Coupling Digital Engineering and AM to Produce Superior Products More Efficiently

In today’s environment of increasing competitive pressure, lingering supply chain issues and rapidly changing technology it is necessary to continually evolve your approach to stay ahead. Recent advances in digital engineering tools and techniques combined with AM’s geometric flexibility offer the opportunity to produce superior designs more efficiently than we have done in the past. Many of the CAD software packages today have the capability to apply the loads and constraints of the application, select your preferred manufacturing method and ask the tool to provide an optimized solution. Different manufacturing processes can be selected to contrast and compare the proposed solution for each, enabling the design engineer to make an informed decision. Product performance, cost and supply chain implications can be considered up front in the design process and the software can factor into the design best practices associated with the selected manufacturing process.
In addition to CAD tool capability, the advent of machine learning and AI techniques enable the creation of automated design cycle models that can optimize a solution and automate common engineering tasks of creating models, prints and specifications. These tools can be taught the manufacturing constraints for a given process like laser powder bed fusion AM. An organization can realize 20-35% engineering efficiency improvements on product lines that lend themselves to this type of an approach. The models can vary from simple BOTs to do repetitive design work to more advanced machine learning models and ultimately to full AI rapid optimization when sufficient data exists to leverage the capability.
During this presentation, I will take the audience through the vision Eaton has for leveraging both digital engineering and AM capabilities to create superior products for our customers much more efficiently than we have done in the past. It will include Eaton case studies.