The Study on Bridge Steel Structure Manufacturing Processes based on Logistics E

Abstract.The steel industry is a national development key industry. Mixed ore information is very important step. Bridge steel structure manufacturing internal logistics chain is lack of hybrid optimization. The deficiency, analyzes the mixed ore material in this article, it is many experts think ore mixed as an independent steps, not production is the internal think the combination of the logistics chain steel company material supply. In view of these questions, logistics balance concept model. And new ideas put forward to solve the mixture model, and give a new original ore hybrid optimization problem. Then, the author use computer programs to realize this idea. Calculation results show that is effective and correct.

Key words: blending; logistics; equilibrium; optimized algorithm

1.Introduction

The massive ore are needed in the steel-making process of the Iron and steel enterprise. The blending of the ore material is the important Step, which influence the following production process. Until now, many scholars have already carried on the discussion of blending optimized.

XuWei[1]used ant colony algorithm to achieve Burdening plan and expected ingredient. Li Zhi[2]established Raw ore balanced-blending model and ant colony algorithms were used in optimization of raw ore balanced-blending for smelting iron and steel in order to settle the gradual shortage of raw ore materials. A math model for blending the material was established by LI Zhi[3] and the amount of the blended material in the Industrial port of bridge steel structure manufacturing was calculated by means of the simulated annealing based optimal algorithm. However, these literatures regarded ore blending as a independent production step and has not consider that blending is belong to the bridge steel structure manufacturing internal logistics chain. This paper put forward a new way to solve the blending optimized mode by means of logistics equilibrium mind.

2.Logistics Equilibrium Conceptual Mode Of Bridge Steel Structure Manufacturing

The bridge steel structure manufacturing internal logistics flowing process may summarize as follows. The ships arrive at the port and unload. A part ore is entered the materials yard to store up and the other is delivered to carry on blending process through the belt conveyer. This entire process is regarded as a union of two kind of different production method. The first stage is as follows: the ships arrive at the port to unload cargo and then the ore materials are delivered to the materials yard, which is belongs to the push type production process. The second stage is as follows: ore raw materials are transported from the materials yard to blending Location and mixed powder, which is belongs to the pull type production process. There is a boundary exists in two kind of different production method's Combining site. This boundary can adjust the conflict between the push and pull-type production, which is stocks of bridge steel structure manufacturing internal logistics (as fig 1).

Therefore, Inventory control becomes an important part of logistics equilibrium. As a part of bridge steel structure manufacturing internal logistics industrial port’s internal logistics system, the inventory control mainly relies on two aspects. On the one hand, ore raw materials procurement should be planned according to Productive schedule. On the other hand, the put out of raw materials should be controlled. In short, blending should be managed on the grounds of the inventory. What are mentioned above enables WISCO’s industrial port internal logistics system to have the big improvement.

3.Blending Model And Optimized Algorithm

Blending proportioning relies on the work of the factory dispatchers who selects varieties of single-irons, and then the technicians use the traditional method for calculating or estimating to obtain the approximate quantity of varieties of iron ores finally. The key to balance the process of logistics in this system lies in making use of storage yard effectively which play an important role in adjustment supply and demand, consequently, ascertaining the combination of raw materials under the process of blending proportioning has become a key issue.

3.1.Set up a blending model

Raw material blending is generally chosen from many kinds of single variety ores comprehensively, according to the number of existing yards, the content of TFe and the content of SiO2. The constrains for blending are as follows: each selected single variety iron ore can not be less than 3% of the total; the content standard for TFe is Invariable, and the content standard for SiO2 is Invariable after the iron ore blending, the total volume of the blending should be 180,000t.

On the premise that the volume of the blending meet the requirements , this model should ensure that the accuracy of TFe and SiO2 is the highest, namely, minimum the sum square of the difference between the actual value and the theory value which satisfies the technological requirements. The lower the difference between the actual value and the theory value is, the more accurate the blending is. The basis for selection of the iron ores is their, namely, the priority of the iron ores entering into model is based on the priority of their inventory volume. Whose inventory reach a high level of restriction has priority to. When all iron ores which have high level of priority enter into the blending proportioning calculation , the others whose inventory volume are at reasonable level will enter into the model [4].

Blending proportioning mathematical model [3] is a linear programming model of multi-variable and linear constraints, and the number of variables selected is in accordance with the types of iron ores chosen. Its mathematical model is as follows:

Where,

i represents the all types of iron ores can be used in industrial ports’ operations;

is the amounts of requirements for;

is the content of TFe for iron ore i;

is the content of TFe for SiO2;

is the existing stock of the iron ore i on the storage yard;

D is the volume of the blending ores.

R is the number of the iron ore that will be used in blending process.

X is the TFe%

Y is the SiO2%

k=0

3.2.Solution strategy of blending model

Solution strategies are as follows:

Step 1: First of all, the set of iron ores to choose for blending can not be less than 3% of the total volume of the blending stack, which shows as follows:

Step 2: Assume that

Obtain a number of combinations

by method of permutation and combination. Given there are n kinds of iron ores which meet the requirements of the blending, and we choose k kinds of them for blending, then the content of Tfe for each of them can be represented as

And content of SiO2 for each of them can be represented as

Step 3: For a combination PI , the optimal model for solving the problem are as follows:

firstly Make ki=0 , ……..by judging the value of permutation and combination, for example, assuming that

, then

is the subscript ,at the same time, the corresponding content of Tfe and SiO2 can be obtained, the model can be simplified to an optimization problem which is the exclusive constraint

Step 4: Circulation solution , and reached the optimal solution

4.Example

We have a Example is as follows: according to reference [4], the 12 raw material stocks, TFe and SiO2 content were Known.(as table1). The blending model is solved by computer program that is written according to the optimized algorithm what is mentioned above. The result is different from the paper [4] and is demonstrated in table 2.Which is provided another kind of mentality. Namely, the optimized algorithm is based on logistics equilibrium. The stock must be considered firstly.

Table i. Known data

Other known date is as follows: the content standard for TFe is 62%, and the content standard for SiO2 is 4.89%, R=6.

The result is as follows (as table 2):

Table ii. Results

5. References

[1]XuWei1, Rongcheng Wang. Application of ant colony algorithm in sinter burdening of mixed and uniformed ore. Metallurgical Industry Automation. 2010.6,pp12-15.

[2]Li Zhi, Xie Zhao-Hong. Application of ant colony algorithm in optimization of metallurgical raw ore balanced blending. MINING & METALLURGY.2004.3, pp75-78

[3]Li Zhi, Langguang Lu. Application of simulated annealing based optimization algorithm in material blending. Research on Iron&Steel.2009.6

[4]Li Zhi,Appl ication of Hopf ield Neural Network in Blending of Raw Ores Metal Mine.2003.9

[5]Zhang Wangxin et al. Practice of improving the output and quality of blending ores in wisco industrial-port . Sintering and Pelletizing,2004.6.

[6]Zhang Ruinan.Influnce of raw material blending on the economic benefit of sintering process. Sintering and Pelletizing,2003.1.