Development and influence of setting variables in single point incremental sheet metal forming of AA 8011 using ranking algorithm

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DEVELOPMENT AND INFLUENCE OF SETTING VARIABLES IN SINGLE

POINT INCREMENTAL SHEET METAL FORMING OF AA 8011 USING

RANKING ALGORITHM

Ganesh Babu Loganathan

1

, S. P. Sundar Singh Sivam

2

, V. G. Umasekar

2

and Saravanan K.

3

1

Mechatronics Engineering, Tishk International University, Erbil, Kurdistan Region, Iraq

2

Department of Mechanical Engineering, SRM Institute of Science and Technology, Kancheepuram District, Kattankulathur, Tamil Nadu, India

3

Department of Mechatronics Engineering, SRM Institute of Science and Technology, Kancheepuram District, Kattankulathur, Tamil Nadu, India

E-Mail: [email protected]

ABSTRACT

Single point Incremental shaping (SPIF) is a metal forming process which rose to unmistakable quality toward the start of the 1990s. ISF is an exceedingly limited twisting procedure in which a device, modified to take after a specific direction, moves over a sheet metal and structures the coveted shape. During the SPIF, process parameters such as the Axial Feed (mm), Feed (mm/min), tool Diameter (mm) and Depth (mm) at the specimen interface greatly influence in the Cone shaped Mechanical quality such as Maximum Thinning (mm), Cone Height (mm), Wall Angle (mm) &Forming Time (min) of Forming. The aim of the present work is to study these parameters while build up a cone quality, were formed by VMC. To carry out a detailed study of these parameters, experiments were conducted by using the L9 orthogonal array. The output parameters such as affecting mechanical quality were analysed by Grey relational Analysis and ANNOVA.

Keywords: single point increment forming - forming environment-grey relational analysis - ANNOVA.

1. INTRODUCTION

Single Point Incremental Forming (SPIF) is another metal forming procedure with a potential financial result for fast prototyping applications for adaptable and little amount creation satisfying this hole in metal framing forms. These days, the need of enhancing the two procedures and segments has coordinated with the need of weight decrease. This is especially vital for aluminium composites with poor formability. As of late, they have gotten expanding interests in the car business as potential auxiliary materials because of their low mass thickness that permits noteworthy weight lessening and, thus, fuel reserve funds. Aluminum is that the lightest basic metal. Furthermore to its low particular weight, it offers heavenly mechanical properties contrasted and distinctive metallic materials. Diverse advantages of aluminium combinations for auxiliary applications grasp savvy properties at raised temperatures (contrasted with plastics and polymer grid composites), weakness quality, dimensional steadiness, scratch resistance, machinability, consumption resistance and stylish interest. In this way, there has been a developing enthusiasm for utilizing magnesium combinations for stack bearing and basic components. Aluminium combination parts have generally been made utilizing pass on throwing. Be that as it may, press framing has turned into a promising diverse as a result of ecological issue with throwing, and in light of the fact that higher material properties might be acquired by press shaping. To alter such applications, it's fundamental to have the capacity to foresee the press framing of those materials and furthermore the technique parameters that empower the part to be shaped without burst or deformities instigated by the framing strategy. The

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TPIF (Two-Point Incremental Forming) as a process [8]. The fast Single Point Incremental Forming of titanium compounds. Single Point Incremental Forming forms have impediments in dimensional exactness and process gradualness, overcome by presenting the fast framing, enabling a lessening to under 1 min of execution time of target Titanium composite components [9-35] .Light weight components improve engine efficiency and reduce fuel consumption and pollution. Thus aluminium replaces steel in automobile industries. The development characterized by high flexibility in sheet forming uses new concept products. The objective is to evaluate the performance with respect to various parameters like Axial Feed (mm), Feed (mm/min), tool Diameter (mm) and Depth (mm) for the response of Maximum Thinning (mm), Cone Height (mm), Cone Diameter (mm) & Forming Time (min) informing Quality in Vertical Machining Center.

2. EXPERIMENTAL PROCEDURE

Machine chose for this investigation is CNC vertical processing machine, has determinations like: Make-LAKSHMI MACHINE WORKS, Control framework FANUC, working range X, Y and Z-hub are 450mm, 350mm and 350mm. Table size is 600×350mm, Positional Accuracy-0.01mm, Repeatability-0.05mm, Power required 15KVA, Range of spindle speed 80-8000 RPM. CNC Milling Machine is appeared in Figure-1. The rod shape forming tool with a hemispherical head (12mm diameter) was clamped into the spindle of the Milling machine. The sheet metal was situated with the upper blank holder, pressed onto the lower blank holder where the straightforward pass on was put on the worktable. In this we consider distinctive parameters like rotation of spindle, axial feed rate, X, Y feed rate. Experimental Setup and Assembly Fixture are appeared in Figures 1 & 2. For directing analysis, we chose parameters are appeared in Table-1. Conical Cups having shape were framed utilizing the part program.

Figure-1. Experimental setup.

2.1 Design model of fixture

The main function of the fixture was to hold the work piece securely during forming. Forming produces lot of localized stress, hence clamping is important. A metal frame was the clamp. The sheet metal was placed in between the base of the fixture and the clamping plate using steel bolts. Fixture was decided to build with five components. The first component was the base to be bolted. Due to vibrations and forces, it was decided to make it 20 mm thick. The other four components are rectangular bars 42 mm thick which rise up vertically from the base plate and provide a framework for holding the work piece. For designing and making 3D models of the components, software CATIA V5 was used. The fixtures were fabricated as per the requirements of final shapes shown in Figure. The design and fabrication of the tool diameter 8, 10, 12 mm, were made as per the requirements to get conical shape.

Figure-2. Fabrication of Assembly Fixture.

2.2 Material selection

The present work going to be concentrates on the consideration of single point incremental forming (SPIF) procedure of Aluminum alloy AA 8011 composition is appeared in Table-1, which has important industrial applications mainly for sheet metal forming.

2.2.1 Chemical Composition

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Table-1. Chemical Composition of AA 8011.

Alloy Al Si Fe Cu Mn Mg Zn Ti Cr

Volume % 97.5 0.7 0.8 0.1 0.2 0.05 0.1 0.08 0.05

Here the Si acts nearly as good deoxidizing agent which kills the metal oxide formation, carbon ascribes to hardness and strength of the specimen. Iron, Increases quality strength due to formation of Al-Fe intermetallics and Decreases ductility and flexiblity. Copper, Cu Increases tensile strength, fatigue strength and hardness of the alloys due to the effect of solid solution hardening. Manganese, Mnimproves the Strengthens and hardens the alloys Improves ductility of aluminum alloys containing iron and silicon due to modification of Al5FeSi intermetallic inclusions from platelet to cubic form Al15(MnFe)3Si2. Magnesium, Mg Strengthens and hardens the alloys by solid solution hardening mechanism without considerable decrease of ductility. Zinc, Zn, in a combination with magnesium or magnesium-copper allows strengthening the alloys by precipitation hardening heat treatment (Wrought aluminum-zinc-magnesium alloys. It Increases vulnerability of the alloys to Stress corrosion cracking. Titanium, Ti Refines primary aluminum grains (grains formed during the Solidification) due to formation of fine nuclei Al3Ti. Titanium is regularly supplementary to aluminum alloys together with boron because of their synergistic grain refinement impact. Chromium, Cr Suppresses the grain growth at elevated temperatures due to high speed and feed. Improves ductility and toughness of aluminum alloys containing iron and silicon due to modification of Al5FeSi intermetallic inclusions from platelet to cubic form (similar to the effect of manganese).Reduces susceptibility of the alloys to Stress corrosion cracking. The presence of all alloys increases the draw ability.

3. METHODS OF ANALYSIS

3.1 Analysis of variance

Analysis of variance (ANOVA) with Taguchi technique as in could be a statistical procedure won’t to interpret experimental knowledge. Amid this examination, there are four essential controllable Factors, i.e. four-level Axial Feed (1/2/3 mm), Feed (100/300/500 mm/min), Bottom Diameter Tool Pin (8/10/12), and Step Down (0.2/0.4/0.6 mm), as appeared in Table-1, which are used for ANOVA. Their interactions may be computed from the experimental information through multivariate analysis. During this study, using Taguchi techniques, The L9 orthogonal arrays are needed for Maximum Thinning (mm), Cone Height (mm), Cone Diameter (mm) and Forming Time (min). Total degrees of freedom may be calculated17. Based on Taguchi’s recommendation within the larger the S/N ratio for ultimate tensile strength and elongation rate is the better14.

3.2 Grey relational analysis (GRA)

The transformation of S–N quantitative relation values from the initial response values was the initial step. For that the equation (1) of ‘larger the better’ was used. Ensuant analysis was carried out on the premise of these S/N ratio values. This can be shown in Table-3.

S/N = −10 log10(_n1∑ni=r_y1_ij2) ……….….. (1)

In GRA, initially the experimental knowledge is normalized. By using this normalized data, relational coefficient are evaluated, the Grey relational grade was obtained by averaging the GRC values related to selected experimental results.

3.2.1 Grey relational generation (GRG)

GRG may be classified into 3 sorts particularly Smaller the better, Larger the better or Nominal could be a better (NB) criterion. The preferred quality characteristics for final maximum Thinning, Cone height, wall angle and Forming time are Larger the better criterion, then it's expressed by using equation (2):

𝑦𝑖∗(𝑘) =_{𝑚𝑎𝑥 𝑦}𝑦𝑖(𝑘)−𝑚𝑖𝑛 𝑦_𝑖_{(𝑘)−𝑚𝑖𝑛 𝑦}𝑖(𝑘)_𝑖_(𝑘) ………. (2)

Where i = 1,…m; k = 1,2,3,…n; m = no. of experimental

data; n = no. of factors; yi(k) = originalsequence; yi*(k)

value after Grey relational generation; min yi(k) and max

yi(k) are the minimum and maximum value of yi(k),

respectively. The normalized values are shown in Table-3.

3.2.2 Grey relational coefficient (GRC)

The calculation for Grey relation coefficient was done using equation (3):

𝜀𝑖(𝑘) =_∆∆ min +𝜔∆ 𝑚𝑎𝑥_𝑜𝑖_{(𝑘)+ 𝜔∆ 𝑚𝑎𝑥} ……….. (3)

Where εi (k)εi (k) is the Grey relation coefficient; ΔoiΔoi is

deviation among yo*(k)yo*(k) and yi*(k)yi*(k); yo

*(k)=ideal (reference) sequenceyo

*(k)=ideal (reference) sequence;

Δmax=highest value of Δoi (k)Δmax=highest value of Δoi (k,

Δmin=least value of Δoi (k)Δmin=least value of Δoi (k).

3.2.3 Grey relation grade

The Grey relational grades (GRG) (Ґi) are determined by taking average of the GR coefficient related to every observation as given in equation (4), Table-3 and Figure-7:

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Where, Q = total amount of reactions and n

indicates the amount of yield responses. The GRG Ґi speaks to level of relationship among the reference or perfect arrangement and the near grouping. On the off chance that bigger GRG is gotten for the identical arrangement of process parameters contrasted with different sets, it's considered as the best ideal setting.

3.3 Process parameter

The selection of process parameter is the main factor in the SPIF. The process parameters which are used to Form the good strength of the specimen can be obtained based on the forming parameters. The process parameters are listed in Table-2.

Table-2. Process parameter Design.

Parameters Unit Levels

1 2 3

Material

Thickness mm 1 1.5 2

Feed mm/min 100 300 500

Tool

Diameter mm 8 10 12

Step Down mm 0.2 0.4 0.6

4. RESULTS AND DISCUSSIONS

The process for SPIF aluminium alloys AA8011 in Figure-3.

Figure-3. Formed Sample of Aluminium Alloys.

Table-3. Response data of L9Orthogonal arrays.

Trial No.

Material Thickness

(mm)

Feed X,Y(m m/min)

Tool Diameter

(mm)

Step Down z (mm)

SPIF process Response Maximum

Thinning (mm) Cone Height (mm)

Wall Angle (mm)

Forming Time (min)

1 1 100 8 0.2 0.6 28.3 73.2 48

2 1 300 10 0.4 0.58 31.5 68.2 39

3 1 500 12 0.6 0.56 32.5 66.7 30

4 1.5 100 8 0.2 0.68 34.2 73.8 48

5 1.5 300 10 0.4 0.51 35.7 69.8 39

6 1.5 500 12 0.6 0.3 37.2 65.3 30

7 2 100 8 0.2 1.4 39.5 74.2

48 39 30

8 2 300 10 0.4 1.3 42.7 69.2 39

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Table-4. Response Data with Normalized, Grey relational and Grey Grade.

Normalized S/N ratio Grey Relational Coeff Grey

Maximum Thinning (mm)

Cone Height

(mm)

Wall Angle (o)

Forming Time (min)

Maximum Thinning

(mm)

Cone Height (mm)

Wall Angle(o)

Forming

Time (min) Grade Rank

0.022866978 0.022866978 0.1063063 0.995886814 0.995886814 0.995886814 0.995886814 0.995886814 0.5063564 8

0.613914819 0.228669781 0.6594595 0.558168014 0.53088025 0.515932112 0.508095 0.504080546 0.5208261 7

0.945886814 0.295549545 0.8333333 0.022866978 0.333333333 0.428571429 0.4666667 0.483870968 0.6002008 5

0.663506418 0.404475043 0.0423423 0.995886814 0.995886814 0.995886814 0.995886814 0.995886814 0.5992879 6

0.40781797 0.495942955 0.4783784 0.558168014 0.53088025 0.515932112 0.508095 0.504080546 0.4940193 9

0.888127188 0.583968527 0.995886814 0.022866978 0.333333333 0.428571429 0.4666667 0.483870968 0.6740823 2

0.788943991 0.712072781 0.022866978 0.995886814 0.995886814 0.995886814 0.995886814 0.995886814 0.6677723 3

0.995886814 0.878534546 0.5459459 0.558168014 0.53088025 0.515932112 0.508095 0.504080546 0.7148774 1

0.608226371 0.995886814 0.7054054 0.009958868 0.333333333 0.428571429 0.4666667 0.483870968 0.6308164 4

Table-5. ANOVA for Maximum Thinning (mm).

Source of variation Sum of Squares DOF Mean Square F F table Contribution %

Material Thickness 1.7340 2 0.8670 4335.06 4.2 91.56

Feed X,Y 0.0142 2 0.0071 35.39 4.2 0.75

Tool Diameter 0.0990 2 0.0495 247.39 4.2 5.22

Step Down 0.0468 2 0.0234 117.06 4.2 2.47

Error 0.002 9 0.000200

___

Total 1.8940 17

Table-6. ANOVA for Cone Height (mm).

Source of variation Sum of Squares DOF Mean Square F Ftable Contribution %

Feed X,Y 28.2022 2 14.1011 70505.56 4.2 11.88

Tool Diameter 1.9756 2 0.9878 4938.89 4.2 0.83

Step Down 0.2756 2 0.1378 688.89 4.2 0.12

Error 0.002 9 0.000200

___

Total 237.4689 17

Table-7. ANOVA for Wall Angle (o).

Feed X,Y 78.7467 2 39.3733 196866.67 4.2 94.08

Tool Diameter 1.5800 2 0.7900 3950.00 4.2 1.89

Step Down 1.6467 2 0.8233 4116.67 4.2 1.97

Error 0.002 9 0.000200

___

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Table-8. ANOVA for Forming Time (min).

Feed X,Y 486.0000 2 243.0000 1215000.00 4.2 100.00

Tool Diameter 0.0000 2 0.0000 0.00 4.2 0.00

Step Down 0.0000 2 0.0000 0.00 4.2 0.00

Error 0.002 9 0.000200

___

Total 486.0000 17

Table-9. ANOVA for Grey Grade.

Feed X,Y 0.0056 2 0.0028 13.89 4.2 11.00

Tool Diameter 0.0043 2 0.0022 10.76 4.2 8.53

Step Down 0.0152 2 0.0076 37.90 4.2 30.03

Error 0.002 9 0.000200

___

Total 0.0505 17

The degree of importance of each parameter is considered, namely, Maximum Thinning (mm), Cone Height (mm), Wall Angle (mm) & Forming Time (min) of Form for each response is given in Tables 5-9, respectively and Grey Grade. From Table-5, it is found that Maximum thinning (mm) is the major factor affecting the Material Thickness (91.56%) followed by Tool Diameter (5.22%), Step Down (2.47%) and Feed (0.75%). In Table-6, Cone Height (mm) are found to be the most significant factors affecting the Material Thickness (87.18%) followed by Feed (11.88%), Tool Diameter

(0.83%) and Step Down (0.12 %). In Table-7, Wall Angle (0) is found to be the most significant factors affecting the Feed (94.08%) followed by Material Thickness (2.06%), Step Down (1.97 %) and Tool Diameter (1.89%). In Table-8, Forming Time (min) is found to be the most significant factors affecting the Feed (100%). In Table-9, Grey Grade is found to be the most significant factors affecting the Material Thickness (50.44%) followed by Step Down, Feed and Tool Diameter. from the Figure-4, the optimum parameter would be MT1, F2,TD3, SD1.

Figure-4. Factor Effects on Grade values.

5. CONCLUSIONS

Single Point Incremental forming has immensely high potential in the field of thermo mechanical processing of various alloys especially the aluminum alloys. The forming aluminium alloys of AA8011cone shape are successfully fabricated using CNC vertical milling machine. The influence of each process parameters on final formed cone shape related to mechanical properties have been made to determine its potential and limitations. The results are listed below. The most significant SPIF

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most significant factors affecting the Feed (100%). The best optimum parameter will be MT1, F2, TD3, SD1.

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