Open AccessLaser engineered net shaping (LENS{trademark}) process: Optimization of surface finish and microstructural properties
Author(s) -
John E. Smugeresky,
David M Keicher,
J.A. Romero,
Michelle L. Griffith,
L.D. Harwell
Publication year - 1997
Language(s) - English
Resource type - Reports
DOI - 10.2172/554828
Subject(s) - fabrication , materials science , process (computing) , rapid prototyping , component (thermodynamics) , process window , investment casting , trademark , engineering drawing , mechanical engineering , lens (geology) , macro , computer science , molding (decorative) , nanotechnology , engineering , composite material , mold , medicine , alternative medicine , physics , pathology , petroleum engineering , thermodynamics , programming language , operating system
Rapid prototyping (RP) has revolutionized the approach to fabricating geometrically complex hardware from a CAD solid model. The various RP techniques allow component designers to directly fabricate conceptual models in plastics and polymer coated metals; however, each of the techniques requires additional processes, e.g. investment casting, to allow the fabrication of functional metallic hardware. This limitation has provided the impetus for further development of solid freeform fabrication technologies which enable fabrication of functional metallic hardware directly from the CAD solid model. The Laser Engineered Net Shaping (LENS{trademark}) process holds promise in satisfying this need. This newly emerging technology possesses the capability to fabricate fully dense components with good dimensional accuracy and with unique materials properties. Relatively complex geometrical shapes have been fabricated using this technology. In continuing to develop the LENS{trademark} process, further advancements are required. The functional dependence of the component surface finish and microstructural characteristics on process parameters including power size and size distribution are being evaluated. A set of statistically designed experiments is being used to sort through the various process parameters and identify significant process variables for improving surface finish and achieving optimum material microstructural properties