Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Adaptive adjustment method of steel production

An adaptive adjustment and steel technology, applied in data processing applications, instruments, manufacturing computing systems, etc., can solve the problems of not being able to achieve a good match between the production rhythm and the demand rhythm, and achieve the effect of full utilization

Inactive Publication Date: 2013-06-05
上海宝钢钢材贸易有限公司
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In the prior art, this adjustment method is usually a simple regression analysis or based on empirical data. These analysis methods have their own shortcomings and point out that they cannot make a good match between the production rhythm and the demand rhythm.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Adaptive adjustment method of steel production
  • Adaptive adjustment method of steel production

Examples

Experimental program
Comparison scheme
Effect test

no. 1 example

[0083] In step a), the hot-dip galvanized sheet with a specification of 0.70mm×1170mm that needs to be predicted is selected, and the historical production data of the hot-dip galvanized sheet with a specification of 0.70mm×1170mm is obtained.

[0084] In step b), the actual production data of this steel product for each month in 4 consecutive years (2008-2011) including 2011 is obtained.

[0085] In step c), number the actual purchase volume data for each month of the 4 years a ij , where a 11 = 1460, a 12 = 1580, a 13 = 1980, ...; a 21 =1550,a 22 = 1610, a 23 = 1970, ...; a 31 =1430,a 32 = 1520, a 33 = 1830, ...; a 41 = 1410, a 42 = 1670, a 43=1870, . . . Among them, i=1, 2, 3, 4, representing the first year (2008) and the second year (2009); j=1, 2, ..., 12, representing 1 to 12 months in each year respectively) .

[0086] In step d), let j=1.

[0087] In step e), using a 11 、a 21 、a 31 、a 41 These 4 data are subjected to polynomial fitting to obtain the ...

no. 2 example

[0098] In step a), the hot-dip galvanized sheet with a specification of 0.70mm×1580mm that needs to be forecasted is selected, and the historical production data of the hot-dip galvanized sheet with a specification of 0.70mm×1580mm is obtained.

[0099] In step b), the actual production data of this steel product for each month in 4 consecutive years (2008-2011) including 2011 is obtained.

[0100] In step c), number the actual purchase volume data for each month of the 4 years a ij , where a 11 =817,a 12 =845,a 13 =885,...;a 21 =822,a 22 =850,a 23 = 896, ...; a 31 =840,a 32 =864,a 33 = 904, ...; a 41 =853,a 42 =869,a 43 =912, . . . Among them, i=1, 2, 3, 4, representing the first year (2008) and the second year (2009); j=1, 2, ..., 12, representing 1 to 12 months in each year respectively) .

[0101] In step d), let j=1.

[0102] In step e), using a 11 、a 21 、a 31 、a 41 These 4 data are subjected to polynomial fitting to obtain the single-month longitudinal...

no. 3 example

[0113] In step a), the hot-dip galvanized sheet with a specification of 0.70 mm × 1600 mm is selected, and the historical production data of the hot-dip galvanized sheet with a specification of 0.70 mm × 1600 mm is obtained.

[0114] In step b), the actual production data of this steel product for each month in 4 consecutive years (2008-2011) including 2011 is obtained.

[0115] In step c), number the actual purchase volume data for each month of the 4 years a ij , where a 11 =225,a 12 =232,a 13 = 263, ...; a 21 =228,a 22 =235,a 23 = 259, ...; a 31 =232,a 32 =245,a 33 = 271, ...; a 41 =231,a 42 =238,a 43 =269, . . . Among them, i=1, 2, 3, 4, representing the first year (2008) and the second year (2009); j=1, 2, ..., 12, representing 1 to 12 months in each year respectively) .

[0116] In step d), let j=1.

[0117] In step e), using a 11 、a 21 、a 31 、a 41 These 4 data are subjected to polynomial fitting to obtain the single-month longitudinal model V 1 (x)=-...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an adaptive adjustment method of steel production. The adaptive adjustment method comprises: selecting specification and variety of steel, and calling historical production data of the steel with the selected specification and variety; obtaining a first data group from the historical production data, wherein the first data group comprises a plurality of continuous long cycles, each long cycle comprises a plurality of continuous short cycles, each short cycle in each long cycle is numbered, and the corresponding short cycles in different long cycles have related numbers; calculating a first production model based on the first data group; selecting a pointed time point; obtaining a second data group from the historical production data, wherein the second data group comprises a plurality of continuous short cycles before the pointed time point; calculating a second production model based on the second data group; calculating the forecasting production data of the pointed time point according to the first production model and the second production module, and performing adaptive adjusting on production of steel according to the forecasting production data.

Description

technical field [0001] The invention relates to the technical field of automatic steel production, in particular to an adaptive adjustment method for steel production. Background technique [0002] The automatic continuous production of steel is an important factor to improve the production efficiency of steel enterprises. The production speed of steel is inseparable from the downstream demand of iron and steel enterprises. When the demand of downstream enterprises is strong, they need to increase production to meet the demand, and when the demand is insufficient, they need to reduce production in time to reduce inventory pressure. [0003] Taking steel for automobiles as an example, with the rapid development of the automobile consumer market, the demand for steel by automobile manufacturers continues to increase. The competition for the market share of automobile sheets among various iron and steel production enterprises is also more intense. While continuously improving ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/08G06Q50/04
CPCY02P90/30
Inventor 张海峰
Owner 上海宝钢钢材贸易有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com