SodiusWillert Blog

Impressions of INCOSE IS 2026

Eran Gery — Fri, 31 Jul 2026 08:57:12 GMT

The INCOSE International Symposium (IS) 2026, held in Yokohama, Japan, during June 13-18, brought together around 800 in-person attendees, plus a strong online audience, from the global systems engineering community. Attendance jumped by about 30% compared to last year, despite the far-flung location. This year’s agenda is packed with roughly 160 sessions, including tutorials, paper presentations, and vendor tracks.

How to Achieve Trustworthy Engineering Data in A&D Programs?

Eran Gery — Mon, 27 Jul 2026 12:03:30 GMT

The tools are there (MBSE, PLM, ALM), and most A&D programs have invested heavily in their Engineering Toolchain over the years. Yet they still struggle with fragmented data, unclear authoritative sources, broken traceability, and lack of cross-tool analytics and viewpoints.

Meanwhile, the US DoD Data Strategy requires that engineering data be visible, accessible, linked, trustworthy, interoperable, secure, and understandable. DoDI 5000.97 makes this mandatory for acquisition and engineering programs.

Meeting these goals requires more than domain tools. As a matter of fact, implementing tools without a deliberate and thought-out data architecture and infrastructure behind them is where most engineering programs stall.

This article explores why and identifies the architectural foundations that are typically missing:

Standard-based interoperability
Cross-domain traceability
Cross-domain viewpoints and analytics
Configuration management

It concludes with a practical picture of how these foundations translate into trustworthy, connected engineering data within programs.

Civil Aviation & Defense Traceability: Industry Standards and Constraints

csimon@sodiuswillert.com (Célina Simon) — Thu, 23 Jul 2026 14:43:29 GMT

More than just a documentation exercise, traceability in aviation and defense is a legal, contractual, and engineering obligation, one that must survive decades of program evolution, tool migrations, and organizational change.

This guide explores the main standards that define traceability, the specific constraints that make it genuinely challenging, and the business consequences of getting it right.

How to Reverse Engineer Code and Models into IBM Rhapsody with AI?

Andy Lapping — Tue, 23 Jun 2026 15:51:23 GMT

Many engineering teams have at least one system that nobody fully understands anymore. The developer who originally created it has left, the documentation is minimal, and the model (if there ever was one) is likely out of date. So, getting back to a working understanding of that codebase can take weeks. And that's if they're lucky...

Reverse engineering is commonly suggested as a solution within IBM Rhapsody. However, the process of reverse engineering can be complex, time-consuming, error-prone, and generally unpopular among team members. On top of that, Rhapsody's built-in reverse engineering is limited to C, C++, and Java. For any other language or format, IBM Rhapsody cannot help you.

This is where AI can make a significant difference.In this article, I’ll show you how to use AI Modeling Assistant for IBM Rhapsody to reverse engineer existing code and design artifacts directly into a Rhapsody model, using nothing but natural language prompts.

How to Bridge the Traceability Gap Between Requirements and Models?

csimon@sodiuswillert.com (Célina Simon) — Fri, 05 Jun 2026 12:45:17 GMT

If your teams use both a requirements management tool and a system modeling tool on cross-domain engineering programs, you’ve probably experienced what happens when these two environments are not connected. Requirements change, but the modeling team is not properly notified. Coverage analysis depends on manual checks, and impact analysis often relies on the person with the most experience and knowledge of the model. If that person is unavailable or has left the project, the analysis takes much longer or gets done incompletely.

How to Architect System Models for Cross-Program Reuse

Eran Gery — Fri, 29 May 2026 15:43:26 GMT

Many organizations invest in MBSE but struggle to reuse system models beyond a single project. Architectures, behaviors, and patterns are recreated instead of being leveraged, leading to rework and inconsistencies. This article explains why model reuse across programs is challenging and how to overcome those challenges successfully.

We will first explore the different types of system models that can be reused, from simple types and interfaces to full mission-level architectures, to understand why reuse becomes increasingly difficult as model complexity and context grow. Then, we will examine the root causes that make reuse so challenging in SysML, and walk through practical strategies for both homogeneous and cross-organizational environments, showing how SysML v2 can address these issues.

SysML v1 vs SysML v2: What Changes for Engineering Teams?

csimon@sodiuswillert.com (Célina Simon) — Tue, 26 May 2026 08:29:39 GMT

SysML v2 is built on a different foundation than SysML v1. For engineering teams, that difference directly affects how models are defined, how behavior is specified, how tools integrate, and how teams collaborate. This article focuses on what actually changes for engineering teams when moving from SysML v1 to SysML v2. It includes modeling practices, interoperability, extensibility, and day-to-day workflows.

How to Create a System Model from a PDF with AI in IBM Rhapsody?

Andy Lapping — Mon, 11 May 2026 07:34:39 GMT

If you work with IBM Rhapsody, there is a good chance many of your projects start the same way: someone sends you a PDF full of textual requirements and expects a model. What follows is usually hours of manual work, reading through the document, identifying requirements, creating model elements one by one, structuring them into packages, and hoping nothing gets lost along the way.

AI can help streamline this process. With the right tooling, an AI assistant can read that PDF, extract the requirements, and build the initial model structure in IBM Rhapsody. You'll still want to review and refine the design, but the heavy work is done. Plus, the model stays faithful to what the PDF actually contains.

In this article, I’ll walk you through how to do this using AI Modeling Assistant for IBM Rhapsody, SodiusWillert’s AI extension that brings AI-assisted MBSE directly into the Rhapsody environment.

Reliable Impact Analysis Starts with Interconnected Engineering Data

csimon@sodiuswillert.com (Célina Simon) — Mon, 13 Apr 2026 14:27:01 GMT

Impact analysis refers to the structured process of evaluating the potential consequences of a proposed change before it is implemented. It helps identify the scope, scale, and dependencies affected by modifications to systems, requirements, or processes. As such, it plays a central role in change management within complex engineering programs. Despite this, impact analysis remains inconsistent and difficult to rely on in many organizations. The reason is that they repeatedly face the same issue: engineering data remains siloed and disconnected across tools and domains.

A Practical Guide for SysML v2 Adoption

Eran Gery — Fri, 03 Apr 2026 14:42:43 GMT

SysML v2 marks a significant evolution in MBSE, designed from the ground up with greater precision, rigor, and a strong focus on interoperability and ecosystem enablement. Rather than a simple update to SysML v1, it introduces a fundamentally different architecture and modeling approach, which creates challenges for organizations with existing SysML v1 investments.

This article explores practical adoption strategies, emphasizing incremental approaches and the coexistence of SysML v1 and SysML v2 rather than encouraging a wholesale migration.