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MBSE 솔루션 및 소프트웨어/시스템 모델링 툴 : AI 시대를 향한 추상화와 아키텍처
MBSE Solutions & Software/System Modeling Tools: Abstraction & Architecture for the AI Era
상품코드 : 1927574
리서치사 : VDC Research Group, Inc.
발행일 : 2026년 01월
페이지 정보 : 영문 43 Pages/446 Exhibits
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한글목차

오늘날 임베디드 시스템, 엣지 시스템, AI 시스템은 고도로 복잡해지면서 엔지니어링 베스트 프랙티스에 대한 새로운 관심이 요구되고 있습니다. 기업은 혁신을 촉진하고 변화를 적절히 관리하기 위해 필요한 접근 방식을 파악해야 합니다. 그 핵심적인 방법 및 툴이 MBSE(Model Based Systems Engineering, 모델 기반 시스템 엔지니어링)입니다. MBSE는 차세대 설계 요구사항에 대응하기 위해 지속적으로 진화하고 있는 검증된 일련의 실무 기법 및 기술입니다.

이 보고서에서는 표준 언어 기반 모델링(SLBM) 툴(예: SysML/SysML v2, Modelica 등) 및 독점 언어 기반 모델링(PLBM) 툴(예: SCADE, Simulink 등) 시장 동향과 신흥 동향을 분석합니다. 이 보고서에서는 MBSE 솔루션 및 소프트웨어/시스템 모델링 툴 시장에 영향을 미치는 새로운 동향과 기술, 표준 및 규제, 엔지니어링 동향, 경쟁 전략에 대해서도 상세하게 조사 분석했습니다.

이 보고서에서 언급된 조직

AI는 엔지니어링 조직의 요구와 기회를 재정의하고 있습니다. 이미 소프트웨어 시스템 모델링 툴 사용자들은 AI 워크로드를 통합하는 엔드 디바이스/시스템부터 자체 워크플로우내 AI 활용에 이르기까지 다양한 이용 사례에서 AI의 초기 도입자가 되고 있습니다. 많은 벤더들이 AI를 통합한 인텔리전스로 ALM 툴을 강화하는 가운데, 모델링과 MBSE가 특히 적합한 AI 시스템 개발의 두 가지 명확한 사용사례가 있습니다. 첫째, SysML 툴은 엔지니어링 조직이 첨단 시스템 아키텍처 설계를 지원하고, 안전이 매우 중요한 프로젝트에서 문서화 및 추적성 기반을 구축하는 데 이상적이라는 점입니다. MATLAB/Simulink, SCADE 등 독자적인 언어 기반의 툴은 첨단 알고리즘과 복잡한 환경 및 운영 요인에 대한 실시간 대응이 필요한 시스템의 설계, 개발, 시뮬레이션을 지원합니다. 시스템 복잡성 증가, 안전에 중요한 기능적 요구사항, 효율성에 대한 기업의 요구가 결합되어 향후 수년간 고급 모델링 툴와 MBSE 원칙에 대한 수요가 증가할 것으로 예측됩니다.

주요 조사 결과

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수요측 조사 : 개요

개요

세계 시장 : 개요

최근 시장 동향

수직 시장

지역 시장

경쟁 구도

엔지니어링 인사이트

범위와 조사 방법

저자 소개

VDC 조사 소개

KSA
영문 목차

영문목차

Inside this Report

The complexity of today's embedded, edge, and AI systems demands new attention to engineering best practices. Organizations must identify the approaches required to drive innovation and manage change. Chief among those methods and tools is MBSE, a proven set of practices and technologies evolving to meet the needs of next-generation design requirements.

This report analyzes the market and emerging trends for standard language-based modeling (SLBM) tools (e.g., SysML/SysML v2, Modelica, etc.), as well as proprietary language-based modeling (PLBM) tools (e.g., SCADE, Simulink). It includes detailed discussion of emerging trends and technologies, standards and regulations, engineering behaviors, and competitive strategies that are impacting the market for MBSE solutions and software/system modeling tools.

What Questions are Addressed?

Who Should Read this Report?

This research program is written for those making critical business decisions regarding product, market, channel, and competitive strategy and tactics. This report is intended for senior decision-makers who are developing embedded technology, including:

Organizations Mentioned in this Report

Demand-side Research Overview

VDC launches numerous surveys of the IoT and embedded engineering ecosystem every year using an online survey platform. To support this research, VDC leverages its in-house panel of more than 30,000 individuals from various roles and industries across the world. Our global Voice of the Engineer survey recently captured insights from a total of 600 qualified respondents. This survey was used to inform our insight into key trends, preferences, and predictions within the engineering community.

Executive Summary

The overall market for MBSE and software/system modeling tools reached $B in 2024 and will reach $B in 2029, a CAGR of % over the forecast period, driven by strong growth within the embedded solution market. We believe this growth could accelerate even further in the coming years, as a function of both organic market need as well as further evangelism by the growing roster of PLM, EDA, and ALM companies all working to integrate more MBSE and SysML v2 solutions across their portfolios.

AI is redefining the needs of and opportunities for engineering organizations. Already, software and system modeling tool users are early adopters of AI across a range of use cases from end devices/systems integrating AI workloads to using AI within their own workflows. While many vendors are enhancing their ALM tools with AI-infused intelligence, there are two distinct use cases for AI system development for which modeling and MBSE are well suited. For one, SysML tools are ideal to help engineering organizations architect advanced systems and establish an underpinning for documentation and traceability for safety-critical projects. Proprietary language-based tools, such as MATLAB/Simulink and SCADE, can help organizations design, develop, and simulate systems with advanced algorithms and needs for real-time response to complex environmental, operational factors. We believe that the combination of advancing system complexity, safety-critical functionality requirements, and corporate mandates for efficiency will drive increasing need for sophisticated modeling tools and MBSE principles for years to come.

Key Findings

Code generation has been a key area of extension and value add for modeling tool vendors for over a decade. In practice, however, legacy solutions fell short due to shortcomings of architectural abstractions and the realities of fragmented hardware ecosystems. Despite generative AI coding capabilities only recently becoming widely commercially available, users of modeling tools have eagerly adopted these solutions at a disproportionately high rate, with % using the technology - a rate twice that of the industry overall.

Developers across both enterprise and embedded domains report significant reservations regarding the trustworthiness of AI-generated code. Across organization types, engineers identified code quality, security, compliance, and license infringement as leading concerns. Embedded engineers cited code quality as the absolute highest concern due to the importance of software performance in embedded system function. Software must run exactly as intended, regardless of deployment environment. Tool providers should restrict model training databases to ensure that AI generates reliable code based on tested documentation and examples, which will also help end users reduce licensing risks. In tandem, solution providers should offer model training and refinement as a service to further ensure a level of specialized code quality that generic LLM-based solutions cannot provide.

To address compliance concerns, modeling tool vendors should partner with requirements management, test, and software composition analysis (SCA) providers. Engineering organizations must effectively manage and trace

requirements to meet standards such as DO-178C and ISO 26262. IBM DOORS, Jama Connect, and Polarion from Siemens all help engineers track compliance from design to code to test. Similarly, SCA tools from vendors such as Black Duck, CodeSecure, Mend, Revenera, Sonatype, and Snyk track violations from known repositories to ensure that open source and AI-generated code do not violate existing licenses. In the same way that application lifecycle management, software testing, and SCA have converged in recent years to form single-platform solutions, AI code generation solutions and extensions fit directly within the software tooling landscape. A fully combined solution featuring modeling, requirements management, code generation, and software verification and validation would give customers a single dashboard or source of truth for code generation analytics, quality, induced risks, and impact on development time.

Table of Contents

Inside this Report

What Questions are Addressed?

Who Should Read this Report?

Organizations Mentioned in this Report

Demand-side Research Overview

Executive Summary

Global Market Overview

Recent Market Developments

Vertical Markets

Regional Markets

Competitive Landscape

Engineering Insights

Scope & Methodology

About the Authors

About VDC Research

List of Exhibits

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