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The basic oxygen furnace (BOF) is the dominating primary steelmaking process. It is an autothermal process where hot metal and scrap are used as charging materials. The decarbonization and transformation of integrated BOF steelmaking will be the most important challenge in the coming years. Steel scrap is a charge material without new CO2 emissions, whose availability is expected to grow significantly and will play a key role in this decarbonization process. Several solutions have been developed by Primetals Technologies to provide additional energy for processing higher scrap rates in integrated BOF steelmaking. Such solutions include simple upgrade packages installed on existing converters such as process models for heat optimization, post-combustion, and scrap preheating lances. For higher scrap rates from 30% to 50%, a combination blowing converter and JET converter is required to provide sufficient mixing during scrap melting and the highest heat transfer from the increased post-combustion. Hybrid EAF–BOF operation and limitations regarding scrap quality also need to be considered for the transformation of steelmaking. Scrap sorting and processing can be a solution to reduce residual levels in crude steel for high scrap rates. Based on reference plant data, the CO2 reduction potential of the presented solution versus the effort and complexity of implementation is compared.

This research aims to propose a novel approach for evaluating and minimizing scraps in an industrial production of premium food cans with distortion printing. Beyond conventional formability criteria, a waving requirement is introduced to ensure aesthetic quality of the printed graphics. The research focuses on real production conditions, specifically involving double-cold-reduced (DR) low-carbon steel sheets and chromium-coated tin-free steel with a thickness of 0.16 mm. The sheets are laminated on both sides with a plastic film prior to undergoing distortion printing on the exterior. Subsequently, a blank is subjected to a drawing-redrawing process to form a food can. To address challenges associated with characterizing these thin sheets, a material parameter identification method is proposed and demonstrated. The thickness profile and flange length are identified as key criteria for this identification process. Measurements of thickness distribution and flange length are obtained using digital image correlation (DIC) and microscopy techniques. Within the manufacturing system, uncertainties related to material properties and forming processes can result in scraps or defects. To analyze these processes, finite element analysis (FEA) is employed and validated through experiments. For the evaluation of scrap rates, uncertainty propagation is conducted using a metamodeling technique, specifically employing radial basis function (RBF) neural networks. The study concludes by offering process optimization recommendations aimed at reducing the scrap rate.

Purpose - This paper seeks to document an approach to reduce scrap losses using the root cause analysis technique in a lean manufacturing environment.Design methodology approach - The study uses lean manufacturing root cause problem solving (RCPS) technique. The study starts with the collection phase, followed by the analysis phase and ends with the solution phase. Supporting data are presented using a Pareto chart to prioritise wastage in order to be more focused for improvement. The Toyota Production System's 5-whys analysis is performed to analyse the cause of wastages, to formulate and implement corrective actions.Findings - The application of the 5-whys analysis in a manufacturing industry (XYZ Corporation) provides a fact-based and structured approach to problem identification and correction that not only reduces, but also totally eliminates defects. Corrective action has permanently eliminated the top defect, which is the \"last piece material scratch\" and this results in zero scrap thereafter. In this study it was also proven that with sound understanding of manufacturing coupled with possible solutions using the 5-whys analysis the authors were not only able to eliminate waste, but also to do it with zero-cost.Originality value - The approach documented in the paper can be extended to other areas in the manufacturing industry to help improve overall equipment efficiency, breakdown, time loss, customer complaints, etc.

Some manufacturing firms, particularly in the high-technology sector, have production processes which are characterized by very low initial yields followed by steady \"experience\" based yield improvement. Material Requirements Planning literature reveals that MRP implementations are seldom adjusted in any systematic way to account for such yield improvement. A single product, single stage MRP model is developed which incorporates learning curve behavior into conventional MRP logic. A series of experiments systematically examine the impact on mean inventory level of various combinations of environmental conditions and managerial policies. The research demonstrates that substantial reductions in mean inventory levels can be realized in low yield environments if learning is properly included in the order release logic. This finding proves to be robust with respect to modest errors in the estimation of learning rate.

Assigning tolerance to the nominal dimension of a component is one of the important tasks required to ensure that the product assembled will be within the functional requirements. A non-linear mathematical programming model is proposed for determining the component tolerances by formulating the component's manufacturing cost, the machine's process capability and scrap rate.

The materials charged into a converter comprise molten iron and scrap steel. Adjusting the ratio by increasing scrap steel and decreasing molten iron is a steelmaking raw material strategy designed specifically for China’s unique circumstances, with the goal of lowering carbon emissions. To maintain the converter tapping temperature, scrap must be preheated to provide additional heat. Current scrap preheating predominantly utilizes horizontal tunnel furnaces, resulting in high energy consumption and low efficiency. To address these issues, a three-stage shaft furnace for scrap preheating was designed, and Fluent software was used to compare and study the preheating efficiency of the new three-stage furnace against the traditional horizontal furnace under various operational conditions. Initially, a three-dimensional transient multi-field coupling model was developed for two scrap preheating scenarios, examining the effects of both furnaces on scrap surface and core temperatures across varying preheating durations and gas velocities. Simulation results indicate that, under identical gas heat consumption conditions, scrap achieves markedly higher final temperatures in the shaft furnace compared to the horizontal furnace, with scrap surface and core temperatures increasing notably with extended preheating times and higher gas velocities, albeit with a gradual decrease in heating rate as the scrap temperature rises. At a gas velocity of 9 m/s and a preheating time of 600 s, the shaft furnace achieves the highest waste heat utilization rate for scrap, with scrap averaging 325 °C higher than in the horizontal furnace, absorbing an additional 202 MJ of heat per ton. In the horizontal preheating furnace, scrap steel exhibits a heat absorption efficiency of 35%, whereas in the vertical furnace, this efficiency increases notably to 63%. In the vertical furnace, the waste heat recovery rate of scrap steel reaches 57%.

In this study, the electrochemical deoxidation of Ti scrap metal was performed at 800, 850, 900, and 950 °C using graphite and Pt as the electrodes and molten MgCl 2 as the electrolyte. These temperatures were selected to investigate how the efficacy of deoxidation was affected by the Ti crystallographic structure, as the body-centered cubic β-Ti phase occurs above 882 °C. The results revealed that temperature significantly influences the oxygen diffusion rate and kinetics of deoxidation reactions. A corresponding kinetic model was developed to gain insights into the deoxidation mechanism. The measured oxygen content after deoxidation at 800, 850, 900, and 950 °C was 2100, 1900, 1500, and 3494 ppm, respectively. Furthermore, the effect of MgO activity on the Ti deoxidation rate was experimentally proven to be a function of temperature. These findings indicate that the best deoxidation performance is achieved at 900 °C, compared to the other tested temperatures.

Scrap steel is an important raw material in converter smelting. Increasing the weight of scrap steel can both improve energy recovery rate and reduce the consumption of auxiliary materials. However, due to the fluctuation in raw material conditions and the dispatch hysteresis of the scrap steel, conservative approaches are often adopted during the addition weight of the scrap steel. This study identified the key influencing factors of the scrap ratio in the converter and proposed a scrap addition principle based on molten iron conditions. To solve the problem of precise addition of scrap steel, this study proposed a combined scrap steel addition mode and established a burdening calculation model, making the weight of added scrap steel adjustable during the smelting process. This work can guide the energy in the furnace to converge towards the product and improve the energy recovery rate in the converter. The industrial experiments of this scrap steel addition mode showed that the average scrap ratio increased by 2.13%, the consumption of lime per ton of steel decreased by 1.5 kg/t, the consumption of iron ore per ton decreased by 1.52 kg/t, and the production of steel slag per ton decreased by 10.2 kg/t, significantly reducing costs and increasing efficiency. Graphical Abstract

Metallic materials have enabled technological progress over thousands of years. The accelerated demand for structural (that is, load-bearing) alloys in key sectors such as energy, construction, safety and transportation is resulting in predicted production growth rates of up to 200 per cent until 2050. Yet most of these materials require a lot of energy when extracted and manufactured and these processes emit large amounts of greenhouse gases and pollution. Here we review methods of improving the direct sustainability of structural metals, in areas including reduced-carbon-dioxide primary production, recycling, scrap-compatible alloy design, contaminant tolerance of alloys and improved alloy longevity. We discuss the effectiveness and technological readiness of individual measures and also show how novel structural materials enable improved energy efficiency through their reduced mass, higher thermal stability and better mechanical properties than currently available alloys. Structural metals enable improved energy efficiency through their reduced mass, higher thermal stability and better mechanical properties; here, methods of improving the sustainability of structural metals, from recycling to contaminant tolerance, are described.