Evaluation of Generative Models for Predicting Microstructure Geometries in Laser Powder Bed Fusion Additive Manufacturing

In-situ process monitoring for metals additive manufacturing is paramount to the successful build of an object for application in extreme or high stress environments. In selective laser melting additive manufacturing, the process by which a laser melts metal powder during the build will dictate the internal microstructure of that object once the metal cools and solidifies. The difficulty lies in that obtaining enough variety of data to quantify the internal microstructures for the evaluation of its physical properties is problematic, as the laser passes at high speeds over powder grains at a micrometer scale. Imaging the process in-situ is complex and cost-prohibitive. However, generative modes can provide new artificially generated data. Generative adversarial networks synthesize new computationally derived data through a process that learns the underlying features corresponding to the different laser process parameters in a generator network, then improves upon those artificial renderings by evaluating through the discriminator network. While this technique was effective at delivering high-quality images, modifications to the network through conditions showed improved capabilities at creating these new images. Using multiple evaluation metrics, it has been shown that generative models can be used to create new data for various laser process parameter combinations, thereby allowing a more comprehensive evaluation of ideal laser conditions for any particular build

Software development: A paradigm for the future

A new paradigm for software development that treats software development as an experimental activity is presented. It provides built-in mechanisms for learning how to develop software better and reusing previous experience in the forms of knowledge, processes, and products. It uses models and measures to aid in the tasks of characterization, evaluation and motivation. An organization scheme is proposed for separating the project-specific focus from the organization's learning and reuse focuses of software development. The implications of this approach for corporations, research and education are discussed and some research activities currently underway at the University of Maryland that support this approach are presented

A Framework proposal for monitoring and evaluating training in ERP implementation project

During the last years some researchers have studied the topic of critical success factors in ERP implementations, out of which 'training' is cited as one of the most ones. Up to this moment, there is not enough research on the management and operationalization of critical success factors within ERP implementation projects.Postprint (published version