Examples of ETD (Part 1)
The first decisions are critical when defending against technical debt
A critical step to stop incurring technical debt is selecting the right software to manage your engineering data to start with. Implementing a software that meets the current and future needs for engineering is vital to the long term success of the management of your engineering data.
When evaluating document management systems for engineering data, it's important to consider several key areas to ensure that the chosen system meets the specific needs of your organization. Here are some areas of concern to vet during the evaluation process:
Integration with Engineering Tools: Ensure that the document management system seamlessly integrates with the CAD/CAM/CAE tools and other engineering software used within your organization. This integration should facilitate efficient collaboration and workflow automation between the document management system and engineering applications.
Version Control and Revision Management: Verify that the document management system provides robust version control capabilities, allowing users to track changes, manage revisions, and access previous versions of engineering documents easily. This feature is critical for maintaining data integrity and ensuring accurate documentation of design iterations.
Metadata Management: Evaluate the system's ability to capture and manage metadata associated with engineering documents, such as project information, part numbers, revisions, and other relevant attributes. Effective metadata management facilitates efficient search, retrieval, and organization of engineering data within the document management system.
Security and Access Control: Assess the system's security features, including user authentication, access control, and permissions management. Ensure that the document management system provides granular control over user permissions, allowing administrators to define access levels based on roles and responsibilities within the organization.
Workflow Automation: Determine whether the document management system supports workflow automation capabilities, such as approval routing, task assignment, and notification mechanisms. Workflow automation streamlines document review and approval processes, reducing cycle times and improving productivity.
Scalability and Performance: Consider the scalability and performance of the document management system, particularly its ability to handle large volumes of engineering data and support concurrent user access. Ensure that the system can scale to accommodate future growth and maintain optimal performance under heavy workloads.
Compliance and Regulatory Requirements: Evaluate whether the document management system complies with relevant industry standards and regulatory requirements, such as ISO 9001, AS9100, or FDA regulations. Ensure that the system supports compliance-related features, such as audit trails, electronic signatures, and document retention policies.
User Experience and Training: Assess the usability and intuitiveness of the document management system's user interface, as well as the availability of training and support resources. A user-friendly interface and comprehensive training materials can facilitate user adoption and minimize resistance to change within the organization.
Now that we have defined some basic guidelines for selecting a data management software, let’s look at some of the situations that can create EDMTD once a system is purchased.
Navigating Technical Debt in CAD Systems: Harnessing Metadata
Introduction: In the realm of modern CAD systems, metadata emerges as principle linchpin for steering clear of technical debt while optimizing enterprise efficiency. Beyond mere data organization, metadata serves as a potent catalyst for accurate and dynamic downstream data, especially in the critical area of Bills of Materials (BOM). Below is a list of how leveraging metadata within traditional CAD systems not only prevents technical debt accumulation, but also streamlines BOM creation and management.
Capturing Key Metadata:
Description: Detailed descriptions ensure clarity and precision in every component, forming the backbone of an accurate BOM.
Material Information: Metadata capturing material details empowers various teams with insights into product compliance and performance.
Finishes: Documenting finish specifications within metadata ensures consistency and quality in the BOM, reflecting real-world manufacturing requirements.
Vendor Names and Part Numbers: Integrating vendor details and part numbers facilitates seamless procurement and supply chain management, minimizing errors and delays in BOM creation, even if that data is suggested source and not a mandated one.
Design Part Numbers: Metadata-driven part numbering ensures coherence between design elements and the BOM, streamlining referencing and traceability processes.
Approval Signatures (Names and Dates): Including approval signatures and dates in metadata establishes accountability and transparency in BOM creation, crucial for regulatory compliance and quality assurance.
Current Status: Real-time status updates within metadata offer instant visibility into BOM revisions and project milestones, enabling proactive decision-making and risk management.
Related Specifications: Linking design specifications and standards to metadata ensures BOM alignment with project objectives, fostering consistency and compliance.
The list provided highlights the potential wealth of valuable data stored in CAD models and the PDM or PLM systems overseeing them. However, it's crucial to recognize the limitations of CAD metadata within the broader enterprise data flow.
In the 1980s and 90s, many companies transitioning to modern 3D CAD systems became overly enthusiastic about metadata, capturing various data types within their CAD models. This often stemmed from either a lack of downstream business systems or inadequate integrations with existing ones. Consequently, this led to technical debt due to the reckless and inadvertent (see chart below) use of metadata in a system (CAD) not originally designed for such extensive data management. Teams soon realized that metadata could quickly become outdated or "stale."
For instance, storing a part's cost in CAD file metadata is an ill-advised practice. Cost, being a dynamic attribute, is better suited for management within an ERP system. Similarly, assigning a project name to a single part file in metadata is prone to obsolescence. What happens when that model is utilized in another project down the line? How will the project attribute be updated across all associated files? Adhering to a sound protocol for metadata in CAD models is essential. Values within CAD models should ideally remain static (excluding the model's revision), as otherwise, CAD models risk accumulating technical debt in the form of inaccurate or outdated metadata.
Understanding the origins and initiation of technical debt is pivotal in preventing its accumulation. By assimilating the quadrants of the technical debt chart, teams can make informed decisions, provided there's meticulous planning regarding the utilization of metadata in engineering systems. Careful consideration of how and where metadata is applied ensures that technical debt is minimized, fostering more efficient and sustainable engineering practices.
Next installment: Examples of ETD - Part 2