Many research issues to enable intelligent manufacturing need to be resolved, such as:
Digital twins: With the latest sensing and embedded computing techniques, data about products through their lifecycles becomes increasely available to stakeholders. For instance, how products are fabricated, deployed, and used can provide valuable input to product designers for informed decision making. Manufacturing equipment's health status can guide suppliers to provide just-in-time shipment of part replacement for preventive maintenance. Product and process design can be more effective with more accurate process-structure-property relationships established from these data.
Data compression: The amount of data collected by sensors is exponentionally growing, which makes communication and data processing the bottleneck. Compressive or compressed sensing is a new approach to obtain information from reduced data sets. Domain specific compression can further improve compression ratios.
Security risk and intellectual property protection: Collaborative design requires design data to
be shared by different parties. Cyper-physical-social systems rely on information sharing to perform their functions. Data security is essential to build trustworthy systems.