МЕТОД ОЦЕНКИ ВЛИЯНИЯ ПРОЦЕССА ТЕРМИЧЕСКОЙ ОБРАБОТКИ НА ЭФФЕКТИВНОСТЬ ОТРАСЛИ ПРОИЗВОДСТВА СТАЛИ

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[17], -, , - . - , - . - 1 , (baranov_anton@inbox.ru, 8(950)45-44-715). 2 , , (fayzrakhmanov@gmail.com, 8(912)88-100-86). </p></li><li><p> . 40 </p><p> 204 </p><p> , - . </p><p> - - . - , . , , , - . , , , - - . - , -, - [3, 15]. </p><p> , -, /, ., - , . </p><p>, , , - : , , , , .. , - - . </p></li><li><p> - </p><p> 205 </p><p> - , . - , ( ). - . -, . - , . , , MatLab . </p><p> - -, (SaaS, Software-as-a-Service). - ForecasterOnline.com , ( ). </p><p> 2011 [5], 4/3 : , , , , , , (. 1). </p><p> - 2000 2011 - , : , / . . , , -, : -</p></li><li><p> . 40 </p><p> 206 </p><p> , . </p><p> . 1. , </p><p>2. </p><p> : (Weighted Moving Average), (Double Exponential Smoothing), (Polynomial Regression). </p><p> . , . : </p><p>(1) k</p><p>ktkktkktkktkt www</p><p>xwxwxwxwS</p><p>21</p><p>1111 </p></li><li><p> - </p><p> 207 </p><p>(2) </p><p> m</p><p>mii</p><p>m</p><p>miiti</p><p>t</p><p>w</p><p>xwS , k = 2m + 1; t = m +1, , n m. </p><p> wi , - . </p><p> - - . - -, , . 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[6] </p><p> . 3. </p><p> , - , - 2. </p><p> 2. \ -</p><p> M[X] D[X] m </p><p> 4726 1830 4841 22808 2822 24315 </p></li><li><p> . 40 </p><p> 212 </p><p> \ - </p><p>M[X] D[X] m </p><p> 18698 6760 20530 635 22943 11402 860 1729 1003 28166 3693 29372 </p><p> 2084 2827 2717 </p><p>3.3. </p><p> 2008 2012 [4], 2014 - -; 3, . 4. </p><p> 3. </p><p>20.07.08 1035 20.10.10 475 20.10.08 280 20.01.11 540 20.01.09 325 20.04.11 520 20.04.09 315 20.07.11 590 20.07.09 351 20.10.11 530 20.10.09 339 20.01.12 509 20.01.10 420 20.04.12 476 20.04.10 530 20.07.12 370 20.07.10 400 </p></li><li><p> - </p><p> 213 </p><p> . 4. </p><p> - , ( , ). </p><p> - 4. </p><p> 4. </p><p> \ </p><p>, M[X] D[X] m </p><p> - 444 133 415 </p><p> - </p><p> 312 352 475 0,4 0,3 </p><p> -</p><p> ( 2012 ), , , -</p></li><li><p> . 40 </p><p> 214 </p><p> , , - . </p><p>5. </p><p> - (crude steel, ), - (. 5). </p><p> . 5. </p><p> ( ) - , , . , . </p><p> , , , , , , . , , , -. </p><p> , , , </p></li><li><p> - </p><p> 215 </p><p> , , , [12, 13] , ACEAH 45%. - 2008 2012 , . 6. </p><p> , - , . : ; ; - - . </p><p> . 6. </p></li><li><p> . 40 </p><p> 216 </p><p> (10), (. $), . (10) )())((),,,,( occooocc pPNXVtptNXPVfK ww , V , ; NX , ; Pw 1 , $; t , , %; p , $. </p><p> ( t p) 2010 , , . 7. </p><p> . 7. 2010 </p><p> K (. 8) , , - ( 10 90%). </p></li><li><p> - </p><p> 217 </p><p> . 8. </p><p> , 50% K , , - . </p><p>6. </p><p> . </p><p> - : - MAD, MAPE, MSE. - 56. </p></li><li><p> . 40 </p><p> 218 </p><p> 5. / / - \ </p><p>MAD, MAPE, % MSE, </p><p> 2556/1388 6/64 3541/1884 2270/1100 3/5 3026/1579 6110/6596 8/55 8325/8174 10512/20393 3/2329 12524/26264 1235/1458 3/96 1843/1972 4950/1827 5/5 7321/2944 </p><p> 1513/2665 3/777 2121/3271 </p><p> 6. \ MAD, MAPE, % MSE, </p><p> 71 16 91 </p><p> - 271 71 377 </p><p> , , , , - . , - : 3%; 5%; 16%. , K - 8%. </p><p> , - , , [2, 8] </p></li><li><p> - </p><p> 219 </p><p>1. .. . - . , 2005. 56 . </p><p>2. .. - // : . . . , 2011. . 159161. </p><p>3. .. -. .: -, 2002. 427 . </p><p>4. [- ]. URL: http://www.lme.com ( - 14.05.2012). </p><p>5. [- ]. URL: http://www.worldsteel.org ( - 20.04.2012). </p><p>6. .. . . : , 2006. </p><p>7. .. . -. : , 2008. </p><p>8. BARANOV A.A. Analytical review of software products for modeling process of heat treatment // XXI : . . . VII . .-. ., , 2011. 2. . 34. </p><p>9. HOLT C.C. Forecasting trends and seasonals by exponentially weighted moving averages // O.N.R. Memorandum, Carnegie Inst. of Technology. 1957. 52. P. 510. </p><p>10. http://businessforecast.by/partners/publication/402 ( - 12.05.2012). </p><p>11. http://forecasteronline.com/index.php ( 25.04.2012). </p><p>12. http://www.metalika.ua/news/356192 ( 16.05.2012). </p></li><li><p> . 40 </p><p> 220 </p><p>13. http://www.metalinfo.ru/ru/news/56346 ( 16.05.2012). </p><p>14. http://www.planetcalc.ru/594 ( 20.05.2012). 15. http://www.raexpert.ru/researches/metallurgy ( </p><p>22.05.2012). 16. http://scm-book.ru/HoltWinters ( 12.05.2012). 17. http://www.srinest.com/book_754_chapter_83_18.1._CHernaja_</p><p>metallurgija.html ( 11.05.2012). 18. SRIVASTAVA R. Polynomial Regression // Technical report, </p><p>Indian Agricultural Statistics Research Institute, 2004. METHOD TO ESTIMATE INFLUENCE OF STEEL HEAT TREATMENT TECHNOLOGY LEVEL ON EFFICIENCY OF STEELMAKING INDUSTRY Anton Baranov, Perm National Research Polytechnic University, Perm, Postgraduate (baranov_anton@inbox.ru, 8(950)45-44-715). Rustam Fayzrakhmanov, Perm National Research Polytechnic University, Perm, Doctor of Science, professor (fayz-rakhmanov@gmail.com, 8(912)88-100-86). Abstract: We propose a formal method to forecast a complex of parameters describing heat treatment technology and perform analysis of technology parameters dynamics for steelmaking indus-tries worldwide. Than we investigate influence of steel heat treat-ment technology level on efficiency of steelmaking industry. Keywords: prognostic evaluation method, production indicators, heat treatment. </p><p> . . </p></li></ul>