Skip to content

newsletter

CM+AI: A Day in the Future Life of a Configuration Manager

On May 15, I presented about the future of configuration management enhanced by AI at the IpX International CM2 Congress. The presentation highlighted a fictitious day with an AI assistant, Chrissy, illustrating its role in tasks like meeting organization, impact analysis, and change planning, while addressing data quality and bias concerns in AI systems.

Configuration Management connects the dots

How Configuration Management is the glue between Model-Based Systems Engineering, Product Line Engineering, and Agile teams.

The article discusses the critical role of Configuration Management (CM) in integrating Model-Based Systems Engineering (MBSE) and Product Line Engineering (PLE) within Agile teams. It emphasizes that CM is essential for managing product diversity and enabling collaboration, ultimately supporting the fast-paced evolution of engineering and enhancing customer satisfaction through better adaptability.

Lamppost blocks partkingspot

Embedding the Change: from Dynamic to Static

In a recent IpX True North Podcast, Ray Wozny and Ken Black discussed the importance of Enterprise Change assessment or Impact Analysis for successful change management. They emphasized that effective documentation and ownership are crucial to avoid costly mistakes. Cultural integration of change is essential to ensure sustainable improvements in organizations.

to revise or not to revise

Parts don’t have Revisions

In his year-end post, Martin Eigner discusses the nuances of part revisions within PLM tools, summarizing insights from previous writings. He highlights that parts themselves shouldn’t have revisions; instead, data sets linked to parts should. Various methods for managing Bill of Materials revisions are explored, noting each approach’s strengths and weaknesses.

Achievements 2023

The Future of CM – Achievements – 2023

In 2023, significant milestones were achieved, including a 380-subscriber growth for the newsletter “The Future of CM,” collaboration on two popular articles, and the publication of “The Essential Guide to Part Re-Identification,” rated 4.6 stars on Amazon. Future projects and collaborations are planned for 2024, enhancing engagement in Configuration Management.

Configuration Management: Change is coming

Help…Why is Configuration Management so Hard to Implement?

Configuration Management faces challenges in implementation due to the need for widespread organizational buy-in, making change difficult. It is often undervalued, treated as part of engineering when it should be recognized as a distinct discipline. Proper Configuration Management ensures trust in crucial systems and connects various organizational functions effectively.

Boost your Knowledge Graph with Events to gain Untapped Insights

This article discusses enhancing the CM Baseline’s knowledge graph by integrating product and event data, creating a comprehensive ‘product 360.’ It emphasizes the significance of Event Knowledge Graphs to uncover insights overlooked by traditional analysis. By modeling relationships between events and states, it proposes improved predictive capabilities and behavior understanding in product development.

Customer Focus

How Configuration Management supports the shift in Customer Focus

The article discusses the need for a shift in customer focus within the automotive industry, particularly among Western OEMs, to adapt to shorter product life cycles driven by software integration. It emphasizes the importance of agile methodologies in product development, configuration management adjustments, and collaborating across hardware and software engineering to meet evolving customer expectations efficiently.

autonomous driving object detection

Is the introduction of AI in products, changing the paradigm of testing?

Recent incidents involving autonomous vehicles highlight safety concerns and the complexities of AI development. As AVs face challenges in predictable behavior, the need for Explainable AI becomes crucial. Ensuring accountability and transparency in AI decision-making can build public trust while addressing the risks associated with testing on public roads.