JPS596328A - Manufacture of cold-rolled steel strip - Google Patents

Abstract

PURPOSE:To fit the quality of cold-rolled steel for a target by controlling it, by determining annealing temperature considering the effecting degreee of steel composition and manufacturing conditions on mechanical properties of steel sheet when coils passed through hot rolling and cold one are heat-treated in a batch-type annealing furnace. CONSTITUTION:Both elongation and tensile strength of cold-rolled steel strip are appreciably intensely correlated with annealing temperature and N content. How other respective factor involving those ones have an influence on mechanical properties of cold-rolled steel collectively correlatively, is analyzed with multiple regression method and multiple regression formula is obtained. To obtain aimed materials from results such as composition of products, temperature history of rolling process, draft, etc. by using this formula as that for estimating materials, the control of reached temperature of the coldest point (CS) within coil is necessitated. The dispersion of material qualities of cold-rolled steel represented as elongation and tensile strength can be reduced by controlling this CS temperature. Therefore, the coil CS should preferably reach a temperature necessary for obtaining required quality and the annealing temperature is obtained from said multiple regression formula.

Description

[Detailed Description of the Invention] The present invention relates to a method for manufacturing cold rolled steel sheets, and in particular, the present invention relates to a method for manufacturing cold rolled steel sheets, and in particular, the difference in the steel composition of the coil and the hot rolling and cold rolling conditions does not affect the mechanical properties of the cold rolled steel sheets. By taking this into account and determining the annealing temperature in the annealing process, the material quality of the cold rolled steel sheet can be appropriately controlled to meet the target quality.

Conventionally, when manufacturing cold-rolled steel sheets, in order to obtain products with target mechanical properties in each manufacturing process, the manufacturing conditions for each actual process are determined individually based on the accumulation of past empirical technology. Take as an example.

However, in cases such as cold-rolled steel sheets, which require complicated processes from steelmaking to hot rolling to cold rolling, the influence of variations in manufacturing conditions in each of the above steps cannot be quantitatively understood. In addition, since it is impossible to actually measure the internal temperature of the coil during annealing, it is necessary to allow a margin for the holding time in the annealing furnace.

Therefore, due to the fact that the limits of the conditions selected in each of the above processes were set quite widely, the mechanical properties of the final product often varied considerably due to mismatches. show.

For example, Figures 1(a) and (b) show the elongation Et, tensile strength T, and S after annealing for conventional process materials (steel type 5PCD, sample size 0.711111 thickness, number of samples 80). As shown by the frequency distribution, its standard deviation σEt,
,σT,S.

There was a large variation of 1.58 and 1.1, respectively.

Regarding batch annealing of cold-rolled steel sheets, some of the inventors disclosed in Japanese Unexamined Patent Publication No. 157-48984 that the pace fan capacity, total spacer thickness, By using a regression formula that takes into account dynamic and static factors such as coil width, coil weight, and charge weight, the coldest point during annealing (hereinafter abbreviated as 0.8)
An accurate prediction formula for the temperature reached was established.

The inventors conducted further experiments and based on the results of the development of the O8 temperature prediction formula described above, the inventors determined that the effects of variations in manufacturing conditions in each process of cold-rolled steel sheet manufacturing can be advantageously controlled by appropriate selection of the annealing temperature. We discovered that it is possible to absorb and maintain the target mechanical properties of cold rolled steel sheets by controlling the annealing temperature. This realizes the control that can be obtained.

＼ In heat-treating a steel plate that has been rolled up through hot rolling and cold rolling in a batch-type annealing furnace, the steel composition of the steel plate, the extraction temperature during hot rolling, the finishing temperature and The above problem is solved by determining the annealing temperature using a relational expression determined based on statistical processing to determine the influence of the coiling temperature on the thermal history and cold rolling conditions on the material quality.

The inventors first identified the causes of the above-mentioned variations and investigated in detail the correlation between each manufacturing history factor and material properties. A typical example is shown in Figure 2(a).

Fig. 8(a), Φ). As is clear from both figures, the elongation (El, % monthly tensile strength T,
It was found that Sr/, 2) both have a fairly strong correlation with the annealing temperature and the 9-element N component content. What should be noted here is that the annealing temperature, which is the temperature reached by the coil, is always a major influencing factor. This is extremely convenient from the viewpoint of material quality control, and indicates that it can be used as a sufficient control factor.

We investigated to what extent the individual influencing factors, including the above-mentioned annealing temperature and N content %, collectively influence the mechanical properties of cold-rolled steel sheets, and performed the following multiple regression analysis. Ta.

An example of the results is shown as the following general formulas (1) and (2).

E7. = 1o4(J)+ to Ko+, 1. to -X[K)+. -+[L] ・(1) T, S, = Ko'1□'
4 [A) +, '≠ (B) + 8' + [O) + 6' +
(F)+, 'each (G]+□.'舛(J)+K□□
′≠〔K〕 ...(2)K here\ni. , Ko' is a constant, and Ko is 18°K0' is 18' as shown in Table 1.
The factors shown in [ ] are shown in Table 2.

Table 1 Table 2 Note: For (M) here, plate thickness is constant (rolling reduction rate is 70
Since the test was conducted under the condition of % (constant), Ni' is 0, but if this reduction rate exceeds 80018 18 °C, the higher it is, the lower the recrystallization temperature will be, and the essentially advantageous tendency will be inhibited. It will become impossible to ignore it.

By using these multiple regression equations (1,) and (2) as mutual prediction equations, product component values, rolling process history,
In order to obtain the target material based on the actual results such as the rolling reduction rate, it is necessary to control the O8 temperature in the coil as the annealing temperature, which is the final step in which the material can be controlled, according to this invention. By controlling, stretching,
It is possible to reduce variations in the material quality of annealed products of cold-rolled steel sheets, which is represented by tensile strength.

Among the factors in the multiple regression equation, the one that has been the most difficult to measure in the past is the annealing temperature [J]. In particular, in batch-type coil annealing furnaces, the only temperature information obtained from inside the furnace is the temperature at the bottom coil edge (base temperature) and the exhaust gas temperature (bell temperature), and it is not possible to actually measure the internal temperature of the coil. .

The method for estimating the internal temperature of a coil is to use a simulation model of an annealing furnace, as described in Japanese Patent Application Laid-Open No. 57-48984, which has already been mentioned, and the data regarding the internal temperature of the coil are extremely reliable. The effect of annealing temperature [J) on mechanical properties can be predicted with high accuracy.
It is clear that the degree can be grasped quantitatively.

Incidentally, in the case of batch type tight coil annealing, the O8 temperature includes the center of the width W of the coil, as shown in FIGS. 4(a) and 4(b), which show the temperature distribution within the coil cross section and the end cross section, respectively. It refers to the winding thickness R of the coil in the plane.

In general, the annealing temperature and elongation (Et)% are determined by grain growth after the start of recrystallization, as shown in Figure 5, and good elongation properties, but in this case, as shown in Figure 6. Compared to the annealing temperature, the influence of the soaking time is very small.

Therefore, during annealing, it is only necessary that the O8 of the coil reaches the temperature necessary to obtain the desired material quality.

The method for determining the annealing temperature is based on equation (1) as follows:
8) Find an annealing temperature device that regulates the elongation value to approximate the elongation (target value).

Similarly, based on equation (2), the annealing temperature TT, S, which regulates the tensile strength value to be close to the target tensile strength value, is determined by the following equation (4).

For these positions, , TT, and S, the one with a higher temperature pattern is adopted as the necessary annealing temperature.

Equations (3) and (4) can be said to be material prediction equations because they give the annealing temperature that determines El, T, and S. The above is just one example, and by creating each steel type individually according to the multiple regression equation (1) + (2), it is possible to reduce the variation in υ mechanical properties. A cold-rolled steel product is obtained.

A material control system based on a material prediction formula is built into the cold rolling online computer, making it possible to directly change the target temperature during annealing based on the actual results of steelmaking, hot rolling, and cold rolling.

The target temperature is transmitted to and controlled by the process computer of the annealing line.

In this case, the O8 temperature of each stacked coil is controlled to the target temperature based on an annealing furnace control method that can accurately estimate the O8 temperature.

That is, the target annealing temperature is determined using the multiple regression analysis formula according to the present invention, and the heating time for the O8 temperature of each stacked coil to reach the target temperature is determined by the heating completion time shown in the following equation (5). Calculated using a prediction formula.

tA-D=fl~4(XA~xDl''
A~D I Sl~I! IBFAN
IBM Max l BT81np lθAO,S, ~θD
o, S, ) °° (5) ' Bell Initial Temperature For example, if we describe an example in which the annealing temperature is determined using the multiple regression equations (1) and (2) above, 0
0.04%, Mn 0.20%, po, oig%
, S O, 015%, At 0.040%, N O
,0060%, Ou + Ni 10 Or total 0.06
%, ”/N 6.67 A slab manufactured by continuous casting was hot rolled, and the extraction temperature was 1240°0° and the finishing temperature change was 8.
A coil with a winding temperature of 60℃
In order to achieve the target value of 46.0%, the annealing temperature is determined to be 598° C. according to equation (8), and the annealing temperature for TEt, TT, S, and 614° C. The frequency distribution of elongation and tensile strength (50 specimens) when these were batch annealed at the target temperature is as shown in Figure 7(a)t(b>) Figure 1(a),
Compared to (b), the standard deviations σ and σ are significantly /=
T and S were reduced to 1.05 and 0.80, respectively.

Therefore, by optimizing the annealing temperature, despite fluctuations in component elements within the standard working range and differences in hot rolling temperature conditions, by adopting an appropriate annealing temperature calculated using a multiple regression equation, variations in quality can be reduced. However, improvement in quality and stabilization of materials can be advantageously achieved.

[Brief explanation of the drawing]

Figure 1 is a graph showing the frequency distribution of elongation El, tensile strength T, and S of conventional process materials.
Graph showing the effect of annealing temperature on tensile strength, Figure 3 (a
), Φ) are graphs showing the influence of cold rolled steel N content on the elongation and tensile strength of cold rolled steel annealed materials, and Figure 4 (a) shows the coil coldest point (O8) temperature and coil cross section. Figure 4 is a cross-sectional view of the coil showing the O8 temperature position of the coil. Figure 5 is a graph showing the relationship between annealing temperature, elongation Et, and %. Figure 6 is a cold-rolled steel plate. 7 is a graph comparing the influence of annealing temperature on the elongation El, with respect to the soaking time. FIG. 7 is a graph showing the variable distribution of the elongation Et, tensile strength T, S of the material processed according to the invention. Figure 8 (a) (b) Figure 4 (t)) Figure 5 Pregnancy degree Figure 6 Pregnancy degree procedure amendment August 16, 1981 1. Indication of the case 1988 Special Patent Application No. 114912 2, Title of the invention: Method for manufacturing cold rolled steel sheets 3, Relationship with the amended case Patent applicant (125) Kawasaki Steel Corporation■, "Authorized by Dan" on page 2, line 1 of the specification ” should be corrected to “accumulation.” 2. On page 6a, lines 8 to 6, ``This rolling reduction rate cannot be m-'' is corrected as follows.

Claims (1)

[Claims] 1. When heat-treating a steel plate that has been hot-rolled and cold-rolled and coiled in a batch annealing furnace, the steel composition of the steel plate, the thermal history of the extraction temperature, finishing temperature, and coiling temperature during hot rolling, and A method for manufacturing a cold rolled steel sheet, characterized in that an annealing temperature is determined by a relational expression determined based on statistical processing to determine the degree of influence of cold rolling conditions on material quality.