Smart manufacturing and energy systems

• Published in: Computers & chemical engineering Vol. 114; no. C; pp. 130 - 144
• Main Authors: Edgar, Thomas F., Pistikopoulos, Efstratios N.
• Format: Journal Article
• Language: English
• Published: United Kingdom Elsevier Ltd 09-06-2018; Elsevier
• Subjects: Advanced control; Energy efficiency; Optimization; Process modeling; Smart manufacturing; Smart sensors; Advanced control; Energy efficiency; Process modeling; Smart sensors; Optimization; Smart manufacturing
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2017.10.027

•Advances in smart manufacturing are covered in the context of PSE tool application.•Systems interface with smart manufacturing apps through a vendor agnostic platform.•Smart manufacturing apps employ high fidelity models, cybersecurity, and optimization algorithms.•Smart manufacturing can increase energy productivity and maintain product quality.•Goals are described for newly established Department of Energy manufacturing institute.
While many U.S. manufacturing operations utilize optimization for individual unit processes, smart manufacturing (SM) systems that integrate manufacturing intelligence in real time across an entire production operation are not pervasive in industry. A vendor-agnostic SM platform is under development that integrates information technology, models, and simulations driven by real-time plant data and performance metrics. By utilizing existing process control and automation systems, manufacturing organizations can manage systems at a much lower cost, optimizing process knowledge and improving energy productivity. Three case studies are presented: steam methane reforming to make hydrogen, optimization of a heat treatment furnace for metals processing, and a fuel cell system, all of which utilize high fidelity models as a starting point for optimization and control. The Smart Manufacturing Leadership Coalition has led the national effort in SM, and the recently established National Manufacturing Innovation Institute funded by DOE, private industry, and state governments will be described.