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Applications of Reverse Osmosis Process in Wastewater Treatment
Published in Mudhar Al-Obaidi, Chakib Kara-Zaitri, I. M. Mujtaba, Wastewater Treatment by Reverse Osmosis Process, 2020
Mudhar Al-Obaidi, Chakib Kara-Zaitri, I. M. Mujtaba
Iron is specifically found in different concentrations in surface water and groundwater, and in wastewater streams from steel production, which consumes a significant amount of water. For instance, the iron and steel industry of China consume around 14% of the total industrial water used in China (Huang et al., 2011). More importantly, a low concentration of iron can impair water distribution systems due to its link to aesthetic and operational issues, including colour, staining, and deposition. This is why physical, chemical, and biological treatment methods have been commonly used to remove iron from various wastewaters under given process conditions (Ellis et al., 2000; Sharma et al., 2001).
Data Envelopment Analysis: Applications to the Manufacturing Sector
Published in Kaushik Kumar, J. Paulo Davim, Optimization Using Evolutionary Algorithms and Metaheuristics, 2019
In addition, several studies considered undesirable outputs into the energy efficiency analysis. Mandal (2010) assessed the energy efficiency considering undesirable outputs of the Indian cement industry. The study proved that without the inclusion of undesirable outputs, the energy estimates are biased. The presence of environmental regulations not only reduces pollution levels but also enhances the energy use efficiency estimates in the Indian cement industry. Wu et al. (2012) assessed energy efficiency of industrial sectors in China using a DEA model with CO2 emissions. The study measures both dynamic and static efficiency performance indexes with a framework of undesirable and desirable outputs. The study found 82.3% improvement in dynamic energy performance. He et al. (2013) quantified productivity and energy effectiveness of 50 enterprises in iron and steel industry of China using conventional DEA and MI. The study also considered undesirable outputs to measure the productivity change using the Malmquist-Luenberger index. The result proved that environmental regulations such as raising the emission standard and charging a pollution emission tax that increases the environmental costs of the firm has a positive effect on the productivity of China’s iron and steel industry. Bi et al. (2014) measured the environmental performance of thermal power generation sector under the environmental regulation framework using the DEA approach. The study used the SBM model of DEA to provide additional insights for environmental protection and energy utilization. The result found low environmental and energy efficiency of the power generation sector. Perroni et al. (2017) applied three different techniques to measure the relative efficiency: DEA, SFA and COLS. The regression quantile is applied to test the link between the enterprise efficiency and the energy efficiency practices adoption level.
A graph partitioning based cooperative coevolution for the batching problem in steelmaking production
Published in International Journal of Production Research, 2021
Gongshu Wang, Qingxin Guo, Wenjie Xu, Lixin Tang
Over the last three decades, the steel industry in China has grown rapidly and becomes the world biggest due to the rapid modernisation of the Chinese economy. Faced with an increasingly competitive market environment, many steel companies in China are committed to promote their capability to produce more varieties of products with different quality requirements to gain more market share. The diversification and individuation of customer needs arisen in the current steel market poses challenges in the area of operations management. In this paper, we study a challenging operation planning problem which deals with consolidating different customer orders into a set of batches to accommodate the mass production mode of steelmaking furnaces. Our goal is to find an efficient method to generate production batches during the daily planning operations such that the key performance indices including utilisation rate of the steelmaking furnace, inventory holding cost, and customer satisfaction can be improved significantly.