Abstract: This invention presents an innovative framework for the application of machine learning for identification of alloys or composites with desired properties of interest. For each output property of interest, we identify the corresponding driving (input) factors. These input factors may include the material composition, heat treatment, process, microstructure, temperature, strain rate, environment or testing mode. Our framework assumes selection of optimization technique suitable for the application at hand and data available, starting with simple linear, or quadratic, regression analysis. We present a physics-based model for predicting the ultimate tensile strength, a model that accounts for physical dependencies, and factors in the underlying physics as a priori information.

Abstract: This invention presents a framework for applying artificial intelligence to aid with product design, mission or retail planning. The invention outlines a novel approach for applying predictive analytics to the training of a system model for product design, assimilates the definition of meta-data for design containers to that of labels for books in a library, and represents customers, requirements, components and assemblies in the form of database objects with relational dependence. Design information can be harvested, for the purpose of improving decision fidelity for new designs, by providing such database representation of the design content. Further, a retrieval model, that operates on the archived design containers, and yields results that are likely to satisfy user queries, is presented. This model, which is based on latent semantic analysis, predicts the degree of relevance between accessible design information and a query, and presents the most relevant previous design information to the user.

Abstract: This invention presents Ecosystems addressing limited capabilities for interactive team design, amidst thrust for improved productivity, enhanced creativity and higher quality. The Ecosystem for Team Design and Collaboration presents apparatus for taking snapshots of whiteboards with sketches from planning, design or brainstorming meetings, using image sensor embedded in a mobile client, for offering a vector representation of the content and hence expediting the preparation of ‘presentable entities’ (eliminating the need to redraw). The Ecosystem for Learning and Team Design outlines a flexible design methodology for automatically assessing the quality of design activities relative to a given design process. It is the only learning tool for computer aided design (CAD) capable of assessing all the five design stages. Its assessment engine, the e-design process, is modular and can be integrated into electronic lab notebooks.