Tối ưu hóa các thông số hoạt động của thiết bị nhiệt định hình bằng phương pháp taguchi

SÑ 45B (1) pdf , , 2020 © 20 Thành , nguyenkhoatrieuiuh edu vn 18 khóa , Minitab Abstract In this article, an investigation for optimization of process parameters for thickness uniformity in a thermoforming process utilizing Taguchi method with analysis of variance (ANOVA) was presented At first, five parameters, including setting temperature of ceramic heaters, distance between plastic sheet and the heaters, areal draw ratio, heating time, thickness of the plastic sheet were considered in the.

, , 2020 , nguyenkhoatrieu@iuh.edu.vn 18 khóa , Minitab Abstract In this article, an investigation for optimization of process parameters for thickness uniformity in a thermoforming process utilizing Taguchi method with analysis of variance (ANOVA) was presented At first, five parameters, including setting temperature of ceramic heaters, distance between plastic sheet and the heaters, areal draw ratio, heating time, thickness of the plastic sheet were considered in the initial approach towards optimization As a continuation of previous works, three levels of the processing condition for each parameter were established based on the recommended ranges Therefore, an L 18 Taguchi orthogonal design was selected As the next step, 18 experiments were carried out by utilizing the combination of process parameters based on this L 18 array Then, the S/N ratio and ANOVA were used to find the optimal levels to indicate the impact of the process parameters on the uniformity, showing that thickness of the plastic sheet and areal draw ratio played the most important roles, 34.90% and 32.48%, corespondingly A verification test was also performed to demonstrate the effectiveness of Taguchi method, resulting a 0.06 mm uniformity, better than any previous results Hence it can be clearly infered from this investigation that Taguchi method is a simple, sufficient tool to optimize such a traditional manufacturing process as thermoforming without using any complicated scientific researches or expensive software solutions Keywords Thermoforming, Optimization, Taguchi, ANOVA, Uniformity, S/N ratio, Minitab [1, 2] © 20 Thành không [1] [3] [4] [5] dùng mơ hình Ogden Arrudatrình [6] [7] [8] [9] -Livlin thành mơ hình - Mooney[10] [11] [12] [13] [14] nh [14] [15] [16] [17] [18] [19] - hóa [20] - © 20 Thành 2.1 10H8O4)n cao, -900 [21, 22] TT 10 11 12 13 g/cm3 g/cm3 MPa MPa % kJ/m2 C C C W/(m·K) 1/K kJ/kg·K - 1,370 1,445 2,800-3,100 55-75 50-150 3.6 75 260 170 0.24 7×10-5 1.0 0.16 1.5750 t) 2.2 Hình [23] [23] © 20 Thành [23] Trong k thu t này, v t li ck c c ép khuôn b ng cách di chuy n v t li ng th c áp d ng qua l thông éo s n ph m vào b m t bên ngồi khn S n ph c làm mát ti p xúc v i khuôn K thu t t o hình b ng c ch hình L i th c a t o hình b i t o hình b sâu kéo l c mà khơng có nh ng ch m ng q m c S n ph c ép khuôn v m i B i v y, t o hình cu i x uv dày t t nhi ng h p có th c v i m t khn âm 2.3 Taguchi c ng d ng r ng rãi l p quy ho ch th c nghi m [24] n c i thi t trình nghiên c u phát tri n, t o s n ph m có ch ng cao mà giá thành th p Nhà nghiên c a thí nghi m m ng tr c giao (Orthogonal Array) nh m gi m tham s c a thí nghi m v i s b trí thích h p u ki n thu n l i nh t c a tham s u c, b ng Các m ng tr c giao t o m t s cân b ng gi a thí nghi m t s Signal to Noise (S/N) hàm logarit c u mong mu n, th a mãn m c phân tích d t qu t ng ch giá tr trung bình (giá tr mong mu n) c a m u thu t ng ch giá tr không mong mu n Do v y t s cs d tính s sai l ch so v i giá tr mong mu n [25] T s Nh S/ N L S/ N t -t 10 log10 / n yi2 (1) -t 10 log10 1/ n 1/ yi2 (2) thí nghi m, yi k t qu thí nghi m th i 25] M ng tr c giao S thí nghi m L4 L8 L9 L12 L16 12 16 16 18 25 27 L18 L25 L27 © 20 Thành S thông s t 11 15 13 2m c S m c 3m c 4m c 5m c 11 15 13 L32 L36 L50 L54 L64 L81 32 32 36 36 50 54 64 64 81 31 10 23 16 12 26 63 21 40 31 11 1 63 12 13 11 25 21 40 Thi t k c a thí nghi m s d u qu ng kê khác B ng cách ch phù h p c a bi c l p khác nhau, s ng thí nghi c gi t mát b t k thơng tin gi m s thí nghi m M c tiêu c a m thi u s i xung quanh m c tiêu nâng cao ch ng Vi c s d ng h c t p k thu t cho phép k c nghiên c u c n th i gian cho quy ho ch th c nghi m phân tích k t qu i nh ng c i ti n công ngh thành d s d ng d ng Ph bi n nh t phân tích k thu t dùng ph n m m máy tính [18] 2.4 p Taguchi ch u ki n ràng bu c khuôn màu s c c a s n ph ng s n xu t cs d u ki n ràng bu c tính uv dày c a s n ph m nhi nh o hình, chép l i hình d ng c a c ki m tra ngo 3.1 giao trình bày hình Trong trình nhi nh hình, m t t m v t li u nh a nhi t d o (3) c k p vào khung k p g m t m k p (2) t m k i (9) T m nh a n nhi chuy n pha th y tinh nh nhi t n tr tr thành nên m m d o m nh a c di chuy n ti p xúc v i khuôn (16) b ng cách th công nh t (11 c g n khung máy (1) Ti p theo, t m nh a v n tr ng thái d o có th chép l i hình d ng c a khuôn b ng cách dùng chênh l ch áp su t nh bu ng hút (4) Trong trình t o hình, t m nh i chi u c n thi t c t m nh a ngu i Các tham s n ch ng c a trình nhi t nh hình [18]: (1) Các thông s n nhi g m nhi gia nhi t th i gian gia nhi t; (2) Các thông s n v t li u g m lo i v t li dày t m; (3) Các thông s n áp su t g m áp su t chân không, áp su tr ; (4) Các thông s n khuôn g m lo i khuôn, t s kéo, chày ép, t di chuy n kho ng cách di chuy n Qua nghiên c y [26] nh có kh tr ng vi c n ch m c a s n ph m nhi u G m nhi c a nhi n tr (oC), kho ng cách gia nhi t (mm), th i gian gia nhi t (s), t s kéo Ra (-), dày c a t m v t li u (mm) © 20 Thành thơng Sai hình - Sai ch n ph m vi tham s t vài th nghi m th nghi nh ph m vi c a giá tr tham s mà s n ph m có th c t o hình thành cơng Các th nghi m c th c hi n d a kinh nghi m c a chuyên gia, tham kh o thông s c a thi t b hi n có th c nghi m th sai n này, t m nh c © 20 Thành s d n s n ph nghiên c u ng t t u c u, in hình khn hồn tồn, hình 3, d ng l i chuy n sang b c ho ng Các thông s c trình bày b ng TT 300 27 s 40 mm B ng li t kê y u t m y ut C c ch n thí nghi m TT A B 290 300 310 38 40 42 mm C 26 27 28 s D 1.5 2.5 - E 0.2 0.25 0.3 mm cách © 20 C Thành 10 (a) (b) Hình T [26] Vi c xây d ng m ng tr c giao ph thu c vào s y u t s m c c a t ng y u t [27] này, v i y u t , m i y u t m c, m ng tr c giao có c u trúc L18 ng Hình trình bày mơ hình 3D c a thi t b nhi © 20 Thành ng h p c xây d ng b ng ph n m m SolidWorks® 11 Hình [26] 5: C STN 10 11 12 13 14 15 16 17 18 A 1 2 3 1 2 3 B 3 3 3 C 3 3 2 3 Trung bình Trong tính tốn D 3 1 3 2 E 3 2 1 3 18 0.073 0.1 0.18667 0.11 0.12667 0.08 0.12333 0.09 0.16333 0.11333 0.07667 0.08667 0.09 0.07 0.13667 0.13667 0.09667 0.09333 1.953 0.1085 , MSD 0.00533 0.01 0.03484 0.0121 0.01604 0.0064 0.01521 0.0081 0.02668 0.01284 0.00588 0.00751 0.0081 0.0049 0.01868 0.01868 0.00934 0.00871 0.22935 S/N 22.73354 20 14.57866 19.17215 17.94675 21.9382 18.17839 20.91515 15.7385 18.91285 22.30787 21.24296 20.91515 23.09804 17.28675 17.28675 20.29447 20.59926 19.61919 MSD [27] © 20 Thành 12 3.2 K t qu S/N nhi h tính tốn S/N (signal/noise) M c ch c bi u di n b -t 6: a báo t A B C D E 19.96265 19.53314 19.58888 21.47588 21.33991 20.05951 20.76038 19.81375 19.31729 19.58680 18.83542 18.56406 19.45494 18.06440 17.93086 1.22409 2.19632 0.35881 3.41149 3.40905 10.59976 11.55 20.72 3.39 32.18 32.16 100 58.85757 Hình 3.3 ng K t qu phân tích ANOVA (0,01,2,7), © 20 Thành có ý 13 7: 3.4 S f V F F(0.01,2,7) P% A 0.00072878 0.000364389 1.43315 9.54658 4.18 B 0.00290915 0.001454574 5.72089 9.54658 16.67 C 0.0002747 0.000137352 0.54021 9.54658 1.57 D 0.00566804 0.002834019 11.14629 9.54658 32.48 E 0.00609026 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