Improving Business Outcomes Through Advanced am Data Management

This presentation explores the challenges and opportunities in seamlessly integrating digital technologies into the additive manufacturing (AM) workflow, with a focus on improving engineering processes and optimizing business outcomes. While transitioning from traditional manufacturing to digital platforms holds great promise, establishing a cohesive digital 'thread' and adopting a common data model within the AM process are complex tasks often underestimated.

Through a detailed case study, this talk examines the critical considerations, potential pitfalls, and significant benefits of implementing a comprehensive software strategy to enhance AM operations. We will delve into the integration of the Renishaw AM500 and EOS M290 systems, both utilizing Direct Metal Laser Sintering (DMLS) technology, and demonstrate how a common data model can streamline data flow, enhance interoperability, and facilitate more informed decision-making. This approach not only improves process quality and system health but also boosts operational efficiency and consistency.

In addition to technical advancements, this presentation highlights how effective AM data management supports business goals by improving productivity, enabling smoother transitions during workforce turnover, and preserving institutional knowledge. A common data model ensures that critical data and insights remain accessible, reducing downtime and maintaining operational continuity when personnel changes occur.

Attendees will gain practical insights and best practices for developing a robust software strategy that aligns with both technical and business objectives. This includes enhancing cybersecurity, optimizing resource allocation, and ensuring seamless integration of advanced digital tools, ultimately maximizing the potential of additive manufacturing in a dynamic business environment.