Books

Learn SysML v2 with the ultimate guide for all skill levels in MBSE. Authored by insiders, it's your key to unlocking the full potential of system modeling and a passport to mastering your MBSE.

The book highlights the significance of software in systems engineering and uses AI as a subject matter expert. It presents a comprehensive example that covers SysML modeling, including requirements, use cases, logical/ physical architecture, and parametric simulation. It then continues into software, leveraging AI's code generation capabilities to produce software including microcontroller, UI, and DMBS code. It introduces a variety of personas and agents that can help engineers communicate with AI about systems and software engineering. The book also introduces SysML v2, focusing on the new language model and exploring AI's ability to generate models via code generation. Perhaps most importantly, it provides a straightforward roadmap for hardware/software co-design, accelerated at every step by AI. Whether you're a systems or software engineer, or just interested in how to use AI for engineering, AI Assisted MBSE with SysML will prove to be a valuable guide.

SYSMOD is an MBSE toolbox for pragmatic modeling of systems. It is well-suited to be used with SysML. The book provides a set of methods with roles and outputs. Concrete guidances and examples show how to apply the methods with SysML.

Hands on Labs to prepare you for a career in Linux or system engineering. Built by the Professional Linux User's Group to focus on exactly what the professional needs in the enterprise.

"If you intend to use machine learning to solve business problems at scale, I'm delighted you got your hands on this book." —Cassie Kozyrkov, Chief Decision Scientist at Google "Foundational work about the reality of building machine learning models in production." —Karolis Urbonas, Head of Machine Learning and Science at Amazon

Linux is one of the best decisions you can make for your computer — but knowing where to start is the hard part. This guide walks you through everything: choosing a distribution, installing it, and using it confidently every day. It was written by Jay LaCroix of Learn Linux TV, for complete beginners. No prior experience required.

This book familiarizes readers with the world of LLM and agentic AI, and helps them quickly gain a working-level knowledge of building useful agentic AI solutions for process industry operations. With no prerequisites required, practical demo applications, and a hands-on approach adopted throughout, this book makes advanced AI technologies accessible to process engineers and data scientists alike. It aims to help process data scientists and engineers take their first confident steps into Agentic AI world, understand the full picture, and build a strong enough foundation to keep learning and building on their own. Also available here.

This short book introduces process data scientists to knowledge graphs and GraphRAG, a powerful combination that overcomes the limitations of vanilla RAG when answering the kind of cross-document, relationship-heavy questions that process engineers usually care about. With a hands-on, application-driven approach, the book walks readers through the complete pipeline: designing an ontology for plant data, using LLMs to extract entities and relationships from incident reports, building and querying the graph in Neo4j, and finally assembling everything into a demo web application.

The most advanced (show me!) systems engineering writing on the 'constraints' subject. For technical leaders.

This book is a quick foray into the world of deep learning-based computer vision and abnormal equipment sound detection. The readers are introduced to the ease with which powerful equipment and product quality monitoring solutions can be built using sound and visual data.

Why do so many Lean implementations fail to deliver stable flow? Because they ignore the core secret behind Just-in-Time: Heijunka.

The biggest challenge in implementing Standard Work is finding the right balance: Between giving employees clear, repeatable standards — and giving them space to think, improve, and grow.

Inference engineering is now its own discipline, with unique challenges around speed, cost, reliability and scale. This practical guide takes you from core concepts to production systems, showing how modern inference architectures work, how to optimize them and how to make better engineering decisions through measurement and trade-off analysis.

An MBSE workflow for automotive systems engineering teams — run V-model programmes on real agile sprints, with ASPICE and ISO 26262 evidence produced as you go, not reconstructed before the audit.

A practical implementation framework covering 22 essential data center operational domains. Assess gaps, establish priorities and build a controlled improvement roadmap.