Determining the Effect of Key Process Parameters on Forming...

Determining the Effect of Key Process Parameters on Forming Force of Single Point Incremental Sheet Metal Forming

Abdulmajeed DABWAN Industrial Engineering Department

King Saud University, P.O. Box 800, 11421 Riyadh, Kingdom of Saudi Arabia

[email protected]

Adham E RAGAB Industrial Engineering Department


[email protected]

M.A.E. SALEHIndustrial Engineering Department


[email protected]

Abdelnaser K. DAOUD Industrial Engineering Department


[email protected]

Abstract— Incremental forming is an innovative sheet metal forming technology. It is a promising flexible and inexpensive method to form sheet products in small batches. One technique within this technology is single point incremental forming which allows producing complex shape using a computer numerical control machine. It is a new sheet metal forming process which achieves higher formability, greater process flexibility and reduced forming forces compared to conventional sheet forming operations due to its characteristic of localized deformation. In this paper, an experiment was conducted to study the effects of several parameters (tool diameter, feed rate, step size and sheet thickness) on forming forces to provide a better understanding of the process parameters leading to achieve a successful product. Experiments were performed based on a full factorial design of experiment technique. The formed sheets were made of AA1050-H14 aluminum alloy.

Keywords— Incremental forming, Single point incremental forming, Design of Experiment, AA1050

I. INTRODUCTION

In industry, sheet metal forming is a group of high volume production processes. The process of stamping or deep drawing can be used to produce thousands of parts efficiently. Therefore products can be manufactured in large numbers at a reduced cost. However, for small patches and prototype production there remains the need to a more flexible process that can overcome the initial high cost of die making in conventional sheet metal forming processes. This process should be capable of producing parts quickly after they being conceptualized and drafted with minimum cost. Furthermore, the increasing need for limited or unique series sheet metal parts in a wide range of industrial applications such as medical implants, automotive prototype parts or thin shell dies pushed for the use of incremental sheet forming (ISF) process. However, the forming time in SPIF is much higher than those in conventional forming[1]

In incremental sheet forming there are several different process variants. Single point incremental forming (SPIF) is one of the popular processes under the ISF family. Recently a lot of attention is focused on SPIF metal forming, where a dedicated die is not needed. It is an innovative method for metal sheet forming which was developed during last decades [2, 3]. This method is designed for small batch production and prototyping and considered very economical process, especially for single piece manufacturing.

Proceedings - International Conference on Industrial Engineering and Operations Management, Kuala Lumpur, Malaysia, March 8-10, 2016

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The process employs a conventional CNC machine to produce complex parts from sheet metal[4]. It is possible to form parts that are usually deep drawn or stamped without any supporting dies. The concept of this process is based on incrementally deforming a sheet metal blank into a desired shape using a hemispherical stylus and a specified tool path conforming to the final part [5]. The tool path is generally defined by CAD/CAM software developed for machining application. Furthermore, the enhanced formability of this technology is useful to those industrial applications requiring high deformation levels.

The forming forces in this technology is lower compared to conventional forming [1], which allows using smaller and more mobile machines. Forming force estimation in SPIF is especially important in the case of using machinery adapted for the process like milling centers and robots[5]. Forming force also provides key insight into the deformation mechanics of the process. Filice and Ambrogio [6, 7] worked on the force measurement and analysis. They classified the tangential force trends into three types: steady state force trends, polynomial force trends and monotonically decreasing force trends. Therefore, forming force is a potential indicator for forming limits identification. Petek et al.[8] proposed an autonomous on-line system for fracture identification and localization by analyzing the reaction force with skewness function. Another failure criterion presented by Fiorentino[9] is also based on force monitoring during the forming process. Li et al. [10] presented forces during the cone forming process with different wall angles and step down sizes and different force trends were identified and discussed with reference to bending and strain hardening mechanics. Bagudanch et al. [11] focused on the maximum forming force evaluation under the influence of some process parameters (step down, spindle speed, feed rate, tool diameter and sheet thickness) and analysis of the maximum forming force variation with respect to the most significant process parameters involved in the SPIF technology achieved.

The capability of this innovative process is being investigated for different application such as highly customized medical and biomedical products[12, 13], manufacturing of automotive[14, 15], aerospace[5] and for the calibration of void nucleation model for automotive Aluminum sheet metal[16].

This paper is aimed to investigate the relation between four key process parameters (tool diameter, feed rate, step size and sheet thickness) on the forming force components in SPIF. DOE full factorial design was used in order to estimate the significance of each process parameter and the interactions amongst them.

II. EXPERIMENTAL SETUP

A. CAD ModelIn order to form the part with SPIF a CAD model is needed, a truncated cone shaped geometry was built with base diameter

of 100 mm and height of 50 mm as shown in Fig. 1 (a). The CAD model was utilized for devising the tool path using commercial MASTER CAM software. The tool path was generated according to the profile of the CAD model. Tool contours were created and connected using a step transition method[5]. An actual produced part is shown in Fig.1 (b).

(a) (b)

Fig. 1. The test workpiece:: (a) CAD Model and (b) actual prduced part

B. Fixture DesignThe fixture for the experiment was designed and built as shown in Fig. 2. The whole apparatus is clamped to the working

table of the CNC by four screws as shown in Fig. 2 (a). It consists of three parts: upper plate to hold the sheet over the middle plate as shown in Fig. 2 (b), middle plate to support the formed sheet as shown in Fig. 2 (c), lower plate with push and guide that are fixed on the machine working table as shown in Fig. 2 (d). The workpiece dimensions were 240 by 240 mm, while the working area was 200 by 200 mm.


(a) (b)

(c) (d)

Fig. 2. Workpiece fixture

C. MaterialThe material used in this study was commercially available aluminum alloy AA 1050-H14. Two samples of the material

were tested using SPECTRO machine and the composition was obtained as shown in Table I. TABLE I. CHEMICAL COMPASSION OF ALUMINUM ALLOY (1050-H14)

Sample Al %

Fe %

Si %

Ti %

Other

1 99.5 0.368 0.0480 0.0216 0.0624 2 99.5 0.360 0. 0496 0.0205 0.000699

The used sheet was tested for mechanical properties. Nine test specimens were cut \from the sheet by laser cutting process at angels 0°, 45° and 90° degrees with respect to the sheet rolling direction. The specimens were tested on a Zwick/Roell universal testing machine. Test results are given in Table II. The average value of the anisotropy coefficient 𝑅𝑅� was obtained as stated by Kalpakjian, Schmid et al. [17].

TABLE II. EXPERIMENTAL MECHANICAL PROPERTIES OF ALUMINUM ALLOY AA 1050-H14

Material code

Yield Strength 𝝈𝝈𝒚𝒚 (MPa)

Ultimate Tensile Strength 𝝈𝝈𝑼𝑼𝑼𝑼𝑼𝑼 (MPa)

Elongation at Break A (mm)

Young Modulus E (MPa)

AA1050-H14 128 117.5 8.45 67648


TABLE III. SUMMARY OF THE ANISOTROPY

D. Design of Experiment (DOE)DOE is a wide group of efficient techniques to analyze the relation between a response (dependent variable) and a number

of factors (independent variables.) In this research; two level full factorial design with four factors (24) and two replicates was used to estimate the effect of studied process parameters and their interactions on forming force components. The process parameters which were expected to have a significant influence on the forming force components were selected based on literature. These are (1) tool diameter; (2) feed rate; (3) step size and (4) sheet thickness. The levels of studied parameters are presented in Table IV. Table V shows the completely randomized design of the conducted experiment.

TABLE IV. LEVELS OF FACTORS FOR EXPERIMENTS

Annotation Experimental parameter Low level High level (A) Tool diameter (mm) 10 20 (B) Feed rate (mm/min) 500 1000 (C) Step size (mm) 0.5 1 (D) Sheet thickness (mm) 1 2

TABLE V. FULL FACTORIL DESIGN

Experiment No. A B C D Experiment No. A B C D 1 10 500 1.0 1 17 10 500 0.5 2 2 20 1000 0.5 2 18 10 1000 0.5 2 3 20 1000 0.5 1 19 20 1000 1 2 4 20 500 0.5 2 20 10 1000 1.0 2 5 10 500 0.5 1 21 20 1000 1.0 2 6 10 500 0.5 1 22 20 1000 0.5 1 7 10 500 1.0 1 23 10 500 1.0 2 8 20 500 0.5 1 24 10 1000 1.0 2 9 20 500 0.5 2 25 20 500 1.0 1 10 10 1000 0.5 1 26 20 1000 1.0 1 11 20 1000 0.5 2 27 20 500 1.0 2 12 10 1000 0.5 1 28 10 1000 0.5 2 13 20 500 1.0 2 29 10 1000 1.0 1 14 20 500 0.5 1 30 20 500 1.0 1 15 10 500 1.0 2 31 10 1000 1.0 1 16 20 1000 1.0 1 32 10 500 0.5 2

Then Analysis of Variance (ANOVA) is conducted using Minitab 16. The analysis is run for each response (Fx, Fy and Fz) separately. All terms (factors and interactions) are included in the first analysis. Then the mode is reduced by removing items which were not significant one by one [18-20]. The item with the biggest P-value is removed first (unless it is a part of significant higher interaction) and the fitting process is preformed again. The significance of every item is rechecked and the refining process is repeated until a reduced model is reached with all items are significant (P-value < 0.05).

A model refinement technique is then applied. That is removing readings with very large residuals from the reduced model [20, 21]. As Hoaglin and Welsch [22] suggests, it is better to use standardized residuals (SR) to decide removed readings. There is no specific limit for the SR to remove the readings, however, since there is only two replicates in this experiment, it was decided that only runs with SR>3.0 or <-3 be removed from the model. That was run #19 which showed very high SR in the three force components.

0° RD 45° RD 90° RD 𝜺𝜺𝑾𝑾 𝜺𝜺𝑼𝑼 𝜺𝜺𝑾𝑾 𝜺𝜺𝑼𝑼 𝜺𝜺𝑾𝑾 𝜺𝜺𝑼𝑼

Specimen 1 12.30 0.83 12.20 0.82 12.36 0.80 Specimen 2 12.35 0.80 12.25 0.84 12.34 0.83 Specimen 3 12.34 0.81 12.23 0.82 12.33 0.81 Average 12.33 0.81 12.22 0.82 12.34 0.81

𝑅𝑅 0.82 0.84 0.82 𝑅𝑅� 0.83


E. Force measurementThe forming force was measured using the setup shown in Fig. 3 (a). The force was measured in 3 directions, as illustrated

by Fig. 3 (b), using a KISTLER 2825A1 force dynamometer located under of the workpiece fixture and connected to a KISTLER 5019B three channel charge amplifier. With these apparatuses the force components exerted upon the part by the tool were measured and recorded on a computer based data acquisition system. The sampling rate was 50 Hz. The force components were measured in x, y and z directions defined in Fig. 3 (b).

(a) (b)

Fig. 3.Set-up for force measurement during the ecperiment

III. RESULTS AND DISCUSSION

Fig.4 shows a sample of the dynamometer output. Force components in x, y and z directions are shown. From the figure, it is clear that the forces in both x and y directions are symmetric about the zero line. However, they are different from each other due to material anisotropy. Table VI gathers the dynamometer readings from the 32 experiments.

TABLE VI. MEASURED FORCE COMPONENTS

Experiment No.

Fx (N) Fy (N) Fz (N) Experiment No.

Fx (N) Fy (N) Fz (N) Experiment No.

Fx (N) Fy (N) Fz (N)

1 318.16 331.69 529.75 12 186.81 188.07 411.57 23 327.03 331.91 622.96 2 680.92 705.17 1636.29 13 420.70 447.42 873.51 24 257.48 292.22 579.96 3 313.98 304.99 525.67 14 420.70 173.59 295.76 25 157.15 160.28 239.35 4 779.79 770.42 1637.10 15 377.02 380.88 724.60 26 155.08 148.48 234.16 5 200.51 202.94 427.65 16 140.51 143.01 219.14 27 338.47 364.73 665.74 6 197.09 214.55 474.92 17 222.86 262.58 472.52 28 192.35 215.09 513.93 7 307.23 288.38 449.73 18 195.17 236.15 469.88 29 112.52 111.60 176.58 8 323.41 323.65 520.47 19 862.29 868.92 1631.76 30 156.08 157.83 231.07 9 756.54 788.15 1651.34 20 258.35 270.47 564.92 31 97.00 91.32 169.68 10 187.17 186.83 375.34 21 375.95 355.04 863.46 32 211.49 229.27 558.05 11 677.69 678.64 1587.21 22 321.20 329.46 598.28

Fig. 4. Force components measured in x, y and z


A. ANOVA results for forming force in the z direction (Fz) Table VII shows ANOVA final results for forming force component in the z-direction (Fz) after model reduction and

refinement. If the P value in ANOVA table is less than 0.05 indicates statistical significance for the source on the corresponding response. Model adequacy is evaluated using the coefficient of determination (R-squared, adjusted R-squared and predicted R-squared) given in Table VII. Their values show levels very close to 1 which proves the adequacy of the model. Considering the adjusted R-squared, the model explains 95.12% of the variation in the data. The 92.88% value of the predicted R-squared shows that the model is not over fit and has a good predictability.

Examining the adjusted sum of squares (Adj SS), it is evident that factor D (sheet thickness) has the greatest effect on the z-component forming force. This is followed by the interaction between factors A & D (tool diameter and sheet thickness) and then followed by factor A. As a result, it is to be said that selecting a machine for SPIF process is dictated mostly by these two factors: sheet thickness and tool diameter.

The third level interaction of tool diameter, step size and sheet thickness does not allow meaningful interaction of main effect and lower interaction of these three factors. While it is evident that the feed rate did not affect the force in the z-direction, it is interaction with tool diameter had a small significant effect.

TABLE VII. ANALYSIS OF VARIANCE FOR FZ

Source DF Seq SS Adj SS Adj MS F P Main Effects 4 3521432 3500723 875181 96.11 0 A 1 768726 794590 794590 87.26 0 B 1 14219 9191 9191 1.01 0.326 C 1 584338 507588 507588 55.74 0 D 1 2154149 2131681 2131681 234.09 0 2-Way Interactions 3 1596347 1576770 525590 57.72 0 A*B 1 69247 62328 62328 6.84 0.016 A*C 1 592916 565533 565533 62.1 0 A*D 1 934184 890704 890704 97.81 0 3-Way Interactions 1 276788 276788 276788 30.4 0 A*C*D 1 276788 276788 276788 30.4 0 Residual Error 22 200338 200338 9106 Pure Error 15 65826 65826 4388 Total 30 5594904 Model Summary S = 95.4267 R-Sq = 96.42% R-Sq(pred) = 92.88% R-Sq(adj) = 95.12%

B. ANOVA results for forming force in the x direction (Fx) Table VIII shows ANOVA final results for forming force component in the x-direction (Fx) after model reduction and

refinement. If the P value in ANOVA table is less than 0.05 indicates statistical significance for the source on the corresponding response. Model adequacy is evaluated using the coefficient of determination (R-squared, adjusted R-squared and predicted R-squared) given in Table VIII. Their values show levels very close to 1 which proves the adequacy of the model. Considering the adjusted R-squared, the model explains 88.16% of the variation in the data. The 84.86% value of the predicted R-squared shows that the model is not over fit and has a good predictability.

Examining the adjusted sum of squares (Adj SS), it is evident that the sheet thickness and the tool diameter have the greatest effect on x-component forming force. This is followed by the interaction between tool diameter and step size. As in the force component in the z-direction, the feed rate did not affect the force in the x-direction.

TABLE VIII. ANALYSIS OF VARIANCE FOR FX

Source DF Seq SS Adj SS Adj MS F P Main Effects 3 582965 584056 194685 48.52 0 A 1 232235 226086 226086 56.35 0 C 1 85761 76903 76903 19.17 0 D 1 264970 261447 261447 65.16 0 2-Way Interactions 2 333247 333247 166623 41.53 0 A*C 1 203425 191295 191295 47.68 0 A*D 1 129822 129822 129822 32.36 0 Residual Error 25 100309 100309 4012 Pure Error 23 67424 67424 2931 Total 30 1016521 Model Summary S = 63.3432 R-Sq = 90.13% R-Sq(pred) = 84.86% R-Sq(adj) = 88.16%


Fig. 5 is illustrates the effects of interaction between tool diameter, step size sheet thickness. Based on the previous analysis, the effects of interactions (A*C and A*D) are statistically significant to forming force (Fx). The interaction plot shows that larger tool diameter (A) and larger sheet thickness (D) contribute to the increment of forming force component Fx, while larger tool diameter (A) and higher step size (C) contribute to decreasing forming force component Fx.

Fig. 5. Interaction plot for forming force component Fx

C. ANOVA results for forming force in the x direction (Fy)

Table IX shows ANOVA final results for forming force component in the y-direction (Fy) after model reduction andrefinement. As expected the results for forming force components in both x and y directions are very similar. The same discussion on Fx results apply here.

TABLE IX.ANALYSIS OF VARIANCE FOR FY

Source DF Seq SS Adj SS Adj MS F P Main Effects 3 606534 605316 201772 38.23 0 A 1 175206 183954 183954 34.85 0 C 1 77090 65805 65805 12.47 0.002 D 1 354237 353417 353417 66.96 0 2-Way Interactions 2 306001 306001 153000 28.99 0 A*C 1 157610 146277 146277 27.71 0 A*D 1 148391 148391 148391 28.12 0 Residual Error 25 131948 131948 5278 Pure Error 23 83185 83185 3617 Total 30 1044483 Model Summary S = 72.6494 R-Sq = 87.37% R-Sq(pred) = 80.46% R-Sq(adj) = 84.84%

IV. CONCLUSION

In this research, experimental study was conducted to study the role of key process parameters in the SPIF forming force in shaping commercial aluminum alloy AA1050-H14. The key process parameters are: tool diameter, feed rate, step size and sheet thickness. Thirty two specimens, in the shape of truncated cone, were formed according to a completely randomized full factorial design. A special fixture was designed to facilitate the forming process on a CNC milling machine.

The results showed that the sheet thickness is the main factor in estimating the forming force in SPIF process and hence in selecting the appropriate machine. The tool diameter and step size follow next. Feed rate proved to be insignificant in estimating the forming force. However, it’s interaction with the tool diameter showed little significance with respect to the force component in the z-direction. The interaction between tool diameter & sheet thickness and between tool diameter & step size showed a highly significant effect on all forming force components.

ACKNOWLEDGMENT This work was supported by Department of Industrial Engineering in King Saud University in the Kingdom of Saudi Arabia.

The authors would like to thank all personnel involved in this work.

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Interaction Plot for FxData Means


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