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Digitalizing the Circular Economy Circular Economy Engineering Defined by the Metallurgical Internet of Things

MARKUS A. REUTER

Metallurgy is a key enabler of a circular economy (CE), its digitalization is the metallurgical Internet of Things (m-IoT). In short: Metallurgy is at the heart of a CE, as metals all have strong intrinsic recycling potentials. Process metallurgy, as a key enabler for a CE, will help much to deliver its goals. The first-principles models of process engineering help quantify the resource efficiency (RE) of the CE system, connecting all stakeholders via digitalization. This provides well-argued and first-principles environmental information to empower a tax paying consumer society, policy, legislators, and environmentalists. It provides the details of capital expenditure and operational expenditure estimates. Through this path, the opportunities and limits of a CE, recycling, and its technology can be estimated. The true boundaries of sustainability can be determined in addition to the techno-economic evaluation of RE. The integration of metallurgical reactor technology and systems digitally, not only on one site but linking different sites globally via hardware, is the basis for describing CE systems as dynamic feedback control loops, i.e., the m-IoT. It is the linkage of the global carrier metallurgical processing system infrastructure that maximizes the recovery of all minor and technology elements in its associated refining metallurgical infrastructure. This will be illustrated through the following: (1) System optimization models for multimetal metallurgical processing. These map large-scale m-IoT systems linked to computer-aided design tools of the original equipment manufacturers and then establish a recycling index through the quantification of RE. (2) Reactor optimization and industrial system solutions to realize the ‘‘CE (within a) Corporation—CEC,’’ realizing the CE of society. (3) Real-time measurement of ore and scrap properties in intelligent plant structures, linked to the modeling, simulation, and optimization of industrial extractive process metallurgical reactors and plants for both primary and secondary materials processing. (4) Big-data analysis and process control of industrial metallurgical systems, processes, and reactors by the application of, among others, artificial intelligence techniques and computer-aided engineering. (5) Minerals processing and process metallurgical theory, technology, simulation, and analytical MARKUS A. REUTER, Director, is with the Helmholtz-Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, Germany. Contact e-mail: [email protected] Manuscript submitted April 24, 2016. Markus A. Reuter has been Director with the Helmholtz Institute Freiberg for Resource Technology since September 2015. He earned an honorary doctorate (Dr. h.c.) from the University of Lie`ge (Belgium); D Eng. and PhD from Stellenbosch University (South Africa); and Dr. habil. from RWTH Aachen (Germany). Dr. Reuter was Chief Technologist with Ausmelt A