Papers by Author: Hua Zhang

Abstract: Regarding 20 tons hydraulic excavator boom in an enterprise as the research object, the boom volume was set as an optimized object. According to the dynamic simulation analysis of working device in typical working conditions, constraint conditions including the maximum stress, displacement range and thickness variable ranges of each steel plate, were determined, and the thickness of twelve primary steel plates of boom were selected as design variables. A lightweight design scheme has been developed through the optimization module in ANSYS software, which could decrease the boom weight by 9.7% and the strength and stiffness of optimized boom structure also met the design requirements.

Abstract: According to the present situation of lack of systemic analysis for manufacturing resources optimization operation for iron and steel enterprise in domestic and overseas, a resource input/output frame about steel and iron manufacturing unit was established to analyze the resource consumption situation, and the main line of steel green manufacturing resources was built, which is based on the theory and method of green manufacturing and the operation law of iron and steel enterprise. And manufacturing resources optimization operation strategies were put forward for iron and steel enterprises, considering the resource transformation and consumption from the whole steel product life cycle. The operation strategies can provide guidance ideas for the iron and steel enterprises the most efficient use of material resources and the least energy consumption in the steel manufacturing process.

Abstract: According to the present situation of lack of systemic analysis for green manufacturing operation mode for iron & steel enterprise in domestic and overseas, and based on the theory and method of green manufacturing and the operation law of iron & steel enterprise, a kind of five layer structure of green manufacturing operation mode for iron & steel enterprise was put forward, a segmentation model for green iron & steel manufacturing system integrated operation based on the iron & steel product life cycle was established. The operation mode can provide guidance ideas for the iron & steel enterprises to implement green manufacturing.

Abstract: For the iron and steel enterprises are CO₂ emitters, the reduction of CO₂ emission is the requirement to save energy, protect environment and sustainable development of the steel industry. This article research on iron and steel enterprises operation model based on the characteristics of the accessories resources. And on the analysis of the impact of CO₂ emission factors, a mathematical model is built to reveal how the accessories resources influence the steel manufacture system's resource consumption and environmental impact.

Abstract: The transformation efficiency of main raw materials in iron-making systems is influenced by many factors. Principal factor should be selected to describe the relationship between the transformation efficiency and the Influencing factors. A principal factor analysis model based on Grey Correlation Analysis (GCA) is proposed in this paper. The model is employed to process blast furnace production data and determining the principal factor which is the research base of mathematical model of the transformation efficiency of main raw materials.

Abstract: The end point control for converter steelmaking is important operation in converter smelting later stage, and the end point control level directly affects the production efficiency and product quality. From the point of view of auxiliary resources operating characteristics, we analyzed the steelmaking end point control process, established the terminal forecast model based on DRNN type neural network, and established terminal optimization control model using improved particle swarm optimization algorithm to solve, and finally drew converter terminal optimization control strategy. Through the simulation, the optimal results show that: When the end forecast error (ω[△C]＜±0.03%), hit rate is 93.1%, and with (ω[△T]＜±12°C), hit rate is 94%, supplementary blowing oxygen time is 2.3 min, and materials resources saving 15%. For promoting the work of energy saving and emission reduction of Converter steelmaking process, it has important practical significance.

Abstract: With the in-depth study on the blast furnace iron-making process and the operational characteristic of auxiliary materials in iron-making process, the comprehensive coke rate’s main influencing factors based on the operation characteristics of auxiliary materials were found. Then, a BP neural network model was used to simulate the mathematic mapping relationship between comprehensive coke rate and main influencing factors. Based on the established BP neural network model, through setting the comprehensive coke rate lowest as the goal and using the actual production data of a iron &steel company’s 6# blast furnace ,a genetic algorithm method is adopted to find the best optimal combination among the main influencing factors. The results show that after optimization calculation the comprehensive coke rate could be reduced about 35.85kg. A new perspective and a scientific method are proposed to realize the target of energy conservation and emission reduction in ironmaking process in this paper.

Abstract: During the process of blast furnace, auxiliary, such like coal, coke, oxygen, limestone, and refractory can form different resource conversion efficiency when processed with main material resources which are rich of iron, and this has an important impact on resource consumption and environmental emission. Coke rate is one important technical and economical index in the process of blast furnace production as well as the central exemplification of efficiency and consumption of blast furnace production. This discourse will analysis related subjects from the perspective of operative characteristics of auxiliary resource's effects on comprehensive coke rate in blast furnace, using improved BP neural network of 16-20-1 topological structure to predict comprehensive coke rate in blast furnace. Real practices have proved that this model has low chance of predicative error in the blast furnace production, and this means accuracy and effectiveness.

Abstract: A thermal power valve workshop applying the integrated technology of green planning for workshop layout and machining operations (GPIT) has been constructed from the demands of enterprise development. The key technology is to model the full life cycle production for the typical products in the workshop and carry out a green planning for the whole workshop. By the attribute analysis of the resource consumption and environment impacts, some adaptive processes of green manufacturing and prototypes of processing devices are developed for the physical productions in the valve workshop. The green planning and optimal operation for the workshop production is implemented and the remarkable environmental and economic benefits are gained.

Abstract: Owing to the diversity of green evaluation index and multiple-factor related to the process evaluation, existing green evaluation of manufacturing process lacks a set of effective knowledge management model. It leads to the high cost and inefficiency of analysis and evaluation process. A green evaluation model for manufacturing process based on multi agent is presented. Based on the model, green evaluation support system of manufacturing process based on multi agent is developed with the knowledge base introduced. The implementation strategy of green evaluation for manufacturing process is implemented by the closed-loop knowledge chain, which is composed of knowledge mining, knowledge transferring, knowledge application and knowledge feedback. The feasibility of this system is verified by an instance of the valve stem manufacturing process in a valve factory.