Effect of laser welding parameters on the heat input and weld-bead profile
By K. Benyounis, A. Olabi, M. Hashmi. 2005
442 citations recorded by the source corpus.
Abstract Laser butt-welding of medium carbon steel was investigated using CW 1.5 kW CO 2 laser. The effect of laser power (1.2–1.43 kW), welding speed (30–70 cm/min) and focal point position (−2.5 to 0 mm) on the heat input and the weld-bead geometry (i.e. penetration ( P ), welded zone width ( W ) and heat affected zone width ( W HAZ )) was investigated using response surface methodology (RSM). The experimental plan was based on Box–Behnken design. Linear and quadratic polynomial equations for predicting the heat input and the weld-bead geometry were developed. The results indicate that the proposed models predict the responses adequately within the limits of welding parameters being used. It is suggested that regression equations can be used to find optimum welding conditions for the desired criteria.
Subfields: Computational Mechanics, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/147ae16c85f26f76c984494680500467f6fe4c6e
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In Computational Mechanics
In Mechanical Engineering
Citations in the corpus
- Revisiting fundamental welding concepts to improve additive manufacturing: From theory to practice (2020, background): “The energy efficiency, η, depends on the welding process and can vary from about 95% for electron beam [34] and up to 80% for laser [62], while it is lower for gas metal arc welding (30–50%) [63].”
- A simple methodology for predicting laser-weld properties from material and laser parameters (2011, methodology): “Laser and material specific processing windows have been reported (Steen and Courtney 1979, Benyounis et al 2005, Ion 2005), and numerical modelling has been used to validate experimental and theoretical results (Kaplan 1994, Rai et al 2007).”
- Optimization of different welding processes using statistical and numerical approaches - A reference guide (2008, methodology): “[22] have used the previous models [21] to optimize the process.”