Berkeley, CA – System Insights (SI) announced that the National Institute of Standards and Technology (NIST) has selected the VIMANA platform as the base infrastructure for a collaborative project to build a Smart Manufacturing reference architecture to help industry, academia, and standards organizations conceptualize and develop value-added solutions that can address the evolving challenges of integrating manufacturing feedback into design.
Under this project, System Insights will collaborate with NIST researchers and engineers to develop a VIMANA-based architecture to enable analysis across the Digital Thread. The Digital Thread refers to the flow of information between the phases that connect the definition of an idea to the development of a product, integrating phases such as product design, manufacturing planning, execution, and metrology.
Dr. Athulan Vijayaraghavan, Founder and CTO of System Insights, stated, “Thus far, attempts to integrate manufacturing feedback in design have been incremental and marginal, since they always presume that information flows from design to manufacturing, and have only attempted to augment this flow. However, for true integration between design and manufacturing, the flow of information from the manufacturing phase (which is derived from analytics performed on data from the manufacturing shop floor) back to design has to be fundamentally architected.”
SI will work with NIST to address the previous issues of lack of a domain model, connectivity, instrumentation, and common protocols by using VIMANA and the MTConnect standard to provide a high-availability transport and domain model for normalization of the various pieces of data being collected from various shop floor equipment, including machine tools, metrology equipment, transfer equipment, etc.
SI will also work with NIST to augment the existing data collection capabilities of the shop floor equipment using sensors to enrich the streams of data and provide aggregated event streams. SI will also work with NIST to architect, develop, and provide technology to persist data in a high-speed data repository where it can be analyzed using tools for correlation analysis and patterns identification, indicative of adherence to a prescribed process as well as enabling prognostics and health management of manufacturing devices.
The resulting system will lay the groundwork for future smart machine and cyber-physical programs being developed at academia, industry, and standard-organizations around the United States. The data architecture from this project will serve as the fundamental basis to meet the needs of advanced smart manufacturing initiatives.