Issue link: https://resources.randsim.com/i/1492523
2 Using Materials Data for Faster, Cheaper, More Repeatable Additive Manufacturing // / 1) Traceability and capture of data across AM value chain What is traceability? Let us say you are doing an AM project. You just built a part using a laser powder bed AM machine and you tested some test coupons that were built with the part as well. How do you answer the following questions? 1. What powder did you use for building this part, what are the powder characteristics (e.g. chemistry, particle size distribution, etc.)? 2. What process parameters and machine settings did you assign for the part? 3. What was in the log files from the machine after you built it (e.g. sensor readings)? 4. What heat treatments did you put the part through? 5. What were the mechanical testing results? 6. Could you understand and relate the mechanical testing results to the right powder, process parameter and heat treatment information? Traceability answers these questions. It might look easy when you have built just one part, but how would you do it if you worked with multiple machines, various powders and different kinds mechanical testing like tensile, fatigue and fracture toughness? To address traceability, you must first capture all the data in a format that's consistent across different machines, builds and materials. How can you address the challenge of capture and traceability of AM Data? You must have a system that provides an AM schema, which is part of Ansys Granta MI's solution for AM. What is a schema? The schema identifies a comprehensive set of properties, processes and related data that you might require to capture the full details and history of AM processes and testing programs. It structures this data for efficient management and use and captures key relationships between data. Figure 2 below shows a typical schema for AM. What is the business benefit? For a typical AM program, having all the data, from materials, machines to testing data, in a single platform, such as Ansys' Granta MI software, with a configurable schema can yield an overall cost saving of 25% compared with the cost of running the AM program with no data capture. Figure 3 outlines the variety of types of data that can be captured and harnessed. This has proven to yield more than 800 hours of time saved for a team of 10 engineers, eliminating the need to search for data, be it in folders, Sharepoints or physical documents – all by capturing the knowledge in a single platform. Figure 2: Granta MI's AM schema.