VCM - Volumetrically Controlled Manufacturing Technologies
Volumetrically Controlled Manufacturing (VCM), developed by Hawthorne & York International, Ltd. (HYI), is a new innovative design and manufacturing process for advanced composite materials. VCM is based on an inverse Finite Element Analysis (FEA) method, is scalable (i.e. macro, micro, and nano levels), and is derivable (i.e. mechanical, thermal, electro-magnetic, acoustic, and optic applications). VCM helps to reduce failure in laminated composites due to delamination and structural fatigue.
The concept of VCM evolved as a result of previous research conducted by Dr. James St. Ville, President of HYI, and at that time a practicing Orthopedic Surgeon, that modeled a 30% carbon fiber - polysulfone composite laminate hip under dynamic in vivo loading conditions.
VCM is an integrated design and manufacturing approach that optimizes parts by varying the mechanical properties of its material. For any given geometry and set of design goals, VCM will create a finite element based model with proper loading conditions, boundary conditions, and design constraints. The VCM integrated optimization FEA program iteratively analyzes the model and adjusts material properties until all design parameters are satisfied. The results are translated into inputs for CNC machinery and robotics, which fabricates parts with near optimum material properties throughout its volume.
In order to provide an efficient analysis tool to determine the optimum material properties for an engineered product such as a hip stem, a different approach from traditional analysis had to be made. The VCM process encompasses this new approach. Instead of determining the displacements, stresses and strains in a product using traditional analysis methods, through real world testing, displacements are recorded and entered into the analysis. The material properties are now the unknowns and are solved for in an iterative analysis process. The analysis continues until specified elements display displacements all within a specified tolerance. In this way, an iteration process continues until convergence, thereby, optimizing the entire model for its particular environment and loading condition.
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