Additive manufacturing (AM) offers a potential game-changer for low-cost, fast turn-around fabrication of Navy components. Combined with methods such as reverse engineering metrology, AM can produce low batch on-demand quantities, which is ideal in the case of repair/replace Navy components that were damaged in the field or inserting a new design for lightweighting or performance enhancements. Wide-spread implementation of AM structures has been limited, however, mainly due to its lower maturity compared to conventional materials (metals, composites, plastics). There exists no single software application that implements the Navys qualification procedure. However, each exists separately, making it difficult to connect them together to get a clear picture of the risk of using the given AM process versus the original method. Consequently, it is very difficult to qualify any AM parts for naval use and limits the Navys ability to take advantage of this growing field of manufacturing. This proposal will build a tool that will walk users through a series of simulations that compare an AM parts performance to its legacy variant, and determine how much risk is associated with AM replacement. The proposed tool will consist of three major modules. The first module, part performance M&S, will consist of a battery of tests geared towards the Navys qualification process, along with a database of materials, typically in base/AM pairs. The second module will perform optimization to improve the performance of the AM part given its design environment. The third module, risk assessment, will bring together multiple parallel runs of the part performance M&S module and information from a database about a given AM process and material. The risk assessment system will consider the AM part variant for a series of manufacturability checks, compare the simulation and database data against a set of risk metrics, and reduce these datapoints to a single number by weighting them and summing them together to represent the overall risk associated with switching to the AM part.
Benefit: Anticipated benefits include lower total ownership costs and faster turn around for repairs or implementation of new designs via use of additive manufacturing. Increased reliability is also anticipated by performing a full risk assessment for replacing conventional parts with additive manufactured parts. The initial customer for this tool will be the Navy, for use in qualifying AM parts to reduce risk of adoption across Navy SysComs including NAVSEA, NAVAIR, NAVSUP, and the Marine Corps. Other DoD agencies would also benefit from this technology, due to increasing interest in utilizing AM parts in air and ground platforms as well as DLAs development of the Joint Additive Manufacturing Model Exchange (JAMMEX), which will be a database source for DoD AM stakeholders Outside of the defense market, we anticipate interest from a number of commercial industries where AM is increasingly used to support new and aging supply chains. Target industries include aerospace, automotive, oil & gas, utilities, and shipping as shown in Table 4. Hence, qualification of AM parts is of significant interest to these industries and will help advance the adoption of AM. Key stakeholders from these industries will be contacted to gather voice-of-customer (VOC) input so that barriers to market adoption will be lessened. Entry into these markets will likely be accomplished via licensing agreements with established M&S software providers such as Dassault Systemes, developers of Abaqus.
Keywords: Digital Engineering, Digital Engineering, Optimization, t Additive Manufacturing, Risk Managemen
