Configuration Management (CM) is crucial in engineering, ensuring that documentation is properly released and effective before use in design and production. Adhering to CM principles promotes compliance and minimizes risks of rework and delays. Proper release and change control enhance data traceability, fostering collaboration among stakeholders.
I joined Joseph Anderson and Martin Haket on the IpX True North Podcast. This series is about the topics identified in the CM2-500 standard. We will discuss these topics in the context of the Future of Configuration Management. The third topic is about data integrity and operability and the fear of change.
Organizing data within organizations enhances efficiency, flexibility, and agility. A well-structured system facilitates collaboration among groups, while improper alignment can create inefficiencies. The article proposes a model comprising network nodes, datasets, and relationships to streamline information organization, ensuring clarity and integrity during change assessments. An effective structure leads to improved interactions.
Jos Voskuil, known as the PLM Doctor, interviewed me about Product Lifecycle Management (PLM) and Configuration Management (CM). We discussed CM definitions, practices, roles, and their integration within PLM as an enterprise backbone. We also explored regulatory needs, future modeling, and resources for further reading on these topics.
The article discusses the ongoing debate about parts and revisions in PLM tools, stressing that parts should not have revisions while datasets associated with them should. It advocates for linking datasets and parts to enhance change agility, suggesting a model where parts lack revisions but datasets possess them for efficient management and impact analysis in engineering changes.
The transition to a Model Based Enterprise (MBE) offers benefits for impact analysis and decision-making. However, challenges arise in identifying ownership and efficiently planning for changes within modeled information. To enhance usability and maintainability, it is crucial to clearly define dataset boundaries and facilitate decoupling of various elements to ensure effective planning and execution of tasks.
The Industry 4.0 Committee of the IPX Congress distinguishes between models and datasets in configuration management. They define models as constructs supporting value chain activities and categorize them into application, definition, and verification/simulation models. These distinctions are essential for understanding their role in the product development process and addressing challenges in Industry 4.0.
The article discusses the need for structured models and datasets in managing product complexity within engineering and manufacturing. It emphasizes the significance of a Core Platform Network that captures various requirements and dependencies, facilitating effective configuration management. Different views, including engineering and manufacturing, are essential for impact analysis and maintaining alignment between product breakdowns.
Technology advancements, particularly in Industry 4.0 and the Internet of Things, are significantly transforming Configuration Management (CM). Moving from document-based to model-based approaches presents challenges in knowledge artifact identification and change management. The Industry 4.0 committee emphasizes the need to rethink CM methodologies to adapt and efficiently manage these evolving dynamics.