generally include improved weld quality, increased prod- uctivity, reduced weld costs, and increased repeatable consistency of welding (Lane 1987)。

Robots in arc welding

Welding is an integral part of advanced industrial manu- facturing and robotic welding is considered the main symbol of modern welding technology (Cui et al。 2013)。 In the earliest applications of robotic welding, so-called first- generation robotic welding systems, welding was per- formed as a two-pass weld system, in which the first pass was dedicated to learning the seam geometry  and was then followed by the actual tracking and welding of the seam in the second pass。 With developments in technol- ogy came the second generation of robotic welding systems, which tracked the seam in real time, perform- ing simultaneously the learning and the seam-tracking phases。 The latest technology in robotic welding is third-generation systems, in which the system not only operates in real time but also learns  the  rapidly chan- ging geometry of the seam while operating within un- structured environments (Pires et al。 2006)。 Figure 2 shows the major components of a robotic arc welding system (Cary and Helzer  2005)。

The following sections briefly discuss some of the key aspects of robotics in welding  technology。

Robotic configurations

Robots can be categorized based on criteria like degrees of freedom, kinematics structure, drive technology, work- space geometry, and motion characteristics (Tsai 2000)。 In selection of robots for a specific application, all of these factors need to be considered。 Based on the workspace geometry, robots with revolute (or jointed arm) configur- ation are the most commonly used type in industrial ro- botic arc welding (Ross et al。 2010)。 Figure 3 illustrates an example of a revolute configuration robot。

Phases in welding operations

The welding operation consists of three different phases that need critical consideration in designing a fully auto- mated robotic welding system to achieve good perform- ance and weld quality (Pires et al。 2006):

Preparation phase In this phase, the weld operator sets up the parts to be welded, the apparatus (power source, robot, robot program, etc。) and the weld parameters, along with the type of gas and electrode wires。 When CAD/ CAM or other offline programming is used, a robot weld pre-program is available and placed online。 Consequently, the robotic program might only need minor tuning for calibration, which can be easily done by the weld operator performing selected online simulations of the process。

Robotic programming modes

Different methods exist for teaching or programming a robot controller; namely, manual methods, online programming (walk-through, lead-through), and offline programming。 Manual methods are primarily used for pick-and-place robots and are not used for arc welding robots (Cary and Helzer  2005)。

Welding phase Automatic equipment requires the same capabilities as manual welding, i。e。, the system should be capable of maintaining a torch  orientation  that follows the desired trajectory (which may be different from planned), performing seam tracking, and changing weld parameters in real time, thus emulating the adaptive behavior of manual welders。

Analysis phase The analysis phase is generally a post- welding phase where the welding  operator  examines the obtained weld to ascertain if it is acceptable  or whether changes are required in the previous  two phases。 Use of advanced sensors, such as 3D laser cam- eras, enables execution of this phase online during the welding phase。

Online programming This category of robotic program- ming includes lead-through and walk-through program- ming。 Use of the manual online programming method requires no special hardware or software on-site  other than that which is used for  the  manufacturing process。 The major drawback of online programming is that it is quite inflexible and it is only able to control simple robot paths (Pan et al。 2012a)。 In the walk-through method, the operator moves the torch manually through the desired sequence of movements, which are recorded into the memory for playback during welding。 The walk-through method was adopted in a few early welding  robots (Cary and Helzer 2005) but did not gain widespread use。 The conventional method for programming welding ro- bots is online programming with the help of a teach pen- dant, i。e。, lead-through programming。 In  this approach, the programmer jogs the robot to the  desired  position with the use of control keys on the teaching pendant and the desired position and sequence of motions are re- corded。 The main disadvantage of the online teaching method is that the programming of the robot  causes breaks in production during the programming phase (McWhirter 2012)。