At present, sheet metal forming is gaining importance in the manufacturing sector and this process is essentially used to produce various engineering components having applications in railway cars, automobile bodies, construction, farm...
moreAt present, sheet metal forming is gaining importance in the
manufacturing sector and this process is essentially used to produce
various engineering components having applications in railway cars,
automobile bodies, construction, farm equipment, office furniture, lighting
equipment, computer peripherals, medical appliances, etc. The formed
component having the best design, superior quality and an aesthetic look
is the demand of the present sheet metal industry. The present needs
of the sheet metal manufacturing industry are to optimise the forming
operations.
Deepdrawing is one of the sheet metal forming operations widely
used in manufacturing industries for producing cup-shaped components.
In this process, sheet metal placed between the die and blank-holder on
its periphery can be drawn into the die for forming into a cup-shaped
component. This process is extensively used for the manufacture of cups,
cans and other similar types of products. The deep drawing process is
influenced by geometric parameters as well as process parameters. Its
geometric parameters include Die Shoulder Radius (DSR), Punch Nose
Radius (PNR) and clearance between punch and die. The Blank Holder
Force (BHF), coefficient of friction, punch speed and blank temperature
are the process parameters. All these parameters have their influence on
the quality of the cup produced. A literature search reveals that PNR, and
BHFaresignificantly influencing tool design based parameters of the deep
drawing process. In any deep drawing process uniform wall thickness of
the drawn cup is the desired quality characteristic. From the literature, it
is also found that these parameters vary in their respective ranges. Experiments are conducted using DoE to optimise the
combinations of geometric and process parameters and levels that would
give minimum variation in the thickness of the cup produced in the deep
drawing process. To develop optimised deep drawing facilities using
Design of Experiments (DoE), the ranges for highly influencing parameters
are fixed after a thorough study of literature. The tool setup is designed for
optimization of highly influencingparametersusingDoEbasedonTaguchi
technique. The parameter ranges for highly influencing parameters fixed
are PNRfrom 5.5 to 10.5 mm, DSR from 5.5 to 10.5 mm and BHFfrom3
to 7 kN. The uniform thickness of the drawn cup is considered as output
characteristic and the variation in cup wall has to be as minimum as
possible. The three level values fixed for these parameters are 5.5 mm,
8 mmand10.5 mm for PNR; 5.5 mm, 8mm and 10.5 mm for DSR and
3 kN, 5kNand7kNforBHF.
Subsequently, experimental tests are conducted using L9
Orthogonal Array (OA) for optimisation of the process setup. Following
the DoE procedure, nine experiments are performed according to L9 OA
instead of conducting all the possible 27 experimental tests. During the
experimental tests, Aluminium alloy AA6111 blanks are considered as the
test material having 130 mm diameter and 0.9 mm thickness. In every test,
the thickness readings are measured at nine different points, radially from
the edge of the flange to the centre of a cup at the bottom. Considering
"Nominal is the Best" (NB) characteristic, The Signal to Noise (S/N)
ratios are determined using Qualitek- 4 software. The application of this
Taguchi based DoE software for optimisation of the deep drawing process
indicated the optimal values for the parameters considered, and these are
PNRof5.5 mm,DSRof5.5mmandBHFof7kN.Thestatistical method
Analysis of Variance (ANOVA) is applied to estimate the contribution of
each optimal parameter to obtain a minimum variation in the thickness of
the cup produced and it is found that PNR, DRS and BHF contributions
are 33.736 %, 07.140 % and 54.315 % respectively
Experiments are conducted using DoE to optimise the
combinations of geometric and process parameters and levels that would
give minimum variation in the thickness of the cup produced in the deep
drawing process. To develop optimised deep drawing facilities using
Design of Experiments (DoE), the ranges for highly influencing parameters
are fixed after a thorough study of literature. The tool setup is designed for
optimization of highly influencingparametersusingDoEbasedonTaguchi
technique. The parameter ranges for highly influencing parameters fixed
are PNRfrom 5.5 to 10.5 mm, DSR from 5.5 to 10.5 mm and BHFfrom3
to 7 kN. The uniform thickness of the drawn cup is considered as output
characteristic and the variation in cup wall has to be as minimum as
possible. The three level values fixed for these parameters are 5.5 mm,
8 mmand10.5 mm for PNR; 5.5 mm, 8mm and 10.5 mm for DSR and
3 kN, 5kNand7kNforBHF.
Subsequently, experimental tests are conducted using L9
Orthogonal Array (OA) for optimisation of the process setup. Following
the DoE procedure, nine experiments are performed according to L9 OA
instead of conducting all the possible 27 experimental tests. During the
experimental tests, Aluminium alloy AA6111 blanks are considered as the
test material having 130 mm diameter and 0.9 mm thickness. In every test,
the thickness readings are measured at nine different points, radially from
the edge of the flange to the centre of a cup at the bottom. Considering
"Nominal is the Best" (NB) characteristic, The Signal to Noise (S/N)
ratios are determined using Qualitek- 4 software. The application of this
Taguchi based DoE software for optimisation of the deep drawing process
indicated the optimal values for the parameters considered, and these are
PNRof5.5 mm,DSRof5.5mmandBHFof7kN.Thestatistical method
Analysis of Variance (ANOVA) is applied to estimate the contribution of
each optimal parameter to obtain a minimum variation in the thickness of
the cup produced and it is found that PNR, DRS and BHF contributions
are 33.736 %, 07.140 % and 54.315 % respectively
maximumpunchload is linearly proportional to the blank diameter for
all successfully drawn cups and remains constant for all oversized blanks
forming into crack induced/failed cups.
As the maximumpunch load is linearly proportional to the blank
diameter, a newconceptknownasarapidmethodofdeterminationofLDR
using only three blanks of different sizes gained significance. In the rapid
determination method, the LDR values for Aluminium alloy AA6111 and
Copper C11000 material are found. Experiments are conducted with three
different size blanks, i.e., two undersized blanks of different diameters
for determining the linearity of the punch load and one oversized blank
for finding the maximum forming load at which fracture takes place.
The LDR results found in the traditional method involving testing of
several different sized blanks and the rapid method using only three
different blank sizes are compared. The results found through the rapid
determination method of LDR are in close agreement with the traditional
method.
Further, simulation tests are conducted for Aluminium alloy
AA6111 at 30 oC temperature for confirmation of experimentally found
LDRat 30 oCtemperature. The deep drawing model is constructed using
CATIA V5 and simulations are performed using PAM-STAMP 2G®, a
simulation software. It has been observed that the experimental results at
30 oC temperature for Aluminium alloy AA6111 are in close agreement
with simulation results obtained at 30 oC temperature.
It is found through this present research that the rapid
determination of LDR is quick compared to the traditional method. This
concept of finding LDR can reduce testing time and scrap in multistage
deep-drawing operations in which two or more drawing operations are
required to form a complete cup. Results of the parameter optimisation,
the experimental tests conducted determining LDR values for Aluminium alloy AA6111andCopperC11000atdifferenttemperaturesandsimulation
tests discussed and conclusions made are presented.