As products become increasingly software-heavy and connected, model-based systems engineering is transforming from a specialised practice into an essential approach, driven by digital twin technology and data-driven workflows, to manage complexity more effectively.
Model-based systems engineering is moving from a specialist practice to a more practical necessity as products become more software-heavy, more connected and harder to manage with static documents alone. In an interview published by Electronic Design, Becky Petteys of MathWorks argued that the old mix of Word files, spreadsheets and slide decks struggles to keep pace with modern systems because it leaves relationships between requirements, architecture and interfaces largely implicit. That makes it difficult to maintain a single source of truth, and it increases the risk that teams working on different disciplines will drift out of sync.
The appeal of MBSE, according to the Electronic Design report, is that it replaces scattered paperwork with a shared model that shows how system elements fit together and behave. That idea is echoed by Zuken, which says document-centric engineering is increasingly strained by cyber-physical products combining mechanical, electrical and software components. One example cited by Electronic Design is Gulfstream Aerospace’s eSAM approach, built on System Composer, which the company uses to replace much of its document-based workflow with functional and logical architecture models.
A major extension of that approach is the use of high-fidelity digital twins. The Electronic Design interview describes these as executable models that let engineers simulate how a system behaves over time rather than merely sketching it on paper. Academic work in MDPI and ScienceDirect similarly frames digital twins as dynamic virtual representations that can be kept in step with a physical asset across its lifecycle. Together, those sources suggest the same direction of travel: verify earlier, test more often in simulation, and expose integration problems before hardware exists.
Adoption is strongest where complexity is rising fastest. Electronic Design points to aerospace, automotive, defence, energy and healthcare, where software-defined products and systems-of-systems architectures make late discovery of interface problems especially costly. The article also notes Siemens Energy’s use of Simulink and MBSE methods in project line engineering, combining standardised architectures with project-specific variation. That balance of reuse and customisation is becoming more valuable as organisations try to keep pace with tighter regulatory, safety and update requirements.
AI and data science are beginning to make MBSE workflows more productive, but they are not replacing engineering judgement. According to the Electronic Design interview, AI can draft early requirements, generate initial models, produce reduced-order simulations and help with consistency checks and documentation. Data science adds another layer by clustering results, spotting anomalies and connecting simulation, test and operational data. The challenge, as Electronic Design notes, is not only technical; it is also cultural, because many firms still rely on document-led habits and fragmented proprietary tools. Emerging standards such as SysML v2 may help, but the broader shift toward interoperable, data-centric engineering is still underway.
Source Reference Map
Inspired by headline at: [1]
Sources by paragraph:
Source: Noah Wire Services
Noah Fact Check Pro
The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The article was published on April 30, 2026, making it current. However, the content heavily references a recent interview with Becky Petteys of MathWorks, which may indicate reliance on a single source.
Quotes check
Score:
6
Notes:
The article includes direct quotes from Becky Petteys. While these quotes are attributed, they cannot be independently verified through other sources, raising concerns about their authenticity.
Source reliability
Score:
7
Notes:
Electronic Design is a reputable publication within the electronics industry. However, the article’s heavy reliance on a single interview with a representative from MathWorks may introduce bias, as the company has a vested interest in promoting its products and services.
Plausibility check
Score:
7
Notes:
The claims about the limitations of document-based systems engineering and the benefits of model-based systems engineering (MBSE) are plausible and align with industry trends. However, the article lacks supporting evidence from independent sources to substantiate these claims.
Overall assessment
Verdict (FAIL, OPEN, PASS): FAIL
Confidence (LOW, MEDIUM, HIGH): MEDIUM
Summary:
The article presents information on model-based systems engineering trends for 2026, primarily sourced from an interview with Becky Petteys of MathWorks. While the content is current and plausible, the heavy reliance on a single source with potential biases, the inability to independently verify quotes, and the lack of supporting evidence from other reputable sources raise significant concerns about its reliability and objectivity.
Supercharge Your Content Strategy
Feel free to test this content on your social media sites to see whether it works for your community.
