Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support mechanisms for generating a feasible assembly plan for a product based on data analytics. In aspects, information on components of a product is obtained from one or more product models (e.g., a three-dimensional (3D) computer aided design (CAD) model) that define the individual components of the product. The individual component information may be used to represent the assembly of the product as an assembly graph, in which each node of the assembly graph represents one of the components of the product to be assembled. The assembly graph is passed through a set of data analytics modules to generate the feasible assembly plan, or assembly sequence, as a series of sequential contact predictions, wherein each contact prediction identifies a component to be connected to one or more other components of the product.

A method, apparatus, system, and computer program product for managing a product. An engineering product structure for the product is identified. The engineering product structure comprises parts for the product. A manufacturing product and process structure is created using the engineering product structure, wherein the manufacturing product and process structure comprises the parts and manufacturing information for connecting the parts to each other to form the product.

A method, apparatus, system, and computer program product for managing a product. An engineering product structure for the product is identified. The engineering product structure comprises parts for the product. A manufacturing product and process structure is created using the engineering product structure, wherein the manufacturing product and process structure comprises the parts and manufacturing information for connecting the parts to each other to form the product.

A component manufacturing device called Auto-Fab (100) is disclosed. Each Auto-Fab system is a self-contained device including a housing (150), tools (120), robotics (110), sensors (113), and computing functionality (115) that is configured to manufacture a variety of components (160) using various materials available at a location of the Auto-Fab. The Auto-Fab, using the robotics and tools, may be programed to autonomously perform a variety of manufacturing techniques including, but not limited to, deformation, casting, machining, and welding The manufacturing processes used by the Auto-Fab for a particular component may be designed using an iterative feedback method (200; 300) where the manufacturing processes are continuously tweaked and tuned based on a comparison of a manufactured component with predicted attributes.