Capturing Experimental Design Insights in Support of the Model-based System Engineering Approach

MacCalman, Alex; Kwak, Hyangshim; McDonald, Mary L.; Upton, Steve

doi:10.1016/j.procs.2015.03.030

Cited by 9 publications

(5 citation statements)

References 17 publications

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“…Literature also suggests to additionally document the dependencies and interrelations between design decisions [20], [21]. This will provide project members with more insight in the cohesion of the entire system [22]. To further extend this system overview, Babar & Gorton [23] and de Lange et al [24] propose to document a decision's context as well.…”

Section: Whatmentioning

confidence: 99%

The documentation of design decisions in engineering projects: A study in infrastructure development

Kinneging¹,

Siebelink

Graaf

et al. 2021

IJISPM

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In most design projects, the documentation of design decisions is considered important. Among others, documentation of design decisions contributes to the traceability of decisions that shape a project’s development process, helps deal with changes in the project and prevents the recurrence of old discussions. Yet, little attention is given to documenting design decisions in the engineering literature. In this study, a theoretical framework for the key elements of this documentation process was developed. Four infrastructure projects were studied and compared to this framework by means of pattern matching. This method compares theoretical and empirical patterns and determines whether they match or do not match. The findings demonstrate that accessibility of documentation for all involved project parties and the division of documentation tasks are in accordance with the literature. However, the documentation of design decisions and their rationale is not done as completely as is recommended in theory. Literature states that the documentation of interrelations and context of decisions should be described thoroughly, but that is barely done in practice. In addition, the findings show that neither immediate documentation nor periodical monitoring of documentation is applied. Based on these findings, this research proposes a strategy for improving the documentation of design decisions.

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Section: Whatmentioning

confidence: 99%

The documentation of design decisions in engineering projects: A study in infrastructure development

Kinneging¹,

Siebelink

Graaf

et al. 2021

IJISPM

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show abstract

“…MacCalman et al. [] describe the types of DOE insights we can capture in support of the MBSE approach.…”

Section: Discussionmentioning

confidence: 99%

A Systems Design Exploration Approach that Illuminates Tradespaces Using Statistical Experimental Designs

MacCalman

Beery

Paulo

2016

Systems Engineering

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This paper describes an approach that leverages computer simulation models and statistical experimental designs for exploration studies during the early conceptual design of a system. We apply the approach to a naval ship design problem and demonstrate how we can illuminate trade decisions among multiple design decisions and evaluation measures using a dynamic dashboard. After performing experimental designs on a collection of simulation models, we can fit statistical models that act as surrogates to these simulations. These surrogate models allow us to explore a wider variety of system alternatives rather than fixating on a narrow set of alternatives. The purpose of the approach is to simultaneously explore the operational and physical domains using statistical surrogate models in order to illuminate trade decisions between the system's operational effectiveness and physical design considerations.

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“…To address these technical gaps, we demonstrated an MBSE methodology that maps SysML elements to experimental design factors and incorporated the DOE analytical insights as derived requirements within our MBSE integrated system model. 16 SysML allows us to express the conceptual model of a design with a wide variety of value properties that define the structural system characteristics. We can explore several design alternatives by establishing an experimental region defined by the low and high settings of the value properties that define the system alternative.…”

Section: Decompose Tradespacementioning

confidence: 99%

“…By building simpler models we can describe the process, system, or model with functional forms that are useful for understanding or predicting behavior. For a thorough explanation of the types of insights we can derive from fitting metamodels, see MacCalman et al 16…”

Section: Technical Requirements For High Performance Computing Clumentioning

confidence: 99%

Leveraging a design of experiments methodology to enhance impacts of modeling and simulations for engineered resilient systems

MacCalman

Goerger

2018

Journal of Defense Modeling & Simulation

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System engineers rely on a variety of models and simulations to help understand multiple perspectives in several domains throughout a system's life-cycle. These domain models include operational simulations, life-cycle cost models, physicsbased computational models, and many more. Currently, there is a technical gap with regard to our ability to untangle system design drivers within system life-cycle domains. This article provides a procedural workflow that addresses this technical gap by leveraging the methods of experimental design in order to clearly identify tradable variables and narrow the search for viable system variants. Our purpose is to illuminate trade decisions across several different viewpoints by integrating metamodels that approximate the behavior of multiple domain models; a metamodel is a statistical function that acts as a surrogate to a model. Model inputs often represent value properties that define a system alternative configuration or environmental conditions that represent uncertain factors within the system boundary. Model outputs represent measures of performance or effectiveness that allow us to compare alternatives and understand the tradeoffs among several objectives. In order to illuminate the tradeoffs that exist in a complex system design problem we propose an approach that approximates model input and output behavior using the functional form of statistical metamodels. After performing an experimental design, we can fit a metamodel with a functional form known as a response surface. We utilize contour profilers that show horizontal cross sections of multiple response surfaces to visualize where key trade decisions exist. Our research supports the tradespace analytics pillar for the development of the engineered resilient system (ERS) architecture. The article concludes with instructions on how to perform simulation experiments to construct a dynamic dashboard that illuminates system tradeoffs.

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Capturing Experimental Design Insights in Support of the Model-based System Engineering Approach

Cited by 9 publications

References 17 publications

The documentation of design decisions in engineering projects: A study in infrastructure development

The documentation of design decisions in engineering projects: A study in infrastructure development

A Systems Design Exploration Approach that Illuminates Tradespaces Using Statistical Experimental Designs

Leveraging a design of experiments methodology to enhance impacts of modeling and simulations for engineered resilient systems

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