Digitalizing the Circular Economy

有可能 循环经济 过程(计算) 钥匙(锁) 制造工程 资源效率 持续性 物流分析 工艺工程 精炼(冶金) 资源(消歧) 物流 计算机科学 工程类 废物管理 材料科学 冶金 操作系统 心理治疗师 心理学 生物 计算机安全 计算机网络 生态学
作者
Markus A. Reuter
出处
期刊:Metallurgical and Materials Transactions B-process Metallurgy and Materials Processing Science [Springer Nature]
卷期号:47 (6): 3194-3220 被引量:103
标识
DOI:10.1007/s11663-016-0735-5
摘要

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 tools, which are all key enablers of the CE. (6) Visualizing the results of all the tools used for estimating the RE of the CE system in a form that the consumer and general public can understand. (7) The smart integration of tools and methods that quantify RE and deliver sustainable solutions, named in this article as circular economy engineering. In view of space limitations, this message will be colored in by various publications also with students and colleagues, referring to (often commercial) software that acts as a conduit to capture and formalize the research of the large body of work in the literature by distinguished metallurgical engineers and researchers and realized in innovative industrial solutions. The author stands humbly on the shoulders of these developments and their distinguished developers. This award lecture article implicitly also refers to work done while working for Ausmelt (Australia), Outotec (Finland and Australia), Mintek (South Africa), and Anglo American Corporation (South Africa), honoring the many colleagues the author has worked with over the years.

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