The Digital Thread for Engineering Requirements

by | May 19, 2023 | Digital Transformation, Insights, Model-Based Enterprise

“Digital thread” is probably a term you’ve heard many times, but it’s not always clear what it means, and often has different nuanced definitions depending on the industry. In this quick primer, we’ll define the digital thread and then focus on one way to make your digital thread more capable and comprehensive — by enabling the requirements thread.

 

In general, a digital thread is a record of all the digital data that is used to engineer, manufacture, and deliver a product or service. “In the digital world, the complexity of the physical world can be distilled down to the pertinent information needed to make decisions.” This might include information about parts, materials, customer specifications, regulations, testing methods, and may also incorporate real-time data from the product such as performance metrics, user satisfaction, error rates, and more. Taken together across the lifecycle of a product, the knowledge gleaned from one activity can be shared upstream and downstream to inform others’ decision-making.

However, there is an important set of information about products and services that is not yet being captured efficiently in the digital thread: the requirements imposed by customer specs, industry standards, or regulations. If specifications are the building blocks of design and manufacturing, then requirements are the building blocks of specifications.

  1. Finding requirements within the specifications requires a manual effort by subject matter experts. It’s a tedious manual process that can take 30 hours for some documents and is clearly not scalable.
     
  2. Extracting the requirements and sharing them with designers, builders, manufacturers, and compliance engineers is typically done via copy/paste and saving them as new PDF files – for example, a set of hole drilling instructions. The PDF files are then shared with users downstream and incorporated into PLM and other enterprise applications as simple file attachments, not so much integrated into the digital thread as hard-linked to it without the same level of usability and trackability.
     
  3. Requirements in PDF format cannot be reasoned upon for decision-making or to find patterns or potential bottlenecks in the product lifecycle. For example, it would be very difficult for a human to wade through hundreds or thousands of documents to determine if there were restricted materials in the project, or if the project called for castings or forgings (which require extra long lead times and special treatment in procurement).
     
  4. Some software applications can do the job of finding requirements by primitively searching for “should”, “shall”, and “may” statements. But what if you need to find a more granular set of steps to execute a very precise task.

    For example, imagine that you need to find out: “What are the requirements for hole drilling and reaming?” or “What is an acceptable alloy replacement and how do I qualify it?” or “What are the tensile strength requirements for the cable and how do I test it?”. These steps are often hidden in multiple layers of documents – where one document references another which references another and another. That process is even more tedious and difficult because it requires subject matter expertise and zen-like concentration to follow the requirements thread through multiple layers of documents.

As you can see from the illustration below, starting with just one spec or drawing can expand to dozens of documents containing the requirements you need to do the job. Answering the question “What are the requirements for hole drilling and reaming?” can take hours of work and is fraught with potential human error.

 

To solve these challenges, SWISS uses AI and semantic modeling to transform unstructured text and data from engineering documents and drawings into machine-readable digital model data. Once that transformation is complete, the resulting semantically structured data enables a machine to follow the breadcrumbs of meaning and context and pick out the precise requirements that you need for a specific task – in seconds rather than days or weeks. These requirements can then be delivered to users exactly where they need it (e.g. in PLM, in Office365, or other enterprise applications) through the SWISS API.

We call this the “Digital Thread for Engineering Requirements”. Imagine simply asking a question like one above and getting an answer that pinpoints the information you need and gets you to the next step in your engineering or testing workflow.

The promise of SWISS and the digital thread for engineering requirements is to parse all of these requirements in seconds (rather than hours or days) and classify them according to their part, material, and process.

And in line with digital thread concepts, when changes occur to the requirements at the source (for example, a change made by a customer or a compliance engineer), alerts can be sent downstream instantly to notify relevant users.

The benefits of the “digital thread for engineering requirements” are:

  • Improved quality and first-time yield rates
  • Reduced rework, scrap, failures in the field and warranty costs
  • Faster product development and faster time-to-market