Blog left sidebar

Technical paper

Continuous (tandem) cold rolling process with applying abaqus software

Mohammad Reza Moghoomi, Farnaz Ghaderi

Daneshpajoohan Higher Education Institute, Iran

Correspondence: Mohammad Reza Moghoomi, Department of Mechanical Engineering, Daneshpajoohan Higher Education Institute, Isfahan, Iran, Email

  • Volume 2 Issue 2
  • Received: December 03, 2017
  • Published: December 06, 2017

Rolling industry due to high production efficiency rate regarded as the most popular and the most prosperous metal production process especially steel, in the world. Among rolling processes methods, metal's rolling in industry is an important position due to exposed precise control product's dimensions and quality. So in this article, it is tried to investigate process computation and in continue, with applying ABAQUS software analysis this effective parameters and regarded output and study its results.


F → forces applied to the roller mill (rolling mill) (N); Hin → input sheet thickness (mm); K → work hardening coefficient; M → rolling torque (nm); Pm → mean rolling pressure (MPA); R → roller radius (mm); R' → roller radius after deformation (Mm); R → the percentage of sheet thickness reduction; W → sheet width (mm); Y︠ → mean tensile stress (Mpa); Ε0 → initial strain; Μ → friction coefficient; Σbt → tension after tensile (Mpa); Σft → tension be for tensile (Mpa); Σm → mean tension (Mpa); Ω → angular velocity roller (Rad/S)


The most important purpose of cold rolling processes, in addition to obtaining appropriate mechanical features, is to achieve very low and more precise thicknesses', the issue that is not possible in hot rolling processes. Today, most cold rolling lines designed continuously and usually consist of 4 to 6 four-roller rolling rack. Finished surface of obtained sheets of cold rolling is Harder and more smooth than obtained sheets from hot rolling.1 Obtained sheet and Belts from cold rolling produce in different thickness of 6mm to less than 0.1mm as skein and/or sheet with mutual or tandem rolling racks. Also in cold rolling process, it can produce 25 to 90% decreasing in sheet's thickness.2 In sheet's cold rolling, like final hot rolling, it is necessary to control effective parameters on rolling. These parameters include: thickness decreasing in each stage of rolling, the whole size of thickness decreasing, existing sheet's width and thickness, thickness's uniform in sheet's with, smoothness of sheet's surface, imbrication operation, back and forth tensile tensions, each rack's torque and roller forces, speed and coordination among racks.2 So far, numerous efforts are done about steel formation (shaping), especially cold rolling of steel sheets. In 2001, venkada and his colleagues in research named "arrangement model for continuous cold rolling" with emphasize on crucial roles of experimental data, in addition to calculated rollers consumption. Able power with regarding the percentage of sheet's thickness decreasing and 6- racks rolling simulation, they reach to this result that performed calculations confirmed with Roberts reports.3

Venga and his colleagues in 2000 in research about optimized design in order to continuous cold rolling programming, with the purpose of tension and speed optimization, designed algorithm based on genetic optimization method that with regarding power, tension distribution and sheet's smoothness, they observed that obtained results have a good conformity with experimental experiments.4In 2008, Young and his colleagues in research named "Genetic Algorithm optimization in cold rolling", with optimization plans analysis and comparison with existing plans, optimization program performance was satisfactory. In 2009, weining and his colleagues in research named steel cold rolling texture prediction with using artificial neural network "with the aim of designing model that can simultaneously and fast predict in engineering environment.5Regarded carbon and carbide rate and decreasing rolling work as a input calculation. Their obtained research's output was indicative of parameters that confirmed with experimental data.6 Newski and his colleagues in 2004 in research named "interdependence between rolling's speed and nonlinear vibrations of roller's system introduce analytical and approximate solution with presenting nonlinear mathematic model of continuous rolling fluctuation system that their obtained results from research were comparable with practical rolling parameters.7 Vang and his colleagues in 2005 in research named "optimization of computational intelligence process based on continuous cold rolling", with introducing a smart search mechanism for optimizing planning with rolling limitations evaluation and power's tension and distribution combination function, achieve maximum safety ratio of tolled sheet. Introduced model in his research can solve multipurpose (objective) issues.8

In 2008 pitner and siman, in its research named "control of tandem (continuous) cold rolling process" introduce noble method that central rolling process with applying riccati equation.9 In 2008 Din and his colleagues used quadratic linear point-to-point method for optimizing control of continuous cold rolling. They use new strategy for controlling roller as to deal with existing limitations with designing multi-input and multi-output functions. Their results show that rolled output sheet thickness is appropriate between 0.5 to 8% than other researches and caused stability in rolling process.10 Presented picture in figure 1 shows the schematic of cold rolling process (Figure 1).

Figure 1 Cold rolling rollers schematic.

Cold rolling process analysis in ABAQUS

The method of solving cold rolling analysis problem in ABAQUS

Modeling and stimulation of rolling process by limited element soft ware’s like ABAQUS is an appropriate and most effective solution. In sheet's rolling process, sheet with initial thickness of 1.7mm passed between two rollers and it's thickness reduce to 32%mm. sheet's length (the length of sheet) regarded 1m. First Geometric model outlined in trap module. Roller is modeled as a rigid matter (material) with the radius of 261mm and enters in analysis. RP point in Figure 2 is indicative of circle's center (the center of circle) (Figure 2). In continue, regarded (desired) mechanical features are entered in y treporp environment and osldi types of a cross section are defined. With regards to roller's rigidity, we don’t need to define matter and cross section for them. Also density ratio (amount) considered equal to 7850kg/m3, Young's modulus and Poisson's ratio considered equal to 200g/p and 0.3, respectively. Table 1 shows related information to regarded metal sheet (Table 1 & 2). With entering to y/b mess A, sheet and roller assembled to each other, entered to pets' module, we entered needed time period for analysis. In rolling process, we have need to define contact behavior among sheet and roller, so entered to noicaretnl module and considered friction coefficient equals to .0.05. In Idao module, first we bound roller. Form reference point in the event of 1 and 2 according to Figure 3. We give to the bottom roller a rotational speed of 1and 10 R/t to the higher roller (Figures 3 & 4). Now create limited (finite) element on sheet in hse M module (Figure 5). Finally in boj module with time bus of defined boj, it begins to solve the process (Figure 6). Then with going to zilausivnoita module, computed output include figures, video are observable (Figures 7 & 8).

Figure 2 Overview of sheet among two rollers in trap module.

Young’s Modulus

200 Gpa = 29 mpsi

Poisson’s Ratio


Mass Density


Friction Coeff


Table 1 Information table related to material.


Yield Stress

Plastic Strain


































Table 2 Mechanical features of matter in plastic area.

Figure 3 Bound overview of sheet in the events of 1 and 2 point.

Figure 4 The bottom and the higher rotational speed.

Figure 5 Meshed sheet.

Figure 6 The view of some calculated final results.

Figure 7 The conflict between two rollers of initial sheet.

Figure 8 Sheet presentation among (between) two rollers under the effects of incoming force via rollers.

We define analysis kind (type) and appropriate solving problem selection in pet’s module. Then to determine needed outputs for instance incoming pressure by roller on sheet and/or created torque during rolling process, determine changes according to colorful contour or figures based on time (Figures 9‒12).

Figure 9 The table of incoming pressure on each sheet.

Figure 10 Existed Maximum and Minimum tension on rolled sheet.

Figure 11 The table of incoming pressure by roller on rolled sheet.

Figure 12 The table of incoming torque.

The purpose of cold rolling process is to reduce sheet's thickness under great pressure as a result; we can point to interested matter's hardness increasing, in appropriate increasing in crystal structure and increasing yield stress. In doing ABAQUS analysis operation, it is observed that the red and orange area of sheet under rolling rollers are the most tension and also the most incoming force from roller on sheet and in parts that we can see the blue and green sheet, incoming tension is lower, also incoming force amounts (rates) from roller on sheet has reverse relation with sheet's thickness rate, in fact, the lower thickness, the more force effect on sheet.


The authors declare that there are no acknowledgements regarding the publication of this manuscript.

Conflict of interest

The authors declare that there is no conflict of interests regarding the publication of this manuscript.


  1. Moshksar M. Rolling engineering principles. 3rd Ed. Iran: Shiraz University Press; 2013. 20 p.
  2. Mehdi Safari, Mohammadreza Moghoomi. Optimization of Force and Power Imposed on Continuous Tandem Cold Rolling Rollers Using a Multiple-Function Genetic Algorithm. Scientific research. 1985;2(4):1‒13.
  3. N Venkata Reddya, G Suryanarayanaa. A set-up model for tandem cold rolling mills. Journal of Materials Processing Technology. 2002;116(2‒3):269‒277.
  4. DD Wanga, WYD Yuen. Toward a heuristic optimum design of rolling schedules for tandem cold rolling mills. Engineering Applications of Artificial Intelligence. 2000;13(4):397‒406.
  5. J Yang, H Che. Genetic Algorithm-Based Optimization Used in Rolling Schedule. Journal of Iron and Steel Research. 2008;5(2):18‒22.
  6. M Winninga, A Brahmeb. Prediction of cold rolling texture of steels using an Artificial Neural Network. Computational Materials Science. 2009;46(4):800‒804.
  7. A Świątoniowskib, A Bara. Interdependence between the rolling speed and non-linear vibrations of the mill system. Journal of Materials Processing Technology. 2004;155‒156:2116‒2212.
  8. DD Wang, AK Tieu. Computational Intelligence-Based Process Optimization for Tandem Cold Rolling. Materials and Manufacturing Processes. 2005;20(3):479‒549.
  9. J Pittner, A Marwan Simaan. Control of a continuous tandem cold metal rolling process. Control Engineering Practice. 2008;16(11):1379‒1390.
  10.  John Pittner, Marwan A Simaan. Optimal Control of Tandem Cold Rolling Using A Point wise Linear Quadratic Technique With Trims. Journal of Dynamic Systems Measurement and Control. 2008;130(2):1‒11.

Citation: Moghoomi MR, Ghaderi F. Continuous (tandem) cold rolling process with applying abaqus software. Author J. 2017;2(2):37‒40.

Creative Commons License   © 2017 Moghoomi et al. This article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and build upon your work even commercially.