AI-Driven Tool Streamlines Technical Data for ASEAN Factories

Reducing Documentation Overhead with AI in Additive Manufacturing \\[](https://example.com)\\ In the world of additive manufacturing (AM), one of the most significant barriers to efficient production is the extensive documentation required. Boeing, a leading aerospace company, faced a substantial backlog of technical data packages (TDPs) for casting and 3D printed parts, which was costing its engineering teams dearly. Enter Authentise, a Philadelphia-based digital workflow management company, which has developed an AI-driven tool to streamline this process. This innovation not only promises to save Boeing approximately $8 million in engineering costs in its first year but also holds potential benefits for factories across Southeast Asia. \\[](https://example.com)\\ ### The Documentation Bottleneck in AM \\[The paperwork problem behind AM adoption is a universal challenge. Bringing a part into production involves translating unstructured engineering intent, such as CAD files, performance specifications, and design rationale, into actionable technical documents. This process can take up to 150 hours per part, even for relatively simple assemblies. For factories in Thailand, Vietnam, Indonesia, and Malaysia, where the adoption of AM is on the rise, this bottleneck can significantly slow down production and increase costs. \\[](https://example.com)\\ ### How Authentise’s AI Tool Works \\[Authentise’s solution, Threads, is an engineering collaboration platform that integrates messaging, project management, document repositories, and 3D model annotation. The platform uses a large language model (LLM) to analyze engineers' inputs and suggest how to log them, flagging decisions and action items. This structured approach ensures that all discussions are consistently recorded, making it easier to generate comprehensive TDPs. \\[ThreadsDoc, a feature within Threads, automates the generation of TDPs by pulling together the latest versions of specifications and relevant documents. This tool, tested with Boeing, is projected to save millions in engineering costs by handling the time-consuming but low-value tasks of document assembly. \\[](https://example.com)\\ ### Implications for ASEAN Factories \\[For factories in ASEAN, the adoption of such AI-driven tools can be transformative. In Thailand, where the automotive and electronics industries are booming, reducing documentation overhead can accelerate the production of complex parts. In Vietnam, where the mold and die industry is growing, this tool can help manage the intricate documentation required for precision components. In Indonesia, where the food packaging and medical sectors are expanding, streamlined documentation can ensure compliance and quality. In Malaysia, where semiconductor manufacturing is a key sector, the tool can support the rigorous documentation needed for high-precision components. \\[](https://example.com)\\ ### Conclusion \\[The integration of AI in AM workflows is a game-changer for factories in ASEAN. By automating the tedious and time-consuming tasks of document assembly, these tools allow engineers to focus on higher-value activities like review and verification. As the AM industry continues to grow, adopting such technologies will be crucial for staying competitive and ensuring efficient production. Factory buyers in ASEAN should consider investing in AI-driven solutions to streamline their operations and reduce costs. \\[](https://example.com)