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Smart Manufacturing: Enterprise Real-Time, Networked Data, Information & Action
Professor Jim Davis of UCLA will be speaking to the CSR local section of AIChE about Smart Manufacturing. The meeting will be held Monday, March 10 at 6:00 pm at Carrabba's Italian Grill in Augusta. Dinner cost will be $25 for professionals and $5 for students. Please notify James Laurinat at James.Laurinat@srnl.doe.gov if you plan to attend.
Smart Manufacturing is the sophisticated practice of generating and orchestrating the use of data-driven manufacturing intelligence using multiple real-time SM Systems broadly deployed throughout all operating layers (i.e. control, automation, maintenance/reliability, trade-off decisions, operations, logistics, risk, business management, etc.) across the entire factory and supply chain. SM integrates network-based data and information that comprises the real-time understanding, reasoning, design, planning and management of all aspects of the manufacturing and supply chain enterprise, i.e. manufacturing intelligence. SM is achieved through extensive, comprehensive and orchestrated use of advanced sensor-based data analytics, modeling and simulation, and integrated performance metrics constructed for real-time action. Manufacturing intelligence takes the form of (1) a much deeper behavioral understanding of the manufacturing process through modeling and analysis, (2) new capacity to observe and take action on integrated patterns of operation through networked data, information, analytics, and metrics, (3) new insights for manufacturing innovation through a broader base of innovators, and (4) a significantly greater ability to reuse and repurpose integrated practice through shared infrastructure. Shared infrastructure comprises an open-architecture, and precompetitive software development and management environment that integrate the components required to assemble customized systems on a common, standards-based deployment infrastructure. At its technical core, the infrastructure supports systems that can define what data is collected and shared, how computationally-generated results can interface with operating equipment and automation infrastructures, and how results are displayed in an actionable form to operators, engineers, and managers. Implementation is underway as well as the development of next phase R & D requirements. The effort is guided by the Smart Manufacturing Leadership Coalition, which is comprised of industry, university, provider, consortia and agency members.