This article discusses the importance of structured reasoning capture in product design, emphasizing that while documenting decisions can expose liability in court, disorganized records pose even greater risks. Effective governance of documented reasoning creates a defensible narrative, contrasting with unregulated documentation, which can lead to catastrophic legal outcomes, as seen in high-profile cases.
This article discusses the risks associated with Product Memory in design processes, emphasizing the importance of securing not just product data but also the underlying rationale behind design decisions. It warns that careless handling of this information can create significant competitive risks and calls for stringent access controls and classification to protect sensitive reasoning.
The article highlights the challenges of capturing tacit knowledge in engineering design, emphasizing that valuable insights often exist informally within experienced professionals. It advocates for recording reasoning during decision-making processes and acknowledges the importance of mentoring, suggesting a balanced approach between documentation and recognizing human expertise in knowledge management.
The article examines the concept of Product Memory within the context of configuration management (CM), highlighting the importance of preserving the reasoning behind engineering decisions. It emphasizes that while CM effectively manages the “what” of product data, it often overlooks the critical “why.” This gap can lead to significant risks, particularly in complex systems. The integration of AI could assist in retrieving and recording this reasoning, reinforcing the value of… Read More »The Question Your Configuration Management System Can’t Answer!
The article discusses the application of AI in engineering change management (ECM), highlighting two studies that focus on predicting change propagation and adherence to effectivity dates. It emphasizes the importance of confirming the scope before effectivity and the need for documented processes to support AI modeling. Practitioners should consider the quality of process inputs when deploying AI tools.
The article discusses the concept of configuration debt in product development, highlighting how initial errors in product variant assessments can lead to compounded issues over time. Unlike technical debt, configuration debt manifests in hidden warranty claims and field failures, stemming from unaddressed applicability confirmations that impact subsequent engineering decisions.
The article discusses the importance of distinguishing between applicability and effectivity in change management. It highlights how confusion arises when both concepts are tackled simultaneously, leading to unresolved issues during meetings. The author advocates for a structured process that separates scope confirmation from effectivity assignment, enhancing productivity and decision-making in organizations.
The article discusses the challenges in reconciling discrepancies between the as-designed, as-built, and as-maintained baselines in engineering and manufacturing. It highlights how AI can systematically identify these gaps, enabling better tracking and traceability, while emphasizing the human role in interpreting these discrepancies to ensure effective configurations and risk management.
This article discusses the integration of AI in configuration management, highlighting the challenges posed by probabilistic decision-making compared to deterministic systems. It emphasizes the need for governance frameworks to validate AI outputs against compliance requirements and establish confidence thresholds for manual review in decision-making processes.
In the 53rd edition of the Future of CM Newsletter, I continue my collaboration with IpX – Institute for Process Excellence in our “How Do You CM2?” series. This time, an article dear to my heart: the integration between CAD models and Parts. What do you think is the right strategy?