JP4580792B2 - Material analysis method, material stabilization method and material stabilization apparatus for metal materials - Google Patents

Description

  The present invention relates to a metal material analysis method suitable for stabilizing a material at a stage outputted from a processing step, for a metal material such as a plate material, a bar material, a wire rod, and an extruded material manufactured through a plurality of processing steps, and The present invention relates to a material stabilization method and a material stabilization device.

  2. Description of the Related Art Conventionally, for the purpose of improving fuel efficiency and reducing weight, structural materials such as automobile steel materials and aluminum alloys have been increased in strength.

  In the line that manufactures the steel sheet that is the material of the structural material, management points for monitoring processing conditions such as temperature, load, etc. are provided at important points, and processing detected by a plurality of sensors provided at each management point. The material has been conventionally stabilized by managing the conditions (see, for example, Patent Document 1).

  However, in many cases, structural material manufacturing equipment was originally designed on the assumption that relatively low-strength materials were manufactured, and when the production line was used as a high-strength material specification, a new high-strength material was added. Appropriate operating conditions must be found.

  In the case of changing the material specifications in this way, trial and error is performed until an appropriate operating condition is determined, and a great deal of time is consumed. In addition, when trial and error is performed on the production line, it is inevitable that products that do not satisfy the product specifications are manufactured, and non-standard products are disposed of and disposed of, resulting in high costs.

As described above, management of processing conditions has been performed conventionally and has reached a level that satisfies the specified product specifications, but in order to perform management with higher accuracy than that, appropriate operating conditions can be obtained through trial and error. The work of finding out is necessary. This is because there are various variable factors that affect the material quality of the product in the production line, and there is a complicated situation in which these variable factors influence each other and affect the material.
Japanese Patent No. 2509481

  For example, when a manufacturing experiment using an actual machine is performed by changing the conditions for one variable factor among a plurality of variable factors affecting the material of a product in three stages, if the other variable factors are constant, It is possible to grasp the influence of the material. However, in practice, other variable factors are not always constant.

  Further, the temperature and load of the steel plate measured by various sensors arranged on the production line include a measurement error because the steel plate travels at a high temperature and at a high speed in the heating process, for example. Therefore, a large number of measurement results are required to increase reliability, and the large number of measurement results also makes analysis difficult.

  The present invention has been made in consideration of the problems in the conventional material management method as described above, and the first object is from a lot of processing condition data detected from various sensors arranged in the processing process. It is to provide a material analysis method for a metal material that can efficiently identify a variable factor that affects the material and can be selected as an adjustment item in the processing conditions. The second purpose is to use the material analysis method, An object of the present invention is to provide a material stabilization method and a material stabilization device for stabilizing a material at a stage outputted from a processing step.

The present invention is a method for analyzing a metallic material is produced through a plurality of processing steps, based on the processing condition data detected by the detecting means disposed on the respective processing steps constitute a process condition Extract each factor and create a scatter plot of each factor and the material properties as ductility and / or strength obtained by sampling and testing at the stage output from each processing step . Divide the numerical value range into a certain interval for the factor and stratify it, calculate the average value of the material property value within that layer, and check whether there is a correlation between each factor and the material property based on the calculated average value The gist is a material analysis method for a metal material, in which a factor having a correlation is extracted and specified as a factor that affects the material.

  In the material analysis method of the present invention, as the above-mentioned factors, process factors such as temperature, load, stress, etc. measured by detection means arranged in each processing step, component factors such as product component analysis values, and the previous step Includes pre-process factors that are affected by.

The present invention correlates factors extracted by the material analysis method in a metal material stabilization method for stabilizing a material at a stage manufactured by each processing step for a metal material manufactured through a plurality of processing steps. The degree of correlation when the values are stored in descending order, entered into the process computer as adjustment items for the next processing condition, and after setting, a value exceeding the specified passability for ductility and / or strength is not obtained. The gist of the method is to stabilize the material of the metal material, which is input to the process computer as adjustment items in order from the highest to the lowest.

The present invention includes a detecting means for detecting a processing condition for each processing step for a metal material manufactured through a plurality of processing steps, and a material stabilizing device to which processing condition data detected by these detecting means is given. The material stabilizing device comprises a processing condition data storage unit for storing processing condition data detected by the detecting means, and processing conditions obtained from the processing condition data stored in the processing condition data storage unit. A scatter plot creation unit that creates a scatter plot of each factor being measured and material properties as ductility and / or strength obtained by sampling and testing at the stage output from each processing step, The hierarchization processing unit that divides the numerical value width into predetermined intervals for the factor, and calculates the average value of the material property values within the hierarchy, and based on the average value A correlation equation calculator for calculating the related expression, based on the correlation equation with a significance extracts the factor recognized correlated, in the next processing conditions the extracted factors as a factor affecting the material The gist of the present invention is a metal material stabilization device including a setting unit for setting an adjustment item.

In the material stabilization device of the present invention, the apparatus further includes an extraction factor storage unit that stores the extracted factors in descending order of correlation, and the setting unit sets ductility after setting the factor as an adjustment item in the next processing condition. In the case where a value equal to or higher than the pass value for which the strength is defined cannot be obtained, the adjustment items can be set in order from a factor having a high degree of correlation.

  The above factors in the material stabilization device are affected by process factors such as temperature, load, stress, etc. measured by detection means arranged in each processing step, component factors such as product component analysis values, and previous steps. Includes pre-process factors.

  According to the material analysis method of the present invention, it is possible to efficiently specify a factor that affects a material by statistically processing a number of previous factors output from the detection means arranged in the processing step.

  According to the material stabilization method of the present invention, factors that affect the material are input to the process computer as adjustment items in the processing conditions, and when a desired characteristic is not obtained after setting, the degree of correlation is high. Since the factors are input to the process computer as adjustment items in order from the factors, the trial period required to obtain the target material can be greatly shortened.

  According to the material stabilization device of the present invention, since the material at the stage of output from the processing process can be stabilized, it is possible to produce a metal material having no variation in characteristics, particularly suitable for a high-strength material. Metal materials can be manufactured.

  Hereinafter, the present invention will be described in detail based on the embodiments shown in the drawings.

  FIG. 1 shows a continuous galvanizing facility as one processing step in a line for manufacturing a steel plate as a metal material.

  In the figure, the surface of a steel plate 2 that is continuously unwound from the pay-out reel 1 is cleaned by an inlet side cleaning device 3 and sent to a preheating furnace 4, and then reduced by iron oxide on the surface of the steel plate in a heating furnace 5. Is done. Next, the steel sheet is immersed in a molten zinc pot 8 through a slow cooling furnace 6 and a regulating furnace 7.

  The steel plate that has passed through the zinc bath is pulled upward and alloyed in the alloying furnace 9, and the galvanized layer adheres firmly to the steel plate surface.

  Next, the galvanized steel sheet is cooled by the cooling device 10, dried, and then wound on the take-up reel 11.

  In such a galvanizing facility, the material of the steel sheet changes depending on each processing temperature before plating, during plating processing, and after plating.

  Specifically, the material of the steel sheet changes depending on the heating temperature in the heating furnace 5, the material also changes depending on the zinc bath temperature of the molten zinc pot 8, and the material also changes depending on the alloying temperature in the alloying furnace 9. To do.

  As a method for monitoring processing conditions in such a galvanizing facility, a scatter diagram as shown in FIG. 2 has been conventionally created.

  In the figure, the horizontal axis represents the heating temperature before entering the molten zinc pot 8, and the vertical axis represents ductility (hole expansibility λ).

  The steel sheet temperature is detected by a plurality of temperature sensors arranged at control points in the heating furnace 5 before the galvanizing treatment, and the ductility is sampled at the stage of being output from the galvanizing equipment. It is calculated | required by measuring the obtained steel plate.

  Therefore, by analyzing the scatter diagram, it is possible to analyze the correlation between the heating temperature as a variation factor and the ductility which is a metal material characteristic.

  Note that a large number of ductility data is plotted in the scatter diagram in order to increase the reliability of the measurement. This is because, for example, when measuring the surface temperature of a steel plate traveling at high speed without contact, it is inevitable that a measurement error is included between the measured temperature measured via the sensor and the actual steel plate temperature. It is practically impossible to obtain a correlation between these temperatures under constantly changing environmental conditions. In view of this, a technique of creating a scatter diagram by increasing the number of plots and grasping the trend as a whole has been conventionally employed.

  For example, when there is a clear correlation between the variation factor and the characteristics as in the scatter diagrams shown in FIGS. 3A and 3B, the characteristics of the material can be controlled by adjusting the variation factors. it can.

  In the scatter plots shown in Fig. 3 (a) and (b), there is a tendency for the whole plotted point to fall to the right, and the characteristic value is reduced by increasing the value of the variable factor (right on the X axis). (Down on the Y axis).

  In such a case, it is possible to identify the variation factor governing the material from the scatter diagram without applying the material analysis method of the present invention, and select the variation factor as an adjustment item for the processing condition to select the material. It is possible to control the characteristics.

  However, when a scatter diagram as shown in FIG. 3C is obtained, it is impossible to determine whether or not there is a correlation between the variation factor and the characteristic. According to the conventional analysis method, if there are singular points distributed in the vertical axis direction (points that deviate significantly compared to other plot points), the scatter diagram is widely dispersed in the vertical axis direction due to the existence of the singular points. It becomes impossible to judge whether or not there is a tendency.

  As described above, the present invention makes it possible to identify a variation factor that affects a material even when it is difficult to extract a variation factor by a simple analysis using a scatter diagram.

  FIG. 4 is a block diagram showing the basic configuration of the material analyzing apparatus of the present invention.

  In order to simplify the explanation, one process factor data, one component factor data, and one previous process factor data measured in each production line are representatively selected.

  In the processing process of the line that manufactures steel sheets, each manufacturing equipment such as continuous annealing furnace, continuous plating line, batch annealing furnace, hot rolling equipment, cold rolling equipment, extrusion equipment is arranged. A sensor for monitoring processing conditions such as temperature, load or stress (process factor) is provided for each management point.

  For example, in the surface treatment line, a plurality of temperature sensors Sa1 to San are provided at the management point in the reduction furnace 5 before the galvanizing treatment, and the heating temperature signals output from the plurality of temperature sensors Sa1 to San are sensors. Position information representing the position is added and given to the process factor data storage unit 20a of the material stabilizing device 20.

  The process factor data accumulation unit 20a has a position index corresponding to the position information, and sequentially accumulates the heating temperature data at the position index corresponding to the given position information.

  In addition, component factor data indicating the component analysis values of the product, for example, component concentrations such as C, Si, Mn, P, and S in the steel material are detected by the sensors Sb1 to Sbn and sequentially stored in the component factor data storage unit 20b.

  Further, pre-process factor data such as hot rolling is detected by the sensors Sc1 to Scn and sequentially stored in the pre-process factor data storage unit 20c.

  Each of the data storage units 20a, 20b, and 20c functions as a processing condition data storage unit that stores processing condition data.

  When each variation factor data is accumulated in the process factor data accumulating unit 20a, component factor data accumulating unit 20b, and previous process factor data accumulating unit 20c over a period preset as previous processing condition data, the scatter diagram creating unit 20d Creates a scatter plot for each control point. For example, a scatter diagram is created for the correlation between the heating temperature and ductility as shown in FIG. However, ductility shall be obtained as a result of testing the steel plate sampled in the stage output from a certain process process.

  When the scatter diagram is created by the scatter diagram creation unit 20d, the hierarchization processing unit 20e then divides the horizontal axis of the variation factor (heating temperature) shown in FIG.

  When hierarchizing, the number of hierarchies is determined so that a sufficient number of samples n can be secured in each hierarchy. Specifically, in this embodiment, 22 layers and the number of samples n are 5 or more. Next, the hierarchization processing unit 20e calculates an average value in each hierarchy.

  FIG. 5 is a hierarchy of the scatter diagram shown in FIG.

  In the figure, x indicates a plot point in the hierarchy, and A indicates an average value obtained by averaging the values of the plot points in each hierarchy. These average values are the expected values of the material at each level.

  6 to 8 show specific examples in which the factor data measured for each management point is hierarchized by the hierarchization processing unit 20e.

  In the graph showing the process factors in FIG. 6, the horizontal axis of each graph indicates the temperature, and the vertical axis indicates the intensity.

  At “temperature 1” measured at a certain management point, the strength tends to decrease as the temperature increases. “Temperature 2” measured at another management point also has a gentler slope than “Temperature 1”, but tends to decrease in strength as the temperature increases. Although the gradient for “temperature 5” is gentle, the strength tends to increase as the temperature increases. “Temperature 3”, “Temperature 4”, and “Temperature 6” have no correlation and are excluded from analysis.

  Moreover, in the graph showing the component factors in FIG. 7, the horizontal axis of each graph indicates the component, and the vertical axis indicates the intensity.

  Among the components of steel materials, “C” tends to increase in strength as its concentration increases, and “Mn” tends to increase in strength as the concentration increases, although the gradient is gentler than “C”. is there. “Si”, “P”, and “S” have no correlation and are excluded from analysis.

  Moreover, in the graph showing the pre-process factor of FIG. 8, the horizontal axis of each graph shows temperature, and the vertical axis | shaft has shown intensity | strength. None of the graphs of the pre-process factors have a correlation and are excluded from analysis.

  Next, the correlation equation calculation unit 20f of the material analysis device 20 obtains an expected straight line (regression straight line) based on the average value obtained from each of the hierarchized graphs.

  FIG. 9 shows an example in which the regression line B is obtained from the average value obtained in FIG.

  The slope θ of the regression line B shown in the figure is a sensitivity that affects the material of the steel sheet.

  The material variation factor extraction unit 20g extracts and extracts a variation factor for which a significant regression line is obtained from the scatter diagrams shown in FIGS. 6 to 8, that is, a variation factor with a recognized correlation. The variation factor is stored in the extraction factor storage unit 20h.

  The processing condition output unit 20i rearranges the variation factors stored in the extracted factor storage unit 20h from the ones having the larger slope θ of the regression line and gives priorities, and among the rearranged variation factors, the factors with the highest priority ( The fluctuation factor having a large inclination θ is output to the process computer 21 of the production line as a factor that affects the material of the steel sheet.

  The material variation factor extraction unit 20g, the extraction factor storage unit 20h, and the processing condition output unit 20i extract a factor in which a correlation is recognized, and use the extracted factor as a factor that affects the material to be adjusted in the next processing condition. Functions as a setting unit for setting to

  In the process computer 21, the variation factor output from the processing condition output unit 20 i is selected as an adjustment item in the processing condition and adjusted to adjust the current heating temperature by, for example, 10 ° C.

  When the adjustment does not change the material and the desired steel plate cannot be obtained, the process computer 21 gives a variation factor request command to the processing condition output unit 20i, and the processing condition output unit 20i has the second priority. The variation factor is read out and output to the process computer 21 again as a factor affecting the material of the steel plate.

  Until the desired material is obtained, the processing condition output unit 20i reads out the variation factors in order from the one with the highest priority, and gives it to the process computer 21.

  FIG. 10 is a graph showing the effect obtained by the material stabilizing device.

  The graph shown in the figure shows the index of ductility of the steel material, and the vertical axis shows the frequency.

  The steel before the material stabilization had its ductility (bar graph shown in white) varied in the range of 5.5 points (5.5%). However, if the material stabilization of the present invention is performed, the ductility ( The bar graph (shown in black) is within the range of 3.5 points (3.5%), and the material can be stabilized.

It is a lineblock diagram of the plating line to which the material stabilization method concerning the present invention is applied. It is a scatter diagram which plotted the characteristic to a factor. (a)-(c) is explanatory drawing which shows the correlation of the factor and characteristic in a scatter diagram. It is a block diagram which shows the structure of a material analyzer. It is the graph which hierarchized the scatter diagram shown in FIG. It is the graph which hierarchized the process factor. It is the graph which hierarchized the component factor. It is the graph which hierarchized the previous process factor. It is the graph which calculated | required the regression line from the hierarchized graph. It is a graph which shows a material stabilization effect.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Dispensing reel 2 Steel plate 3 Cleaning apparatus 4 Preheating furnace 5 Heating furnace 6 Cooling furnace 7 Conditioning furnace 8 Molten zinc pot 9 Alloying furnace 10 Cooling apparatus 11 Take-up reel 20 Material stabilization apparatus 20a Process factor data storage part 20b Component factor Data accumulation unit 20c Pre-process factor data accumulation unit 20d Scatter diagram creation unit 20e Hierarchization processing unit 20f Correlation equation calculation unit 20g Material variation factor extraction unit 20h Extraction factor storage unit 20i Processing condition output unit 21 Process computer

Claims (6)

In a method of analyzing a metal material manufactured through a plurality of processing steps,
Based on the processing condition data detected by the detection means are arranged in each processing step, we extract each factor constituting the processing conditions,
Create a scatter plot of each factor and material properties as ductility and / or strength obtained by sampling and testing at the stage output from each processing step ,
Divide the numerical values for the above factors in each scatterplot into predetermined intervals and stratify them,
Calculate the average value of the material properties within that hierarchy,
Based on the calculated average value, again determine the presence or absence of correlation between each factor and the material properties ,
A material analysis method for a metal material, characterized in that a factor with a correlation is extracted and specified as a factor that affects the material. As the agent, the temperature measured by said detection means are arranged in each processing step, load, process factors of stress, a step factor before the affected component factors component analysis values of the product, and the previous step The material analysis method of the metal material of Claim 1 contained. In the metal material stabilization method of stabilizing the material at the stage manufactured by each of the above-described processing steps for the metal material manufactured through a plurality of processing steps,
The factors extracted by the material analysis method according to claim 1 or 2 are stored in the descending order of correlation, and are input to the process computer as adjustment items in the next processing condition, and after setting, ductility and / or strength are defined. A method for stabilizing a material of a metal material, comprising: inputting a factor as an adjustment item to the process computer in order from a factor having a high degree of correlation when a value equal to or higher than a pass value is not obtained. A detection means for detecting a processing condition for each processing step for a metal material manufactured through a plurality of processing steps, and a material stabilization device to which processing condition data detected by these detection means is given,
The material stabilizing device includes a processing condition data storage unit that stores processing condition data detected by the detection unit,
Each factor constituting the processing condition obtained from the processing condition data stored in the processing condition data storage unit, and ductility and / or strength obtained by sampling and testing at the stage output from each processing step A scatter plot creation unit that creates a scatter plot with material properties as
A hierarchization processing unit that divides a numerical value into a predetermined interval and hierarchizes the above factors in each scatter diagram;
A correlation equation calculation unit that calculates an average value of material property values within the hierarchy and calculates a correlation equation based on the average value;
Based on the above significant correlation equation, a factor with a correlation is extracted, and a setting unit that sets the extracted factor as a factor affecting the material in an adjustment item in the next processing condition is provided. A material stabilization device for a metal material, characterized in that In addition to having an extracted factor storage unit that stores the extracted factors in descending order of correlation, the setting unit defines ductility and / or strength after setting the factor as an adjustment item in the next processing condition . The material stabilization device for a metal material according to claim 4, wherein when a value equal to or higher than the pass value is not obtained, the adjustment item is set in order from a factor having a high degree of correlation. As the agent, the temperature measured by said detection means are arranged in each processing step, load, process factors of stress, a step factor before the affected component factors component analysis values of the product, and the previous step The material stabilization apparatus of the metal material of Claim 4 or 5 contained.

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