Garima Bhatia

The emergence and adoption of Model‐Based Systems Engineering (MBSE) is driven in part by claimed benefits over traditional Document‐Based Systems Engineering. Despite high enthusiasm for MBSE, few studies have evaluated the value of MBSE implementation or the needs in MBSE implementation across various system types and industry sectors, which may require differing drivers of implementation and analyses of added value. This study investigates the perceptions of MBSE across sectors including Commercial, Contractor , and Government , as well as across system types including Astronautical, Aeronautical , and Infrastructure , to determine the perceived drivers and considerations of MBSE implementation across different industries. From 60 academic sources, this study collected and coded over 2900 claims about MBSE using 68 MBSE attributes. Our study's findings determine that the considerations for MBSE implementation likely vary by both sector and by system. Perceptions of MBSE, regardless of application grouping, were largely positive—negative attributes often captured unfavorable perceptions of implementation and tooling immaturity. The findings of this study suggest that practitioners may need to tailor the implementation of MBSE partly to their organizational priorities and needs, and to be cautious of relying only on broadly reported benefits of MBSE.

Although Model‐Based Systems Engineering (MBSE) is quickly becoming adopted in Systems Engineering (SE), there have not been many studies evaluating literature to determine the perceived value of implementing MBSE. This research first identifies and discusses previous studies on the justification or rejection of MBSE. This study investigates how the SE community perceives the value of MBSE by coding and analyzing positive and negative descriptions of MBSE; perceived benefits and drawbacks of implementing MBSE; and the evidence and metrics used to substantiate and measure each claim about MBSE. From 60 academic sources, this study collected and coded over 2900 claims on MBSE. Our findings determine the most positive attributes of MBSE to be Verification & Validation Capability, Consistency, Reasoning , and Risk & Error Manageability , while the most negative attributes were Approach Understandability, Acceptability, Familiarity , and Approach Complexity . The most‐stated benefits were Reduced Time, Better Communication/Information Sharing, Reduced Costs , and Better Analysis Capability . The most claimed drawbacks were Increased Costs, Increased Time, Increased Effort , and Worsened Capability . A large share of claims (47%) about MBSE was based on author opinions. Most claims (86%) were not substantiated by a metric.

The realization of large-scale complex engineered systems is contingent upon satisfaction of the preferences of the stakeholder. With numerous decisions being involved in all the aspects of the system lifecycle, from conception to disposal, it is critical to have an explicit and rigorous representation of stakeholder preferences to be communicated to key personnel in the organizational hierarchy. Past work on stakeholder preference representation and communication in systems engineering has been primarily requirement-driven. More recent value-based approaches still do not offer a rigorous framework on how to represent stakeholder preferences but assume that an overarching value function that can precisely capture stakeholder preferences exists. This article provides a formalism based on modal preference logic to aid in rigorous representation and communication of stakeholder preferences. Formal definitions for the different types of stakeholder preferences encountered in a systems engineering context are provided in addition to multiple theorems that improve the understanding of the relationship between stakeholder preferences and the solution space.

Examining past research using content analysis can provide detailed information about the trends a discipline has displayed over years or decades. Disciplines such as software engineering and hospitality management have used methods for analyzing topic frequencies in the past. This paper uses similar methods to study the presence of systems engineering topics in literature to understand the occurrence of approaches and metrics in the community over time. This paper reviews the trends of systems engineering topics over the years 1998–2016 by performing a content analysis of four systems engineering and design engineering journals. A mathematical analysis of the trends is performed using rank ordering and a rank correlation metric. The study shows that model-based approaches have grown significantly since the early 2000s, as advocated in the INOCSE MBSE initiative, while other approaches such as Taguchi’s method and axiomatic design have been seen less frequently in literature. Systems engineering metrics that have been frequently seen in literature include complexity, reliability, and quality. The results from this research provide a portrait of the systems engineering landscape.