Eco-efficiency indicator framework implemented in the metallurgical industry: part 1—a comprehensive view and benchmark

Rönnlund, Ida; Reuter, M.A.; Horn, Susanna; Aho, Jatta; Aho, Maija; Päällysaho, Minna; Ylimäki, Laura; Pursula, Tiina

doi:10.1007/s11367-016-1122-9

Cited by 31 publications

(18 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(3) Inform resource efficiency (iRE) and knowledge transfer [5,11] : The development of innovative applications (apps) and visualizing the results of complex simulation models in simple-to-understand visualizations is crucial to empower society to innovate informing RE. (4) Environmental impact [26,40,41] and RI [11] : M-IoT is a detailed process metallurgical first-principles approach, which enables the integration of methodologies such as LCA and simulation-based RI calculation [26] into CAE and CAD. The results provide the consumer with transparent information on products detailing the impacts of all stakeholders depicted in Figure 1.…”

Section: Quantifying the Re Of A Cementioning

confidence: 99%

“…6-M-IoT permits the optimization of both EE and RE, therefore providing the complete detail of iRE. Clockwise from top left: (i) the design wheel [12] for consumer products showing the effect of liberation classes (LCs) with reference to the Metal Wheel [46] (in the center), (ii) the Gaia Refiner [40,41] flower showing environmental impact relative to a baseline, and (iii) the accepted EE calculation [45] and the RI. [11] To recover the metals from such complexity requires complexly linked metallurgical infrastructure that can recover as many as possible metals, as shown by Figure 7.…”

Section: Element Efficiency Resource Efficiency Energy Efficiencymentioning

confidence: 99%

“…Figure 7 shows that if RI values are of any value, their underlying theory must consider and embrace the following: (i) material composition, i.e., both physical and chemical; (ii) the calorific values of the (intermediate) recycling streams based on their composition and mineralogy; (iii) material and mineral classes; (iv) particle size classes; (v) liberation and agglomeration classes of scrap ( Figure 7); [39][40][41] (vi) the economic value of intermediate streams based on metal values; [9,11] (vii) separation physics as well as metallurgical process thermodynamics; [9,11] (viii) losses and emissions and their mineralogy; [11] (ix) harmonization of processing infrastructure with changing product design; [4,9] and (x) distributed and dynamic properties of functional materials in present product designs simultaneously anticipating future designs. [47][48][49] Figure 9 provides a detailed flow sheet of an example of a recycling optimization model, [39] from which it is clear that the complete flow sheet of recycling is always considered.…”

Section: F Optimization and Quantification Of The Ce Systemmentioning

confidence: 99%

“…This UNEP report discusses in detail these limitations in addition to metallurgical processing technology and its sophisticated systems. [5,7,9] The digitalized process metallurgy's SIMP and m-IoT may provide the CEE tools [11,40,41,111] to guide a path toward a sustainable society. These tools will help advise policy of the opportunities and limits of a CE society on a theoretical and techno-economic basis.…”

Section: E Some Final Thoughts and Questionsmentioning

confidence: 99%

See 3 more Smart Citations

Digitalizing the Circular Economy

Reuter

2016

Metall Mater Trans B

101

View full text Add to dashboard Cite

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

show abstract

Section: Quantifying the Re Of A Cementioning

confidence: 99%

Section: Element Efficiency Resource Efficiency Energy Efficiencymentioning

confidence: 99%

Section: F Optimization and Quantification Of The Ce Systemmentioning

confidence: 99%

Section: E Some Final Thoughts and Questionsmentioning

confidence: 99%

See 2 more Smart Citations

Digitalizing the Circular Economy

Reuter

2016

Metall Mater Trans B

101

View full text Add to dashboard Cite

show abstract

“…A comprehensive sustainability indicator framework has recently been developed which combines numerous impacts into one simple result while comparing it to a benchmark (Rönnlund et al 2015). Water, energy and materials are thereby combined and evaluated at the same time.…”

Section: Introductionmentioning

confidence: 99%