyst for a major classified program, specializing in modeling and simulation, model-based systems engineering and system performance.

Table 1

Table 1

Trade study process steps.

Figure 1

Figure 1

MBTIF structure.

Figure 2

Figure 2

Cameo MBTIF Dashboard.

Figure 3

Figure 3

Design Alternative Scoring Results.

Figure 4

Figure 4

Criteria-weighting sensitivity analysis curve example.