Blast Oxygen Furnace (BOF) slag represents one of the largest waste fractions from steelmaking. Therefore, slag valorisation technologies are of high importance regarding the use of slag as a secondary resource, both in the steel sector and in other sectors, such as the construction or cement industries. The main issue regarding the use of BOF slag is its volumetric instability in the presence of water; this hampers its use in sectors and requires a stabilisation pre-treatment. These treatments are also cost-inefficient and cause other environmental issues. This paper analyses the use of untreated BOF slag from a technical and environmental point of view, suggesting it as an alternative to natural aggregates in road surface layers and asphalt pavements. A comprehensive analysis of the requirements to be met by raw materials used in asphalt mixes was performed, and a pilot test was carried out with two different mixtures: one mix with limestone as coarse aggregate and another with 15% BOF slag. Furthermore, the global warming impacts derived from each mix with different aggregates were measured by Life Cycle Analysis (LCA), and a transport sensitivity analysis was also performed. The results show how the utilization of BOF slag as coarse aggregate in road construction improves the technical performance of asphalt mixtures (Marshall Quotient 4.9 vs. 6.6). Moreover, the introduction of BOF slag into the asphalt mix as a coarse aggregate, instead of limestone, causes a carbon emissions reduction rate of more than 14%.

Land degradation, and especially acidification, are global issues that need to be addressed. A common practice to correct this problem is the use of lime or chemical fertilisers that involve the extraction of raw materials. This study proposes a more sustainable alternative using Basic Oxygen Furnace (BOF) slag. BOF slag is the main waste from the steel industry that is usually accumulated in landfills, which also implies environmental impacts. In this study, a series of laboratory tests have been carried out to analyse the feasibility of using BOF slag for the reclamation of degraded land. For soil acidification, BOF slag will be analysed as a liming agent. On the other hand, the benefits slag can provide as a nutrient source will be tested. As an added value, pre-treated and untreated slag will be compared. The results of these short-time experiments show how BOF slag could be a sustainable alternative as liming agent and amendment. Its use increased the levels of some micro and macronutrients available for plant growth and improved soil quality. It could, therefore, be a sustainable management practice that makes an important contribution to the circular economy.

The converter furnace and the continuous casting are the most important stages in steel production. Modern integrated processes directly connect the converter furnaces and the continuous casting machines with a flow of molten metal, and the steel is manufactured synchronously between the various machines. Starting from the traditional handmade programs for the management of these processes, during the last two decades there has been a notable increase in studies and publications in this field, trying to formulate scheduling in a rational and automatic way. The process has been approached for years through the development of both physical and operational research models, many of them theoretically. The main purpose of this study is to present a critical and in-depth evaluation of the previous studies, so that the state of the art of scheduling in steelworks can be evaluated. An approach based on a Systematic Literature Review (SLR) has been used, trying to search, evaluate, synthesize and analyze all the relevant studies for this specific field. As a result, the conclusions of the various analyses are presented and a study route is proposed for the design of the optimal planning methodology in the steelworks.

Galvanised steel atmospheric corrosion is a complex multifactorial phenomenon that globally affects many structures, equipment, and sectors. Moreover, the International Organization of Standardization (ISO) standards require specific pollutant depositions values for any atmosphere classification or corrosion loss prediction result. The aim of this research is to develop predictive models to estimate corrosion loss based on easily worldwide available parameters. Experimental data from internationally validated studies were used for the data mining process, basing their characterisation on seven globally accessible qualitative and quantitative variables. Self-Organising Maps including both supervised and unsupervised layers were used to predict first-year corrosion loss, its corrosivity categories, and an uncertainty range. Additionally, a formula optimised with Newton’s method has been proposed for extrapolating these results to long-term results. The predictions obtained were compared with real values using Euclidean distances to know its similarity degree, offering high prediction performance. Specifically, evaluation results showed an average saving of up to 16% in coatings using these predictions. Therefore, using the proposed models reduces the uncertainty of the final structures state by predicting their material loss, avoiding initial over-dimensioning of structures, and meeting the principles of efficiency and sustainability, thus reducing costs.

Many organizations are currently face significant challenges in terms of sustainability and technological development. Achieving sustainability in business activities, interweaving social, economic, and environmental perspectives, is one of the most challenging goals for companies. On the other hand, as technology advances exponentially, organizations grow in a linear way. This fact causes a gap which increases over the time. Models and tools have been developed to try to solve both problems separately; on one side to make the organization grow exponentially, and on the other side to incorporate sustainability into the business model. However, they do not allow enough time to know if the actions carried out really achieve their aim. The model presented provides a solution to both problems by monitoring the evolution of organizations towards an exponential structure through the analysis of the project portfolio. The main objective is to know how the orientation of ongoing projects has changed during the last period, in order to position them in terms of achieving the desired sustainability-oriented transformation. With the model designed, it is possible to know if the actions developed by the company are really heading towards a sustainable model and exponential growth. With the aim of validating the model, it has been applied in an innovation organization. With this model, the level of exponential progress of the organization was determined, as well as the goals that have been attained best and worst so far.

Organisations are under pressure to digitally transform and become more sustainable. Thus, the convergence of digitalisation and sustainability is inevitable. There are several Digital Maturity models that help companies to develop their digital roadmaps, however, none of them have been developed for Research and Development (R&D) organisations. Additionally, none of these models include the dimension of sustainability. In this paper the authors used the Means-End Chain method to determine which are the key dimensions of the digital maturity model tailored for R&D, as well as to investigate the link between digital transformation and sustainability. The results show that although technologies are important, they cannot successfully transform the organisation on their own. They must be supported by people and culture change. The results also highlighted that sustainability is high on the agenda and cannot be ignored when progressing towards the higher level of Digital Maturity. The findings may serve as a reference for any organisation that is building or revising its digitalisation or sustainability strategies. It highlights the important dimensions that should be considered and prioritised when preparing the transformation roadmap. These dimensions are tailored for R&D but can be a good indication for any other type of organisation.