Scenario Analyses for By‐Products Reuse in Integrated Steelmaking Plants by Combining Process Modeling, Simulation, and Optimization Techniques

Algermissen

et al. 2020

Metals

Self Cite

162

Over the last few decades, the European steel industry has focused its efforts on the improvement of by-product recovery and quality, based not only on existing technologies, but also on the development of innovative sustainable solutions. These activities have led the steel industry to save natural resources and to reduce its environmental impact, resulting in being closer to its “zero-waste” goal. In addition, the concept of Circular Economy has been recently strongly emphasised at a European level. The opportunity is perceived of improving the environmental sustainability of the steel production by saving primary raw materials and costs related to by-products and waste landfilling. The aim of this review paper was to analyse the most recent results on the reuse and recycling of by-products of the steelmaking cycles as well as on the exploitation of by-products from other activities outside the steel production cycle, such as alternative carbon sources (e.g., biomasses and plastics). The most relevant results are identified and a global vision of the state-of-the-art is extracted, in order to provide a comprehensive overview of the main outcomes achieved by the European steel industry and of the ongoing or potential synergies with other industrial sectors.

Section: Introductionmentioning

confidence: 99%

Reuse and Recycling of By-Products in the Steel Sector: Recent Achievements Paving the Way to Circular Economy and Industrial Symbiosis in Europe

Branca

Algermissen

et al. 2020

Metals

Self Cite

162

“…On the other hand, advanced process modelling, control and optimization tools can allow adapting both single processes and the whole production chain, management for residues valorisation and waste and costs minimization while saving and improving steel products quality [68]. Modelling, simulation and optimization approaches can be used to determine the optimal route for by-products reuse and to find information on treatments by supporting selection and validation of potential solutions to overcome technical, economical and environmental issues affecting the by-products recycling rate [69]. In addition, the combination of by-products and waste management simulations and optimization can be used by plant managers and operators for improving by-products management, such as identifying the most suitable activities for potential internal or external recovery and for their reuse.…”

Section: Modelling/simulation For By-productsmentioning

confidence: 99%

Future Research and Developments on Reuse and Recycling of Steelmaking By-Products

Branca

Pietruck

et al. 2023

Metals

Self Cite

In the steel sector, sustainable management of by-products is a key challenge to preserve natural resources and achieve the zero waste goal. In this paper, the main trends of future research and development on reuse and recycling of by-products of the steel industry are presented in the form of a roadmap, which is the outcome of a dissemination project funded by the European Union based on the analysis of the most relevant and recent European projects concerning reuse and recycling of by-products from the steel production cycle. In particular, the developed roadmap highlights the most important topics of future research activities and challenges related to reuse and recycling of by-products from the existing or alternative steelmaking routes. A time horizon of 10 years has been considered, taking into account the European Commission targets to achieve carbon neutrality in a circular economy context. In addition, current technological trends derived from past and ongoing research projects are analysed. Research needs are based on the main categories of by-products and residual materials. Due to the different pathways to reduce CO2 emissions, each category is divided into subcategories considering both current and novel process routes targeting decarbonization of steel production. This work identifies the most urgent and demanding research directions for the coming years based on a survey targeting the steel companies, services providers of the steel industry and research organizations active in the field.

“…The collected data can be exploited, for instance, in order to investigate the viability of novel processes by developing relevant models, to test them and related new operating practices, by thus paving the way to CE and IS solutions, for instance, aimed at decreasing the importance of secondary working operations to provide ready-to-sell resources, according to market requirements. A number of examples can be found in literature, where different kind of modelling tools are exploited after being tuned through process data in order to improve environmental sustainability of steelmaking processes, by enforcing resource and energy efficiency [15][16][17][18]. Such modelling tools can also be embedded into advanced monitoring systems for improving energy and resource efficiency at plant level [19,20].…”

Section: Enabling Circular Economy and Industrial Symbiosis Through Digital Transformationmentioning

confidence: 99%

Environment 4.0: How digitalization and machine learning can improve the environmental footprint of the steel production processes

Pietrosanti

Malfa³

et al. 2020

Matériaux & Techniques

Self Cite

The concepts of Circular Economy and Industrial Symbiosis are nowadays considered by policy makers a key for the sustainability of the whole European Industry. However, in the era of Industry4.0, this results into an extremely complex scenario requiring new business models and involve the whole value chain, and representing an opportunity as well. Moreover, in order to properly consider the environmental pillar of sustainability, the quality of available information represents a challenge in taking appropriate decisions, considering inhomogeneity of data sources, asynchronous nature of data sampling in terms of clock time and frequency, and different available volumes. In this sense, Big Data techniques and tools are fundamental in order to handle, analyze and process such heterogeneity, to provide a timely and meaningful data and information interpretation for making exploitation of Machine Learning and Artificial Intelligence possible. Handling and fully exploiting the complexity of the current monitoring and automation systems calls for deep exploitation of advanced modelling and simulation techniques to define and develop proper Environmental Decision Support Systems. Such systems are expected to extensively support plant managers and operators in taking better, faster and more focused decisions for improving the environmental footprint of production processes, while preserving optimal product quality and smooth process operation. The paper describes a vision from the steel industry on the way in which the above concepts can be implemented in the steel sector through some application examples aimed at improving socio-economic and environmental sustainability of production cycles.