A comprehensive intelligent manufacturing system (CIMS) for Hybrid Manufacturing (HM) process simulation

The development of a Comprehensive Intelligent Manufacturing System (CIMS) for the simulation of Hybrid Manufacturing (HM) processes to predict residual stress formation and part distortion is proposed. HM is a manufacturing process that combines Additive Manufacturing (AM) and subtractive manufacturing (SM) sequentially to build parts of complex geometries. Although this emerging technology is quite promising, there are several challenges in combining the additive and subtractive steps due to uncertainties associated with residual stress formation and part distortion. The residual stress formation and part distortion are well-known issues for AM. They not only deteriorate the part quality but also introduce many uncertainties that are further avalanched when combined with subtractive manufacturing. As a result, determining optimal process parameters that allow mitigating residual stress formation and part distortion is very challenging. A solution to mitigate these challenges is the development of advanced process modeling capabilities that can simulate HM processes and accurately predict residual stress formation and part distortion. The proposed innovation, CIMS, has the potential to address this critical need. The CIMS will primarily consists of three major components, a central control unit (CCU), an AM unit (AMU) and an SMU unit (SMU). The AMU and SMU are units that simulate material addition, i.e. an AM step and selective material removal, i.e. an SM step, respectively. The main function of CCU is to determine the optimal process conditions and parameters for the AM and SM steps using physics based computational models. The proposing team members have developed unique capabilities in the form of computational tools, simulation frameworks, and software in the field of AM process simulation in the past. These capabilities include advanced physics-informed slicing technology and high-fidelity finite element analysis capabilities. In the proposed project, the team will leverage these capabilities for the building of CIMS. Accordingly, the objectives of the proposed Phase I research are to advance the basic capabilities further to meet the challenging needs of HM process, integrate them to build a basic framework of CIMS, and then demonstrate the framework by simulating the repair of a Ti64 bellcrank linkage. The objectives of Phase I option are to invent innovative methods to improve computational efficiency and robustness of the CIMS substantially.