An emergy-based evaluation of a reverse logistics network for steel recycling

Efficient implementation of recycling networks requires appropriate logistical structures for managing the reverse flow of materials from users to producers. The steel sheet distributor studied had established a protocol for scrap recovery with the steel plant and its customers. The company invested in producing containers, hiring a specialized labor force and in purchasing trucks for container transportation to implement the logistics network for recycling. That network interconnected the company with two kinds of customers: the ones returning scrap and the ones who preferred to continue business-as-usual. The logistical network was analyzed using emergy synthesis, and the data obtained were used to evaluate and compare the system's environmental costs and benefits from the perspective of the distributor and the steel plant operator. The use of emergy ternary diagrams provided a way to assess recycle strategies to compare the relative economic and environmental benefits of the logistical network implemented. The minimum quantity of scrap that the distributor must recover to improve environmental benefits was determined allowing decision on whether it is worth keeping the system running. The new assessment method proposed also may help policy-makers to create strategies to reward or incentive users of reverse logistics, and help to establish regulations, by decreasing taxes or stimulating innovation, for effectively implement the National Policy on Solid Waste. (C) 2013 Elsevier Ltd. All rights reserved.

Planejamento e controle da produção de cilindros para laminação: um estudo de caso quantitativo

Este trabalho apresenta um modelo de otimização-simulação aplicado em um estudo de caso real no setor de cilindros para laminação de uma siderúrgica, buscando melhorar o gerenciamento da área/equipamento gargalo da linha de produção. A simulação atuou em conjunto com um modelo de otimização da programação linear inteira (PLI) para melhorar o atendimento de prazo junto aos clientes em uma produção não seriada. Como resultado deste procedimento combinado da PLI e simulação, o processo produtivo foi otimizado e as filas de espera e o lead-time foram reduzidos, melhorando o atendimento aos clientes.

Remote Sensing Detection of atmospheric pollutants using Lidar, Sodar and correlation with air quality data in an industrial area

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

Analise das emissões de CO2 e de energia - simulação com novas tecnologias siderúrgicas

The process of steel production emits a large quantity of greenhouse gases, specifically carbon dioxide (CO2), and the reduction of such emissions is one of the main challenges for the industry in the 21st. Century. To quantify these emissions, the Worldsteel Association (association of the 170 large steel manufacturers of the world) published a methodology (CO2 Emission Data Collection) for calculation and comparison of CO2 emissions among its members. After that, in 2010, this methodology became an ISO (International Organization for Standardization) norm. Today, the calculation of the CO2 emissions in steel making companies follow the ISO 14404-1 for units with blast furnaces and the ISO 14404-2 for units with electric furnaces. In the last years, new technologies were and continue to be developed for the steel making sector aiming at energetic improvements and greenhouse gas reductions (mainly CO2) by the several processes involved in the production of steel. This work had the objective of producing a tool to calculate the CO2 emissions for the steel making sector. An Excel spreadsheet was developed to calculate the emission intensities of CO2 of a steel plant, the Usina Presidente Vargas, of the Companhia Siderúrgica Nacional (CSN). The spreadsheet furnishes results of CO2 emissions and energetic fluxes, and simulates the benefits that some of the new technologies can give to the company. The spreadsheet calculates the emissions in two ways: a) based on the carbon fluxes that enter the unit, and b) based on the emissions of each specific process within the unit (coking, sinterization, blast furnace, among others)

A neural network-based preset generation tool for a steel tandem cold mill

This paper traces the development of a software tool, based oil a combination of artificial neural networks (ANN) and a few process equations. aiming to serve as a backup operation instrument in the reference generation for real-time controllers of a steel tandem cold mill By emulating the mathematical model responsible for generating presets under normal operational conditions, the system works as ail option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based oil a lookup table). which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that by this instrument it is possible to achieve nearly the totality of the presets needed by this land of process. The text characterizes the problem, relates the investigated options to solve it. justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results. (C) 2009 Elsevier Ltd. All rights reserved