تحسين وكريم وخالدة70- 79 Al-Khwarizmi Engineering Journal, Vo Prediction of Process Parameters Roughness Using Tahseen Fadhil Ab Khalida kadhim Mansor *,**,***Department of Production Engineering and Metallurgy / University of Technology (Received https://doi.org/10.22153/kej.2019.10.002 Abstract Multipoint forming process is an engineering concept which means that the working surface of the punch and produced as hemispherical ends of individual active elements (called pins), where each vertically displaced using a geometrically reconfigurable die tools saved precious production time. Also expenses are saved. But the most important aspects of using such types of equipment This paper presents an experimental investigation of the effect of thickness and forming speed that affect the surface integrity for brass (Cu Zn 65 This paper focuses on the development of predict Variance (ANOVA), surface roughness has b rubber thickness and forming speed have been considered as model parameters. The mean surface roughness (Ra) is used as response parameter to predict the surface roughness of multipoin generated, compared and evaluated to the proposed models obtained from experiments. Taguchi algorithm was used to predict the forming parameters (blank holder, rubber thickness and forming speed) on product roughness in forming process of Brass (Cu Zn 65 was used to find the optimum parameters that Keywords: Analysis of variance (ANOVA), Forming Parameters Roughness. 1. Introduction Multipoint forming (MPF) is a modern manufacturing technology for three sheet metal forming process. The idea of die of various shapes has been always attractive as a means of reduction costs of die design, since it would permit design iterations to be rapid and nearly cost Free [1]. The effecting method for manufacturing metal product of 3D complex shapes is Khwarizmi Engineering Journal, Vol. 15, No. 2, June , (2019) P.P. 70- 79 Process Parameters That Affecting on Roughness in Multi-Point Forming Process Using ANOVA Algorithm l Abbas* Karem MohsenYounis Khalida kadhim Mansor *** Department of Production Engineering and Metallurgy / University of Technology *Email: tfalani@yahoo.com **Email: karim_mohsen @yahoo.com ***Email: kh_ak07@ yahoo.com (Received 22 June 2018; accepted 18 October 2018) https://doi.org/10.22153/kej.2019.10.002 Multipoint forming process is an engineering concept which means that the working surface of the punch and produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. an experimental investigation of the effect of three main parameters which are blank holder, rubber nd forming speed that affect the surface integrity for brass (Cu Zn 65-35) with 0.71 mm thickness. on the development of prediction models for estimation of the product quality. Using urface roughness has been modeled. In the development of this predictive model, blank holder, rubber thickness and forming speed have been considered as model parameters. The mean surface roughness (Ra) is used as response parameter to predict the surface roughness of multipoint forming parts. The data required has been to the proposed models obtained from experiments. used to predict the forming parameters (blank holder, rubber thickness and forming speed) ness in forming process of Brass (Cu Zn 65-35) based on orthogonal array of L9 and used to find the optimum parameters that have effect on the product quality. Analysis of variance (ANOVA), Forming Parameters, Multipoint forming process (MPF, Surface forming (MPF) is a modern manufacturing technology for three-dimensional . The idea of forming always attractive as die design, since it to be rapid and manufacturing sheet complex shapes is sheet metal forming process. This use a matched solid die set that forms a cavity into which the sheet is displaced. sets may be needed to form a sheet metal parts. this process, to produce different shaped that must be required different dies. The design and manufacturing of punch and dies is work and must rely on the experience of and workers. The idea of shape has always been attractive as a means of reducing die design costs [ Al-Khwarizmi Engineering Journal on Surface Point Forming Process Karem MohsenYounis ** Department of Production Engineering and Metallurgy / University of Technology Multipoint forming process is an engineering concept which means that the working surface of the punch and die is pin can be independently, everal different products can be made without changing the manufacturing of very expensive rigid dies is reduced, and a lot of the flexibility of the tooling. main parameters which are blank holder, rubber 35) with 0.71 mm thickness. the product quality. Using Analysis of een modeled. In the development of this predictive model, blank holder, rubber thickness and forming speed have been considered as model parameters. The mean surface roughness (Ra) is t forming parts. The data required has been used to predict the forming parameters (blank holder, rubber thickness and forming speed) 35) based on orthogonal array of L9 and finally ANOVA forming process (MPF, Surface . This traditional process a matched solid die set that forms a cavity into which the sheet is displaced. Sometimes, several to form a sheet metal parts. In different shaped of parts different dies. The design punch and dies is a costly work and must rely on the experience of designers of die forming of variable been attractive as a means of [2]. Tahseen Fadhil Abbas Al A schematic of a multipoint forming with a blank-holder is shown in figure (1) Fig. 1. Principle of multi point forming process [1]. A series of experiment have been carried out in design of experiments to investigate the effect of forming parameters such as blank Holder, rubber thickness and forming speed on surface roughness. Linfa Peng et al (2006) [3] design the contact surface between the workpiece and the surfaces of the blank holder. Two designs were developed to transition surface one is a bridge surface extension, and the flexible surface extension. These two approaches that used continuity type (G2) to transition the design surface with both reliable and effective. In this transition design surface, the Applications gave manufactured the forming product with high quality products in (MPF). Yajie Liu et al (2016) [4] designed an original rigid flexible blank holder (FBH) device. Models of Finite element analysis (FBH) are established without used of blank holder (NBH); the simulation is applying with different BHF in forming spherical surface parts and then acquired the optimal BHF. The results indicate that FBH forming process ca effectively wrinkling defects, thickness distribution is more reasonable, sheet metal flow is more uniform, and distribute uniformly and the stress and strain are minimum. Babak Beglarzadeh (2017) [5] investigate a flexible method for forming a metal, multi- is used to form initial size of 300 × 300 mm using aluminum alloy sheet 2024. Finite elements were simulated through ABAQUS/EXPLICIT 6.14.1. Through, increasing of elastic layer (cushion) hardness, the minimum required of elastic layer proliferates. Furthermore, (BHF) increment has a direct relation with the enhancement in hardness of polyurethane layer. The multipoint forming process of aluminum Al-Khwarizmi Engineering Journal, Vol. 15, No. 71 A schematic of a multipoint forming process holder is shown in figure (1). Principle of multi point forming process [1]. A series of experiment have been carried out in design of experiments to investigate the effect of forming parameters such as blank Holder, rubber thickness and forming speed on surface roughness. Linfa Peng et al (2006) [3] design the een the workpiece and the surfaces of the blank holder. Two designs were developed to transition surface one is a bridge flexible surface extension. These two approaches that used continuity type (G2) to transition the design ace with both reliable and effective. In this transition design surface, the Applications gave manufactured the forming product with high- quality products in (MPF). Yajie Liu et al (2016) [4] designed an original rigid flexible blank holder Models of Finite element analysis (FBH) are established without used of blank holder (NBH); the simulation is applying with different BHF in forming spherical surface parts and then acquired the optimal BHF. The results indicate that FBH forming process can be release effectively wrinkling defects, thickness distribution is more reasonable, sheet metal flow is more uniform, and distribute uniformly and the stress and strain are minimum. Babak Beglarzadeh (2017) [5] investigate a flexible -point forming is used to form initial size of 300 × 300 mm using aluminum alloy sheet 2024. Finite elements were simulated through ABAQUS/EXPLICIT 6.14.1. Through, increasing of elastic layer (cushion) hardness, the minimum required a thickness of elastic layer proliferates. Furthermore, (BHF) increment has a direct relation with the enhancement in hardness of polyurethane layer. The multipoint forming process of aluminum sheet are performed, and the comparisons of a forming process between simulation functions and experimental parts are applied, which establish that the aluminum products have the best shape accuracy and surface accuracy. A.A. Tolipov et al (2017) [6] effect of process variable such as the force blank holder, elastic cushion thickness, radius of curvature and coefficient of friction on the performance of forming parts in a flexible multi point process the research was carried out a multipoint forming process using a blank holder in order to study the effects of the, dimpling, wrinkling forming force and reduction of thickness to determine the optimum value of these variables are performed to simulate the multipoint forming of hemispherical shapes using finite element modeling. The effects of pr variables on maximum deviation from thickness reduction, the target shape and wrinkling were estimate using the response surface methodology. Tahseen Fadhel Abaas et al (2018) [7] investigated the achievement of a multipoint die with tools in square matrix and suitable blank holder. Each pin in the punch holder can be a significant moved according to the die high and at different load that applied with spring with respect to spring stiffness. The results shows the reduction in setting time with respe point incremental forming process that lead to (90%). and also show during the forming process, the deformation of the interpolator formed work piece can induce a shape error and the blank holder can eliminate or reduce dimples in work-piece. They predict the optimum value of some process variable that effect on surface roughness and estimate the empirical equation that present the response value with respect to process variables. 2. Experimental Work 2.1. Material and Process Samples of brass alloy (Cu Zn 65 thickness (0.7 mm) were used to perform the experiments (9-samples). The geometry of forming tool that used in this work is shown in figure (2). While the geometry of final product illustrated in figure (3). The experimental work was applied using oil lubricant on a C-tek three machine with rotational speed of (6000 rpm), feed of (10 m/min) to manufacturing the hem shape used as the a half Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) sheet are performed, and the comparisons of a ss between simulation functions and experimental parts are applied, which establish that the aluminum products have the best shape accuracy and surface accuracy. A.A. Tolipov et al (2017) [6] investigated the effect of process variable such as the force of blank holder, elastic cushion thickness, radius of curvature and coefficient of friction on the performance of forming parts in a flexible multi- point process the research was carried out a multipoint forming process using a blank holder udy the effects of the, dimpling, wrinkling forming force and reduction of thickness to determine the optimum value of these variables are performed to simulate the multipoint forming of hemispherical shapes using finite element modeling. The effects of process variables on maximum deviation from thickness reduction, the target shape and wrinkling were estimate using the response surface methodology. Tahseen Fadhel Abaas et al (2018) [7] investigated the achievement of a multipoint die matrix and suitable blank holder. Each pin in the punch holder can be a significant moved according to the die high and at different load that applied with spring with respect to spring stiffness. The results shows the reduction in setting time with respect to traditional single point incremental forming process that lead to (90%). and also show during the forming process, the deformation of the interpolator formed work- piece can induce a shape error and the blank holder can eliminate or reduce dimples in the They predict the optimum value of some process variable that effect on surface roughness and estimate the empirical equation that present the response value with respect to process Experimental Work Material and Process Samples of brass alloy (Cu Zn 65-35) with thickness (0.7 mm) were used to perform the samples). The geometry of forming tool that used in this work is shown in figure (2). While the geometry of final product perimental work was applied using oil tek three-axis (KM-80D) CNC machine with rotational speed of (6000 rpm), feed of (10 m/min) to manufacturing the hem-spherical shape used as the a half-die. The mechanical Tahseen Fadhil Abbas Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) 72 properties and chemical composition of brass (65- 35) is illustrated in tables (1 & 2). The shape of forming tools that used in this work is square tool steel (15x15x80 mm) while the tip of tool is hem- spherical shape. Three types of blank holder was with different size and shape that illustrated in Figure (4) while multi-point forming die and the final nine products are illustrated in figure (5). Table 1, Mechanical properties for Brass sheet (Iso- Cu Zn 65-35 426/1). Material Tensile Strength MPa Modulus of Elasticity GPa Poissons Ratio Elongation % on 50 mm G.L. Vickers Hardness HV Iso 65/35 Brass ’O’ Exp. 230 - 0.375 31.5 100≤ Cu Zn 35 426/1 Iso 230 110 0.33 56 90≤ Table 2, Chemical composition of Brass sheet (Iso- Cu Zn 65-35 426/1). Material Zn% Pb% Sn% P% Mn% Fe% Ni% Si% Al% Cu% Brass Exp. 35.23 0.007 0.001 0.007 0.000 0.021 0.001 0.001 0.002 64.7 Iso 35.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 65.0 Forming Tool Fig. 2. Geometry of the forming tool (all dimension in (mm)). Tahseen Fadhil Abbas Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) 73 Fig. 3. Geometry of part and CNC-part program. (all dimension in (mm)). (a) (b) (c) Fig. 4. Types of blank holder that used in this work. Tahseen Fadhil Abbas Al Fig. 5. The experimental setup and nine The measurement device that used in this work is surf tester (Mahr pocket surf test) (6). This device was used to measure the surface roughness of the formed surface, the forming surface was measured after cut off to simplest the measurement procedures at three different positions and Arithmetic mean surface roughness (Ra) are used as output parameters to surface quality of multipoint forming Fig. 6. Surface roughness measurement device 2.2. Plan of Experiments An important stage in response surface model generation by ANOVA is the planning of experiments. The parameters which has a Al-Khwarizmi Engineering Journal, Vol. 15, No. 74 The experimental setup and nine-samples. The measurement device that used in this work (Mahr pocket surf test) device, figure (6). This device was used to measure the surface , the forming surface was measured after cut off to simplest the procedures at three different positions and Arithmetic mean surface roughness to evaluate the forming product. Surface roughness measurement device. An important stage in response surface model generation by ANOVA is the planning of experiments. The parameters which has a significant influence on surface quality was identified they by blank holder types, cushion thickness and forming speed in multi forming process. Figure (7) present the problem solving and the analysis of data. Fig. 7. define the research problem and their analysis. Uses a special design of orthogonal arrays with a small number of experiments Taguchi method to study the entire parameter space. The methodology of Taguchi for three factors (blank holder, elastic cushion thickness and forming speed) at three levels for each is used to applied the experiments. To define the nine trial conditions, is used the degrees of freedom required for the study is six and Taguchi orthogonal array. The levels and process parameters are illustrated in table (3). The average response and Replicated twice values for each of the process designs of nine trials are used. Table (4) illustrated the present work and the test results, and figures (8, 9 and 10) represent the relationship between experimental data. Table 3, levels and parameters Parameters Unit Blank holder type (B) - Rubber thickness(R ) mm Speed (S) mm/min Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) significant influence on surface quality was identified they by blank holder types, cushion thickness and forming speed in multi-point forming process. Figure (7) present the problem solving and the analysis of data. define the research problem and their Uses a special design of orthogonal arrays with a small number of experiments Taguchi method to re parameter space. The methodology of Taguchi for three factors (blank holder, elastic cushion thickness and forming speed) at three levels for each is used to applied the experiments. To define the nine trial conditions, is used the degrees of freedom quired for the study is six and Taguchi’s (L9) orthogonal array. The levels and process parameters are illustrated in table (3). The average response and Replicated twice values for each of the process designs of nine trials are used. Table the present work and the test results, and figures (8, 9 and 10) represent the relationship between experimental data. Lev.1 Lev.2 Lev. 3 1 2 3 2 4 6 mm/min 2 5 10 Tahseen Fadhil Abbas Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) 75 Table 4, Taguchi’s L9 orthogonal array and response value Parameters Response value Exp. No blank holder type Rubber thickness mm Speed mm/min Surface roughness µm Ra1 Ra2 Ra3 Rav 1 1 1 1 1.11 1.13 1.15 1.13 2 1 2 2 1.30 1.27 1.27 1.28 3 1 3 3 1.02 1.09 1.06 1.0567 4 2 1 2 0.50 0.58 0.57 0.55 5 2 2 3 0.99 1.01 1.01 1.0033 6 2 3 1 1.80 1.71 1.82 1.7767 7 3 1 3 0.80 0.84 0.79 0.81 8 3 2 1 0.55 0.54 0.54 0.5433 9 3 3 2 0.81 0.74 0.77 0.7733 Fig. 8. The relationship of average roughness with respect to process parameters. Fig. 9. The relationship of mean of mean for each process variable. 2 4 0 5. 1.0 1 6 2 3 1.5 ughnessor egarevA redloh knalb t rebbu nickr essh uuuurrrr ffff aaaacccc eeee PPPPllllooootttt ooooffff AAAAvvvv eeeerrrr aaaaggggeeee rrrr oooouuuugggghhhhnnnneeeessss ssss &&&& bbbbllllaaaannnnkkkk hhhhoooollllddddeeeerrrr ;;;;SSSS rrrr uuuubbbbbbbbeeeerrrr tttt hhhhiiiicccc kkkk nnnneeeessss ssss 2 5 0.5 0.1 2 10 4 6 1.5 ughnessor egarevA rebbur t ssenkich dpees uuuurrrr ffff aaaacccc eeee PPPPllllooootttt ooooffff AAAAvvvv eeeerrrr aaaaggggeeee rrrr oooouuuuSSSS hhhhnnnneeeessss ssss &&&& rrrr uuuubbbbbbbbeeeerrrr tttt hhhhiiiicccc kkkk nnnneeeessss ssss ;;;; ssss ppppeeeeeeeeddddgggg 2 5 .50 1.0 1 01 2 3 5.1 Ave age rr ssenhguo redloh kblan pees d uuuurrrr ffff aaaacccc eeee PPPPllllooootttt ooooffff AAAAvvvv eeeerrrr aaaaggggeeee rrrr oooouuuugggghhhhnnnneeeessss ssss &&&& bbbbllllaaaannnnkkkk hhhhoooollllddddeeeerrrr ;;;; ssss ppppeeeeSSSS ddddeeee 321 1.2 1.1 1.0 0.9 0.8 0.7 642 1052 blank holder MM MM ee ee aa aa nn nn oo oo ff ff MM MM ee ee aa aa nn nn ss ss rubber thickness speed MMMMaaaaiiiinnnn EEEEffff ffff eeeecccc tttt ssss PPPPllllooootttt ffff oooorrrr MMMM eeeeaaaannnnssss Data Means Tahseen Fadhil Abbas Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) 76 Fig. 10. The relationship of response value with respect to process variables. 3. Prediction of Process Parameters Using Taguchi’s algorithm to predict the effect of each parameters on the response value and to estimate the empirical equation contribute between each process parameter in second order as illustrated in equation (1) to optimize the present work with present of confidence (R=86.53%), From the given data (blank holder (B), rubber thickness (R) and forming speed (S)) with respect to surface roughness. Table (5) represents the final prediction value using Taguchi’s algorithm, while table (6) represent the analysis of variance using ANOVA algorithm. Rav =0.5617+0.2034B+0.7165R–0.4155 S-0.1778 B2 -0.03105 R2+0.0081S2-0.116BR +0.1321BS ... (1) Table 5, prediction of process parameters with respect to response value using empirical equation Process Parameters Average Response Exp. No. blank holder type Rubber thickness mm Speed mm/min Surface roughness µm Rav 1 1 2 5 0.87037 2 1 2 10 0.95925 3 1 4 2 1.26481 4 1 4 10 1.07148 5 1 6 2 1.52481 6 1 6 5 1.24259 7 2 2 2 1.10704 8 2 2 10 0.91370 9 2 4 2 1.21926 10 2 4 5 0.93703 11 2 6 5 1.19704 12 2 6 10 1.28593 13 3 2 2 0.70592 14 3 2 5 0.42370 15 3 4 5 0.53592 16 3 4 10 0.624815 17 3 6 2 1.07815 18 3 6 10 0.884815 1.50 1.25 1.00 0.75 0.50 3.02.52.01.51.0 1.50 1.25 1.00 0.75 0.50 65432 blank holder * rubber thick blank holder * speed2 bbbb llll aaaa nnnn kkkk hhhh oooo llll dddd eeee rrrr rubber thick * speed2 rrrr uuuu bbbb bbbb eeee rrrr tttt hhhh iiii cccc kkkk 2 4 6 thi ck rubber 2 6 10 speed2 MM MM ee ee aa aa nn nn oo oo ff ff AA AA vv vv ee ee rr rr aa aa gg gg ee ee rr rr oo oo uu uu gg gg hh hh nn nn ee ee ss ss ss ss IIIInnnntttt eeeerrrr aaaacccc tttt iiiioooonnnn PPPPllllooootttt ffff oooorrrr AAAAvvvv eeeerrrr aaaaggggeeee rrrr oooouuuugggghhhhnnnneeeessss ssss Fitted Means Tahseen Fadhil Abbas Al Table 6, analysis of variance using ANOVA algorithm source Df Adj ss blank holder 1 0.84043 rubber 1 0.57484 speed 1 0.16820 Second order blank h*blank h 1 0.18963 rubber*rubber 1 0.03276 speed*speed 1 0.25852 2-Way Interaction blank h*rubber 1 0.00038 blank h*speed 1 0.06678 rubber*speed 1 0.07449 Error 17 1.5834 Total 26 2.61191 Level of confidence (F-value) =95% =0.95 Level of significance (P-value) =5% = 0.05 1- P-value P < 0.05 → Significant P > 0.05 → Non- Significant 2- Fisher value (F-value) F > FT (from table) Critical tabulated FT=4.4513 Percent of contribution % = ��� �� ��� ��� Percent of contribution % Blank holder =53.075 % Rubber thickness =36.301 % Speed of forming =10.622 % 4. Results and Discussion The results of this work is to investigate the effect of various forming parameters (blank holder (B), rubber thickness (cushion) (R) and forming speed (S)) with respect to surface roughness that occurs on the forming parts of Brass (Cu Zn 65-35) using multi-point forming process. The figures were result from the experimental work using ANOVA algorithm that illustrated in Figures (7and 8). The effects of two input parameters represents in each curve in otherwise the parameter was kept constant. The effect of blank holder on the minimum surface roughness at the different cushion thickness and forming speed were used. In this work, with respect to the range of forming parameters used, explain that at the rubber thickness (R=2mm) and using blank hol (3) and forming speed of (S=2mm/min) that gives minimum surface roughness (R as shown in Figures (9) and table (5). While Al-Khwarizmi Engineering Journal, Vol. 15, No. 77 analysis of variance using ANOVA algorithm Analysis of Variance Adj ss F-Value P-Value 0.84043 40.61 0.000 0.57484 27.78 0.000 0.16820 8.13 0.011 0.18963 9.16 0.008 0.03276 1.58 0.225 0.25852 12.49 0.003 0.00038 0.02 0.893 0.06678 3.23 0.090 0.07449 3.60 0.075 1.5834 2.61191 value) =95% =0.95 value) =5% = 0.05 (from table) Critical tabulated �� ��� �� ∗ 100 % ... (2) The results of this work is to investigate the effect of various forming parameters (blank holder (B), rubber thickness (cushion) (R) and forming speed (S)) with respect to surface roughness that occurs on the forming parts of point forming process. The figures were result from the experimental work using ANOVA algorithm that illustrated in Figures (7and 8). The effects of two input parameters represents in each curve in otherwise the parameter was kept constant. The effect of blank holder on the minimum surface roughness at the different cushion thickness and forming speed were used. In this work, with respect to the range of forming parameters used, explain that at the rubber thickness (R=2mm) and using blank holder type (3) and forming speed of (S=2mm/min) that gives minimum surface roughness (Ra=0.42370), as shown in Figures (9) and table (5). While Figure (10) presents the variance of average roughness value with respect to three process parameters. The final empirical model of each forming parameters with respect to average surface roughness using Taguchi’s algorithm. Percentage effect of blank holder types, rubber thickness and forming speed with respect to minimum surface roughness was (53.075, 36.301 and 10.622 shown in Figure (11). Fig. 11. The contribution of process parameters that effect on surface roughness. 5. Conclusion The current research reviewed some important aspects related with surface roughness on forming of materials with special emphasis in brass-alloy. Based on the results of the present work of surface roughness in multi process using ANOVA algorithm, the following conclusions can be drawn: Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) �� � � � � � � � � � Figure (10) presents the variance of average roughness value with respect to three process parameters. The final result is estimate the empirical model of each forming parameters with respect to average surface roughness using Taguchi’s algorithm. Percentage effect of blank holder types, rubber thickness and forming speed with respect to minimum surface roughness was 10.622) % respectively as The contribution of process parameters that effect on surface roughness. The current research reviewed some important aspects related with surface roughness on forming of materials with special emphasis in alloy. Based on the results of the present work of surface roughness in multi-point forming process using ANOVA algorithm, the following conclusions can be drawn: Tahseen Fadhil Abbas Al-Khwarizmi Engineering Journal, Vol. 15, No. 2, P.P. 70- 79 (2019) 78 1. In multipoint forming process, the process parameters (blank holder types, rubber thickness and forming speed) is the main factors that effect on surface roughness. 2. The results of ANOVA Algorithm and the effectiveness experiments data that the developed empirical models for the output responses provide the predicted values and shows an excellent fit of these surface roughness factors that are close to the experimental values, at (R=86.53%)% confidence level. 3. The optimum value of roughness that result from this work using ANOVA is equal to (Ra=0.42370) when using blank holder type (3) and cushion thickness (R=2mm) and at forming speed of (S=5mm/min). 4. medium forming speed gave the best surface roughness, because it give enough time for the metal to reorganize the atoms and thus reduce the strength of the metal resistance to the forming force, the effectiveness range up to (10.622%). 5. Low cushion thickness takes the best surface roughness because the contact area between forming tool and blank is minimum that occurs best result, the effectiveness range up to (36.301%) 6. The blank holder type (3) gave the best surface roughness up to (53.075%). 6. References [1] M.Z. Li, Z.Y. Cai, Z. Sui and Q.G. Yan, Multi-point forming technology for sheet metal, Elsevier Science, Journal of Materials Processing Technology 129 333-338, 2002. 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