Figure 4: Fixture for the plan plates (left) and fixture with component (right).

To obtain temperature measurements, both thermocouples and high-resolution infrared (IR) emission measurements were used. Six thermocouples were positioned perpendicular to the welding direction. The first gauge was positioned as close to the melted zone as possible at a distance of 4mm from the center of the weld. The second and third were positioned 0.5mm radially from the previous one. The remaining gauges were positioned 1.0mm radially from the preview one. The sampling frequency for all thermocouples was 270Hz. The IR-camera used is a VARIOSCAN High Resolution, from JENOPTIK, Laser, Optik, Systeme Gmbh, which works in the IR radiation spectrum of 8 - 12μm. The camera was used both in a line scan mode with a scanning frequency of 270Hz as well as in a full-frame mode with a frequency of 1Hz. The analysis of the IR measurements were made using the IRBIS Plus software provided by JENOPTIK. A comparison between the IR results with the thermocouple was made. Different techniques to soot the plane plates were evaluated to reduce emissivity -dependency in the IRmeasurements. Finally a method using an acetylene flame was selected. This technique was also used on the production part.

RESULTS AND DISCUSSION

The results of the robot programs made off-line showed a high accuracy and very little finetuning after calibrations had to be made. The method appears as a powerful tool, particularly in small batch production such as within the aerospace industry.

The computational time from the parallel calculation was 34hrs for the production part. The predicted fusion zone was 5.0mm on the top-side and 4.8mm at the root-side which agreed well with measured widths.

The predicted and IR-measured temperature histories in the point located 4mm and 7mm from the center of the weld are given in Figure 5. The IR-measurements were performed twice, corresponding to the captions IR1 and IR2 in the Figure 5. There is an excellent agreement between predictions and measurements for the 4.0mm case both in peak temperature and in the cooling history. The agreement for the 7.0mm case is not as good as for the 4mm case but still good. An example of the comparison between the thermocouple and the IR-measurements are given in Figure 6. There is a very good agreement, which implies that that the technique to soot worked well. The reason why data is lacking in the IR-curve is that the camera-system collects data during a maximum time interval of 20 seconds. This data then have to be written to disk before a new sampling sequence can be gathered. A more extensive evaluation between thermocouple and IR measurements is planned.

Figure 5: Predicted and measured temperature-time histories, 4mm (left) and 7mm (right) from the weld centerline.

Figure 6: Comparison between thermocouple and IR measured temperatures.

The overall conclusion from the simulations is that the model predicts the thermal cycle very well. However, further research is needed until welded structures can be optimized without experiments. The temperature predictions are naturally dependent on the heat transfer coefficients (boundary conditions in Table 1). To determine these values, experiments are required since the heat flow can be convection dependent, specifically if the workpiece and fixturing are small. Also, the heat source parameters (in the expression for q above) have to be calibrated by experiments. The on-going work at the laboratory at University Trollhättan/Uddevalla to numerically model the magnetohydrodynamics of the arc and to predict the shape of the molten pool by the use of Computational Fluid Dynamics (CFD) techniques seems as a promising tool to compute the heat source parameters without experiments. Such a model will establish a direct relationship between the welding current, speed, voltage and the shape of the molten zone, which can be used as a boundary condition in the temperature predictions in the solid region. Such model will also increase the knowledge of the stirring of the weld pool, the weld pool surface shape and the physics of the arc.

Several extensions of the modeling work described in this article are possible. The simulations can be extended to compute residual stresses, distortion and in the longer term to predict fracture strength and fatigue life of a structure. To extend the modeling work to include filler wire and pulsed current would also be valuable.

SUMMARY AND CONCLUSIONS

An engineering method and a simulation tool to define robot trajectories and to predict thermal histories on parts with complex geometries have been developed. The method was evaluated on a part with a complex shape where robot weld paths were defined off-line, and automatically

downloaded to a FEM-model where transient temperatures were predicted. These predictions were compared with experimental measurements using both thermocouple and infrared emission measurements and good agreement was found. The described method provides a promising means to construct and optimize torch trajectories and process parameters off-line. Using this system, thermal histories can be predicted on complex shaped parts and thereby resulting changes in microstructure and mechanical properties be estimated. The models used may after futher development enable the optimization of welding processes, thus increasing productivity and reducing the need of weld trials.

ACKNOWLEDGEMENT

The authors wish to acknowledge the guidance in the temperature measurements of Per Henrikson (Volvo Aero Corporation), and the assistance in the laboratory by Xavier Guterbaum (University of Trollhättan/Uddevalla) and Börje Nordin (Volvo Aero Corporation). Appreciation is expressed to Peter Jonsson of Volvo Aero Corporation for providing samples for this research and to Anita Hansbo of University of Trollhättan/Uddevalla for linguistic revision. The work was funded by the Foundation for Knowledge and Competence Development and EC Structural Founds.

REFERENCES

1. Eagar T. W., Tsai, N. S. 1983. Temperature Fields Produced by Traveling Distributed Heat Sources. American Welding Society Journal 62(12) 346-s to 355-s.

2. Gu, M.; Goldak, J.; Hughes, E. 1993. Steady state thermal analysis of welds with filler metal addition. Canadian Metallurgical Quarterlv. 32 (1): 49-s to 55-s.

3. Kou, S.; Le Y. 1983. Three-dimensional heat flow and solidification during Autogenous GTA Welding of Aluminum Plates. Metallurgical Transactions A. 14A: 2245-s to 2253-s.

4. Radej, D. 1992 Heat Effects of Welding: Berlin: Springer Verlag.

5. Goldak, J.; McDill, M.; Oddy, A.; House, R.; Chi, M.; Bibby, M. 1987. Computational Heat Transfer for Weld Mechanics. Proc. of Int. Conf. on Trends in Welding Research, Advances in Welding Science and Technology. Eds S. A. David: 15-20. Metals Park ASM Int.

6. Jonsson, M.; Karlsson, L; Lindgren, L.E. 1985. Deformation and Stresses in Butt Welding of Large Plates with Special References to the Material Properties, J. of Eng. Mat. And Tech. 107: 265-s to 270-s.

7. Lindgren, L.E.; Karlsson, L. 1988. Deformation and Stresses in welding of Shell Structures. Int. J. for Numerical Methods in Eng. 25: 635-s to 655-s.

8. Bolmsjö, G.; Olsson, M.; Brink, K. 1997. Off-line programming of GMAW robotic systems - a case study. Int. J. for the Joining of Materials, 9 (3): 86-s to 93-s.

9. Buchal, R.O.; Cheras, D.B.; Sassani, F.; Duncan J.P. 1989. Simulated Off-Line Programming

of Welding Robots. Int. J. of Robotics Research 8 (3): 31-s to 43-s.

10. Bolmsjö, G. 1999. Programming robot welding system using advanced simulation tools. Proc. of the International Conf. on the Joining of Materials JOM-9, 284-291. May 16-19, 1999, Helsingør, Denmark.

11. Walter S. 1994. Simulation and Calibration for Off-line Programming of Industrial Robots. Proc. of Computer Technology in Welding: Paper 54. Paris 15-16 June.

DYNAMIC MODELING OF GTAW FOR RAPID MANUFACTURING

Z. Jandric, I. S. Kmecko, R. Kovacevic*

ABSTRACT

A new parameter referred to as the geometrical factor was defined to reflect on the geometrical configuration around the molten pool, and an expression for heat conduction dissipation through the workpiece was established. The weld bead width, height, depth of penetration, and the weld bead cross-sectional area, were experimentally determined for different combinations of the welding currents, workpiece velocity, the filler metal flow rates, and for different geometrical configurations of the weald bead. The open-loop controller for the gas tungsten arc welding (GTAW) process based on the developed model was designed and experimentally tested by controlling the metal layer deposition process on top of a workpiece with complex geometrical features, such as conformal channels, edges, and corners.

INTRODUCTION

Rapid prototyping (RP) is the most common name given to a host of related technologies that are used to fabricate physical objects directly from CAD data sources. These methods are unique in that they add and bond material in layers to form objects. Such systems are also generally known as Freeform Fabrication (FFF), solid freeform fabrication (SFF) and Layered Manufacturing. The major advantages of the RP technologies are that:

Objects can be formed with any geometric complexity or intricacy without the need for an elaborate machine setup or final assembly;

- Rapid prototyping systems reduce the construction of complex objects to a manageable, straightforward, and relatively fast process.

The materials used in rapid prototyping are limited and dependent on the production method chosen. Non-metal materials such as plastics, ceramics, waxes, and papers were almost exclusively used for many years. Parts made of these materials can not be used to test if the design of the parts meets the mechanical property requirements. Deposition by welding (DBW) enables the direct production of the metallic parts. The use of welding for creating free-standing shapes was first used in Germany in the 1960's (Ref. 1). Other work in this area has been undertaken by Babcock and Wilcox Co. who were working mainly on large components produced in an austenitic material. Also, work by Rolls Royce has centered on investigating the technique as a means of reducing the waste levels of expensive high performance alloys that can occur in conventional processing. Lately, work on 3D welding has also been in progress at the University of Nottingham, the United Kingdom and Southern Methodist University, Dallas, Texas.

Research Center for Advanced Manufacturing

Southern Methodist University, 1500 International Pkwy. Suite #100, Richardson, TX 75081
*Corresponding author- tel.: 214-768-4865, Email: kovacevi@engr.smu.edu

Gas tungsten arc welding has many properties that makes it very attractive for the DBW such as: the wire feeding rate does not depend on the welding current; it is possible to completely stop the deposition process while keeping the arc on; the wire can be fed directly to the molten pool to let the surface tension to evenly spread the liquid metal; and the presence of the previously deposited bead will not affect the stability of the arc, etc. To make GTAW even more suitable for DBW, a constant heat input and cooling rate should be maintained during the deposition process in order to achieve a homogeneous crystallization and transformation structure throughout the whole workpiece mass, and to obtain the uniform geometry of weld beads across the deposited layer.

As mentioned, a major advantage of RP is the building of the 3D part with the complex geometrical features. Depositing layers above the complex geometrical features directly affect the heat transfer conditions, since the surrounding mass of the material is rapidly changed with the X-Y coordinates. Though, when the weld bead is deposited near the edges or above the channels, any excessive heat input will melt the underlying geometry together with a filler metal - the shape of the 3D part will be destroyed. It is not possible to successfully use the same heat input for depositing the weld bead over the changing volume of substrate. Clearly, heat input is strongly correlated to the geometry of the part (Ref. 2). In order to keep a uniform cooling rate, and subsequently, the uniform mechanical properties of the welded substrate, the heat input must be adjusted for each instance according to the mass of the surrounding material. A new parameter referred to as the geometrical factor (EG) was designed to reflect on the geometrical configuration around the molten pool. Since the geometry of the built part is known, the geometrical factor can be calculated in advance and that represents the base for the open-loop controller.

To verify the correlation between the geometry of the part and the weld-bead width, height, depth of penetration for different combinations of the welding currents, welding speed, and the filler metal feeding speed, the number of experiments were designed and performed. An accurate dynamic model and an expression for the heat conduction dissipation through the workpiece were established. A number of researchers (Ref. 3-8) modeled the welding process without taking in consideration the geometry of the substrate. In this paper, an expression is presented that balances the mass and energy flow through the controlled volume set around the molten pool including the net heat input, filler metal feeding speed, welding speed, and geometrical factor. The open-loop controller based on this model is experimentally tested, by controlling the metal layer deposition process on top of the workpiece with complex geometry.