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The aim of this study is to investigate the ongoing energy management and energy efficiency practices in the industries of Peshawar division of Khyber Pakhtunkhwa, Pakistan. The outcomes of this research shows that Khazana Sugar Mills, Caliph Pharmaceutical, Naguman Flour Mill have no or low awareness of energy management practices (awareness level mainly includes barriers to energy efficiency and drivers for energy efficiency) except FF steel mill. The major paces observed in lacking the awareness are (1) “understanding level of staff and workers about energy savings due to energy management practices” (2) “interest level of top managers for energy management implementation” (3) “awareness level regarding energy efficiency” (4) “lack of technical competence” (5) “use of standardized procedures”. When the industry managers were inquired about the relationship with energy service providers it is found that there is absolute absence of energy engineers, relationship with energy consultancies and long-term energy strategy in all the industries. It was also found that there is lack of using renewable energy technologies in all industries as they were relying upon using the generators during the blackout hours. In terms of percentage, the energy saving factor of 36 kWh/day has also observed with the replacement of fluorescent tube lights with light emitting diode (LED) tube lights. Proper maintenance and energy management practices in the heating, ventilation and air conditioning system (HVAC) would also save energy in a significant amount. The study shows that there is an overall improvement factor of 4% to 8% if the inclusion of energy management and energy efficiency practices would have been applied in all the stated industries.

Water from the River Niger in Ajaokuta, Kogi State, Nigeria, was tested for physico-chemical characteristics.Temperature, dissolved oxygen (DO), electrical conductivity (EC), total hardness, total alkalinity, magnesium(Mg), calcium (Ca) and chloride were the variables studied (Cl). During the rainy and dry seasons, watersamples were taken in triplicate from six separate locations along the river and were subjected to physicochemicalanalyses using APHA standardized procedures. The results were compared to World HealthOrganization (WHO) and Nigerian Standards for Drinking Quality Water (NSDQW). Consequently, themajority of the parameters examined were below the WHO's recommended safe drinking water threshold.However, the pH and surface water temperature were above WHO guidelines. Comparison of data obtainedbetween rainy and dry seasons was made using t-statistics at P≤0.05 and this revealed significant seasonalvariation in water temperature (28.80oC and 29.40oC), DO (6.43mg/l and 7.18mg/l), Ca (5.21mg/l and 4.16mg/l)and Cl (5.20mg/l and 3.50mg/l). Therefore, in order to protect the communities living along the water body, it isrecommended that regular water quality testing be made mandatory.

The heating furnace is a sizeable energy-consuming device in iron and steel industry. In compact strip production (CSP), the size of the heating furnace is large and the working conditions are complicated. Furthermore, the large fluctuation of furnace temperature leads to large loss of billet combustion and energy consumption. This paper deals with the design of hybrid intelligent control based on condition identification for the combustion process of the CSP heating furnace. By analyzing the process of the heating furnace and existing problems, the structure of a hybrid intelligent control system is proposed, and the working conditions are divided into two categories: stable and fluctuating. A fuzzy controller is designed to improve the control accuracy of furnace temperature under the stable working condition, and an expert controller is used to adjust the temperature rapidly under the fluctuating working condition. Besides, calorific value compensation is introduced to reduce the influence of calorific value of gas fluctuation on temperature. After verifying the effectiveness, the proposed method has been used in a steel plant and achieved a good control result. The intelligent control system improves the control precision of the furnace temperature and reduces energy consumption compared with the traditional control system.

Early guidance is required to match Industry 4.0 ambitions with an understanding of the evolving Industrial Internet of Things (IIoT) system and its capabilities. Considering IIoT systems and operational methodologies within steel manufacturing, a three-stage evolving IIoT system is proposed. IIoT requirements for selected Industry 4.0 applications are presented and generalized guidance matches the application with the relative support level of each evolutionary stage. The guidance specifically considers digital twins, cyber-physical systems, horizontal and vertical integration, integrated worker health and safety, increased workforce mobility, and advanced maintenance. To demonstrate how the evolving IIoT system aids or potentially prevents Industry 4.0 applications, the feasibility of advanced maintenance strategies within steel manufacturing are presented, including predictive and self-maintenance.

Based on the core developmental demands of smart steel manufacturing plants, this review analyzes the essential characteristics of the steel manufacturing process and its implications for production and operation decision optimization (PODO). A discussion on the potential application of technologies, including the Industrial Internet, big data, cloud computing, and 5G, in the PODO of smart steel plants based on the Industry 4.0 intelligent manufacturing and human-cyber-physical system (HCPS) is also presented. An adaptive update conception for a new dual-level cyber system (for management control and unit operation) of a flat-structured HCPS for steel plants is proposed to eliminate issues such as the hierarchical structure of the cyber system, the occurrence of data islands, and weak intelligence in PODO ability. Additionally, the review provided an in-depth analysis of the closed-loop decision logic of a dual-level HCPS. The critical technologies required for developing the HCPS model include data platforms and their associated application technologies, intelligent modeling, human-machine collaboration, and platform-based integration. Finally, suggestions are proposed to develop smart steel plants, including concept renewal, technological integration, and talent training.

Recycling plays a vital role in preserving resources like steel and consequently in a circular economy. Scrap dealers and steel mills, the main business units in this system, often encounter opposing financial and sustainability incentives in using scrap as feedstock because regular sorting and scrap-preparation infrastructure cannot deal with the increasing complexity of steel scrap. Mismatches between the inputs and the target composition of the recycled steel result in trade-offs that favor the economics at the expense of resource efficiency. By examining literature and interviewing several actors, different scrap characteristics were identified as dimensions of scrap quality. Quality is typically associated with chemical composition, which is important, but this study aims to elaborate the concept of quality further and to connect it to the realities of scrapyard operations. Industry actors have different definitions for desired content, physical condition, shape and size, and homogeneity, based on their needs. Very few studies examine these details. Additionally, the relationship of quality and the level of information about the characteristics of the material was established. Having more definitive information on scrap increases opportunities for resource-efficient actions. This work offers an alternative perspective on how to address issues pertinent to recycling. Graphical Abstract

Steel slag is an industrial by product of steel manufacturing processes and has been widely utilized within civil and construction materials for road materials and environmental remediation in countries like Japan, USA, and European Union nations. However, the current utilization of steel slag in Vietnam is very low mainly because of lack of quality control of slag treatment and chances for reuse of treated steel slag. This paper presents the up to date steel slag production status in Vietnam through the extensive survey and sampling at seven large steel factories. The paper also highlights the environmental and quality control issues of these steel slags to use as road construction aggregates by assessing the heavy metals concentration in the leachate. The basic oxygen furnace (BOF) and electric arc furnace (EAF) slag samples were collected to evaluate leaching properties of metals leached from the slags. The two standardized batch leaching tests of steel slag roadbed material in Japan (JIS K 0058-1) and toxicity characteristics leaching procedure (TCLP-EPA method 1311) were performed to the evaluated the hazardous metals. The results of the leaching test show that almost all of the concentration of the metals in the leached solution does not exceed the National Standard for Industrial Wastewater Discharge (QCVN 40-2011). The pH and parameters such as total chromium, nickel, copper, lead, arsenic, and manganese differ from the two test methods. The acidic conditions employed in the EPA 1311 were not representative of condition excepted during slag reuse in road constructions because in the operation condition of the road, acidic liquid is absent. The leaching test results confirmed that JIS test which uses deionized water with gentle mixing prevents the slag sample from size degradation is suitable for the environmental assessment of steel slag use for roadbed material. This research suggests that the adjustment of pH value prior to disposal or reuse as base materials and official guideline should be promulgate by the authorities to ensure the leachate meet the surface water quality standard.

To optimize ladle scheduling in the empty-ladle operation stage of steel plants, a mathematical scheduling model was established for the empty-ladle operation stage, taking the minimum total waiting time in the empty-ladle operation stage as the optimization goal and setting the equipment assignment uniqueness as the key constraint. An improved genetic algorithm was designed to calculate the mathematical scheduling model. In the operation of the genetic algorithm, the strategy of “ladle temperature drop control” was adopted to solve the problem of equipment conflicts and reduce unreasonable ladle temperature drops to enhance “red-ladle” utilization. Five main production modes operating at 95% capacity in a Chinese steel plant were simulated using the genetic optimization model. The results showed that the genetic optimization model could improve the efficiency of ladle operation and reduce the total waiting time in the empty-ladle operation stage by 868–1147 min.

Purpose The purpose of this paper is to establish the structural relationships between the environmental sustainability enablers (ESEs) for the steel supply chain in India and also to classify them on the basis of driving and dependence power with an objective of achieving enhanced environmental sustainability performance. Design/methodology/approach The ESEs were identified through extensive literature review and discussion held with experts from the Indian steel industry. The interpretative structural modeling (ISM) approach was applied to an Indian steel supply chain to arrange these 12 ESEs in different hierarchies of the structural framework on the basis of their driver dependence power and also diagraph was developed to classify them. Findings The water pollution control system, air pollution control system and soil pollution control system were found to be in the bottom hierarchy of the ISM framework and these enablers were also observed in the driving quadrant of the diagraph. These driving enablers should be given priority for its full-scale development, management and monitoring to sustain and enhance the environmental sustainability in the Indian steel supply chain, whereas top management commitment, environment compliance certification and government regulation and incentives are the antecedents for carrying out the sustainability program. Research limitations/implications The outcomes of the current study are limited to the Indian steel manufacturing company in specific but the results will not change significantly for the steel sectors in India. However, an empirical analysis can be used to explore and validate the structural framework for its acceptability. Practical implications The outcomes from the methodology provide the basis for an Indian steel manufacturing industry to develop the right strategy in their quest for environmental sustainability. Originality/value Although the study on ESEs of various industries was reported in the literature, the comprehensive study to identify the significant ESEs related to the Indian steel supply chain for environmental sustainability in specific have been hardly carried out. The current study will definitely be a valuable addition to environmental sustainability literature in general and steel supply chain environmental sustainability in specific.

In the BOF steelmaking process, lime quality and quantity directly affect slag quality, affecting metallurgical results, liquid metal yield, productivity, and therefore the total cost and environmental impact of the steel production. In this paper, a value in use model based on mass balance and heat balance was developed and used to evaluate the impact of lime quality on the BOF process. The model is capable of calculating the consumption of scrap, lime, oxygen, the volume and composition of the slag and the volume and composition of off-gas and facilities to calculate the cost-benefit contributions and potential cost saving for a configured choice of various types of lime and operating parameters. The model has been successfully validated using the data of the Steel Plant. Then three types of lime with different qualities were used to elaborate on the impact of lime characteristics in optimizing the steelmaking process, metallurgical benefits, overall cost impact, potential savings, and environmental benefits. The calculation results show that good-quality lime could increase the scrap ratio, reduce the lime consumption, and reduce iron loss, accordingly, improve the steel quality, increase steel yield, reduce the smelting costs, stabilize smelting operations, and reduce CO2 emissions.

In order to promote the intelligent transformation and upgrading of the steel industry, intelligent technology features based on the current situation and challenges of the steel industry are discussed in this paper. Based on both domestic and global research, functional analysis, reasonable positioning, and process optimization of each aspect of steel making are expounded. The current state of molten steel quality and implementation under narrow window control is analyzed. A method for maintaining stability in the narrow window control technology of steel quality is proposed, controlled by factors including composition, temperature, time, cleanliness, and consumption (raw material). Important guidance is provided for the future development of a green and intelligent steel manufacturing process.

After nearly one hundred years of research, metallurgy (metallurgical science and engineering) has gradually become a system with three levels of knowledge: (1) micro metallurgy at the atomic/molecular scale, (2) process metallurgy at the procedure/device, and (3) macro-dynamic metallurgy at the full process/process group. Macro-dynamic metallurgy development must eliminate the concept of an “isolated system” and establish concepts of “flow,” “process network,” and “operating program” to study the “structure-function-efficiency” in the macro-dynamic operation of metallurgical manufacturing processes. It means considering “flow” as the ontology and observing dynamic change by “flow” to solve the green and intelligent potential of metallurgical enterprises. Metallurgical process engineering is integrated metallurgy, toplevel designed metallurgy, macro-dynamic operated metallurgy, and engineering science level metallurgy. Metallurgical process engineering is a cross-level, comprehensive, and integrated study of the macro-dynamic operation of manufacturing processes. Metallurgical process engineering studies the physical nature and constitutive characteristics of the dynamic operation of steel manufacturing process, as well as the analysis-optimization of the set of procedure functions, coordination-optimization of the set of procedures’ relations, and reconstruction-optimization of the set of procedures in the manufacturing process. The study establishes rules for the macro operation of the manufacturing process, as well as dynamic and precise objectives of engineering design and production operation.

Green supply chain is the process used for diminishing the exploitation of resources and producing sustainable technological development. The aim of the research work is to build the proficient Industry 4.0 green architectures index for assessing the feasible candidate choice. In the research work, a crisp numbers set-based MOORA-FMF advanced technique is executed for examining the Industry 4.0 green architectures of vendors firms. The managers are assisted with an Industry 4.0 green architectures index with optimization technique to quantify the performances of alternatives. Therefore, a real case study of a steel manufacturing plant is carried to simulate the proposed Industry 4.0 GSC architectures. Eventually, the results are presented in the conclusion.

The steel industry is one of the most important industry sectors, but also one of the largest greenhouse gas emitters. The process gases produced in an integrated steel plant, blast furnace gas (BFG), basic oxygen furnace gas (BOFG) and coke oven gas (COG), are due to high shares of inert gas (nitrogen) in large part energy poor but also providing a potential carbon source (carbon monoxide and carbon dioxide) for the catalytic hydrogenation to methane by integration of a power-to-gas (P2G) plant. Furthermore, by interconnecting a biomass gasification, an additional biogenic hydrogen source is provided. Three possible implementation scenarios for a P2G and a biomass gasification plant, including mass and energy balances were analysed. The scenarios stipulate a direct conversion of BFG and BOFG resulting in high shares of nitrogen in the feed gas of the methanation. Laboratory experimental tests have shown that the methanation of BFG and BOFG is technically possible without prior separation of CO2. The methane-rich product gas can be utilised in the steel plant and substitutes for natural gas (NG). The implementation of these renewable energy sources results in a significant reduction of CO2emissions between 0.81 million tonnes CO2eqand 4.6 million tonnes CO2eqper year. However, the scenarios are significantly limited in terms of available electrolysis plant size, renewable electricity and biomass.

Asansol-Durgapur Industrial Region serves as nerve-knot of the economy of West Bengal as well as the entire economic region of Eastern India because of its enormous reservoir of excellent quality of coal of Raniganj Coalfield, outstanding network of transport by rail and road, skillful and cheap labour in close proximity of states. With the establishment of a number of large industrial units like Iron & Steel Plant, Durgapur Steel Plant, Chittaranjan Locomotive works, Durgapur Alloy Steel Plant, Durgapur Thermal Power Station, and hundreds of medium and small-scale industries have made the region great industrial belt after Hooghly industrial belt in West Bengal. Though there was rapid industrialization after independence period but the growth of industries has not taken place uniformly throughout the study area. This is because, high manufacturing intensity found in Durgapur, Asansol, Raniganj and Kulti areas whereas the Salanpur, Jamuria, Fraidpur, Barabani areas witnesses low manufacturing intensity. The decadal growth of industries also noteworthy, in 1951 there were 46 industrial units and it increased to 430 in 2019. The number of basic metal and engineering units was 2 and 18 respectively in the year 1951 whereas in 2019 the basic metal and engineering unit increased to 122 and 66 respectively. This paper primarily focuses on the estimation of spatial and temporal distribution of manufacturing industrial units, growth and structural changes, manufacturing intensity and concentration of the manufacturing sector during the period of 1951 to 2019 in Asansol-Durgapur Industrial Region.

Intelligent iron/steel manufacturing has been drawing increasing attention in recent years. Slagging is of importance for clean steel production in the ladle furnace (LF) refining process. In this ...

This paper aims to present a procedure that allows identifying savings opportunities in a steel manufacturing company. The procedure based on the ISO 50001, 50004, and 50006 standards comprise the use of tools such as energy baselines, the goal line, energy performance indicators, the Pareto chart, and an energy review. As a result of the implementation of the procedure, it was possible to obtain the baseline, the goal line, and energy performance indicators that allow the control of energy consumption and efficiency of the company in general and of the area with the highest electricity consumption. It was possible to identify that there is a potential savings of up to 6% throughout the company and up to 13% in the area with the highest electrical energy consumption. From an energy review carried out in the area with the highest consumption, motors operating with low load and idle for long periods were identified, as well as a lack of maintenance. Besides, the replacement of traditional technology lamps by LED technology lamps was proposed. The procedure can be generalized in steel industries with similar characteristics, which is one of the sectors that consume the most energy worldwide.Keywords: Electricity, Energy, Energy Efficiency, Energy Saving, Energy Performance Indicator, Steel IndustryJEL Classifications: Q4, L610DOI: https://doi.org/10.32479/ijeep.11142

One of the four conditions gives rise to the need for OD interventions. First, the organization has a problem; something is “broken” Corrective actions - interventions - are implemented to “fix” the problem. Second, the organization sees an unrealized opportunity; something it wants is beyond its reach. Enabling actions - interventions - are developed to seize the opportunity. Third, features of the organization are out of alignments; parts of the organization are working at crosspurposes. Alignment activities - interventions - are developed to get things back “in sync”. Fourth, the vision guiding the organizations changes; yesterday’s vision is no longer good enough. Actions to build the necessary structures, processes, and culture to support the new vision. Interventions are developed to make the new vision a reality.

The paper presents a mathematical model for predicting the mechanical properties of hot rolled strips. The realization of this mathematical model relied on statistical measurements of the mechanical properties (Rm, Rp0,2 and A5) for the laminated strip in the LBC rolling mill from the Liberty Steel Galati steel plant. To achieve this mathematical model, there has been used the active experiment method.By means of this mathematical model, significant time and material savings can be made in the process of testing the mechanical properties for hot rolled tape.