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Yan Lu, Paul Witherell, Felipe F. Lopez, Ibrahim Assouroko


Software tools, knowledge of materials and process models, and data provide three pillars on which Additive Manufacturing (AM) lifecycles and value chains can be supported. These pillars leverage efforts dedicated to the development of AM databases, high-fidelity models, and design and planning support tools. However, as of today, it remains a challenge to integrate distributed AM data and heterogeneous predictive models in software tools to drive a more collaborative AM development environment. In our paper, we describe the development of an analytical framework for integrated and collaborative AM development. Information correlating material, product design, process planning and manufacturing operations are captured and managed in the analytical framework. A layered structure is adopted to support the composability of data, models and knowledge bases. The key technologies to enable composability are discussed along with a suite of tools that assist designers in the management of data, model and knowledge components. A proof-of-concept case study demonstrates the potential of the AM analytical framework.
Conference Dates
August 21-24, 2016
Conference Location
Charlotte, NC, US
Conference Title
36th Computers and Information in Engineering Conference (CIE)


additive manufacturing, collaborative development, modeling and simulation


Lu, Y. , Witherell, P. , Lopez, F. and Assouroko, I. (2016), DIGITAL SOLUTIONS FOR INTEGRATED AND COLLABORATIVE ADDITIVE MANUFACTURING, 36th Computers and Information in Engineering Conference (CIE), Charlotte, NC, US, [online], (Accessed May 26, 2024)


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Created August 23, 2016, Updated April 18, 2022