Engineers spend months working on hardware designs, focusing on even the tiniest of details. Yet, the product built can differ considerably from what was designed. The discrepancy between the two stems from a limitation in technology.
An engineer’s design environment is fundamentally different from a manufacturer’s physical landscape. CAD and ECAD designs cannot be directly translated into the physical realm due to a number of restrictions. These constraints include manufacturing tools, engineering tools, and communication gaps between the two.
While discrepancies between designs and builds have always been a part of hardware development, we dream of a world where they don’t exist (or, at the very least, are reduced)! High-level decisions are made primarily during the design phase, meaning that a significant departure from the design during the build phase can introduce costly problems that were not accounted for. By minimizing the differences between designs and builds, teams can be better informed and prepared about the end product.
As with most problems in the industry, there isn’t a quick or easy solution. Closing the gap requires engineers to study past iterations and drive changes in new designs based on previous successes and challenges.
Data from past builds are invaluable—they’re the realest information engineers have about how their designs change throughout the manufacturing process. Of course, simulations provide engineers with a basic idea of how different variables affect designs, but they don’t capture everything. Only the process of actually building a design can do that, which is why teams should learn from real-life data as much as possible.
This, however, is easier said than done. Information silos between engineers and their collaborators complicate the process. In particular, engineers and manufacturers use different tools that don’t interact with each other. Build-related data sit within manufacturer-specific systems, like ERP/MES software or factory servers, that aren’t easily accessible to design engineers.
An engineer would have to source empirical data from the manufacturer by having conversations and asking questions. This introduces many opportunities for mistakes; engineers may forget to ask important questions or manufacturers may provide incorrect data. Inefficient information retrieval hinders the learning process and prevents engineers from creating designs that can be built accurately and easily.
As a one-stop shop for all design-related information, Bild integrates with manufacturing software and enables engineers to easily access build-related information. On the centralized platform, engineers can conduct design reviews and analyze past builds. This creates a closed feedback environment where teams consistently improve their designs—bridging the gap between designs and builds!
It’s important for engineers to understand their manufacturers’ process capabilities, which directly impact how (or even if) a manufacturer builds a design. For example, the perfect manufacturer with years of experience would be able to replicate a design exactly. They would have every aspect of the process planned: the materials to use, the temperatures to reach, the length of time to dry, and so on. On the other hand, less experienced factories would need the design to be changed to better fit their abilities. This is where design for manufacturing (DFM), the practice of designing products in a way that is easy to manufacture, comes into play.
Engineers change their designs based on their manufacturers’ feedback. Traditionally, engineers took a manufacturer’s process capabilities at face value. They didn’t have access to the manufacturer’s empirical data. This meant that engineers often moved their designs away from ideal specifications based on inaccurate factory-provided estimates. Many factories would inflate the tolerances they needed in an attempt to gain more flexibility throughout the process, moving products farther and farther away from their as-designed models.
However, new tools like Bild bring transparency to the previously hidden information. By leveraging this new information on manufacturer process capabilities, engineers can tailor their designs to fit both design and manufacturing standards!