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Contemporary Machining Processes
advanced composites in many mechanical industries (Boujelbene et al., 2021). It
can be applied where remote control is required for dismantling tools due to dangerous environmental conditions. For instance, underwater laser-cutting techniques
with high-power fiber lasers proved to be feasible, producing less secondary waste
than other approaches, such as the waterjet and plasma cutting techniques (Oh
et al., 2021).
Laser cutting of sheet metal is usually performed from a CW laser source with a
coaxial flow of high-pressure assist-gas that removes molten material. Pulsed laser
materials processing exploits rapid deposition of laser energy, limiting heat conduction losses compared to CW exposure (Lutey et al., 2018). Laser cutting of metals
is used for forming and precise processing of shaped parts, but different materials
require some modifications of the cutting process. Mild steels can be laser-cut with
a superior edge quality compared to conventional technologies both in thin sheets
and in thick plates. Stainless or chrome-nickel steel is often laser-cut with nitrogen
assist-gas, but the maximum thickness is less than that for mild steels at equal laser
power and similar cut-edge quality. Aluminum is second after steel in terms of the
volume of industrial laser-cutting applications. Because of its quick oxidation, Al is
often laser-cut with nitrogen or air assist-gas. Titanium is usually laser-cut with an
inert assist-gas, e.g., argon, which enables finer cutting with microcracks eliminated.
Laser can cut both pure copper and copper alloys, such as bronze and brass, but
bronze is not often laser-cut because it is usually formed from castings. Oxygenassisted laser cutting of copper alloys can be performed at higher cutting speeds than
the neutral or inert gas-assisted process (Caristan, 2004). For sheet-metal cutting
operations, process planning and production planning can nowadays be automated
to some extent, so that 2D cutting operations focus on minimization of waste material (Verlinden et al., 2007). Laser-cutting techniques are largely standardized so
that various companies throughout the world achieve similar results in metal sheet
cutting in terms of efficiency, thickness, or cutting speeds.
The laser welding process is not only easily automated, but various real-time
monitoring technologies can be applied for improving welding efficiency and guaranteeing the quality of joint products. An extensive review provided by Cai, Wang
et al. (2020) distinguishes three different parts of the monitoring: pre-processing
scanning, in-process monitoring, and post-process diagnosing. The pre-process
scanning mainly focuses on the joint gap between workpieces and seam tracking
problems to ensure the central position of the laser beam spot in the gap and thus to
obtain reliable joints. The real-time in-process monitoring is concentrated on welding zone characteristics such as keyhole, molten pool, plasma, and spatters. Based on
the analysis of dynamic changes of these characteristics, the quality of a weld seam
can be adjusted using AI-based methods. The post-process diagnostics is focused on
defects like pores, cracks, spatters, surface collapses, underfills, etc., which are critical indicators of the weld seam quality. Among the various sensing techniques, the
authors present acoustic emission measurement, optical signal, and thermal signal.
Novel monitoring methods, such as X-ray imaging, in-line coherent imaging, and
magnetooptical imaging were demonstrated to achieve excellent results. However,
a welding situation can be reflected more effectively and comprehensively when
Contemporary Machining Processes
advanced composites in many mechanical industries (Boujelbene et al., 2021). It
can be applied where remote control is required for dismantling tools due to dangerous environmental conditions. For instance, underwater laser-cutting techniques
with high-power fiber lasers proved to be feasible, producing less secondary waste
than other approaches, such as the waterjet and plasma cutting techniques (Oh
et al., 2021).
Laser cutting of sheet metal is usually performed from a CW laser source with a
coaxial flow of high-pressure assist-gas that removes molten material. Pulsed laser
materials processing exploits rapid deposition of laser energy, limiting heat conduction losses compared to CW exposure (Lutey et al., 2018). Laser cutting of metals
is used for forming and precise processing of shaped parts, but different materials
require some modifications of the cutting process. Mild steels can be laser-cut with
a superior edge quality compared to conventional technologies both in thin sheets
and in thick plates. Stainless or chrome-nickel steel is often laser-cut with nitrogen
assist-gas, but the maximum thickness is less than that for mild steels at equal laser
power and similar cut-edge quality. Aluminum is second after steel in terms of the
volume of industrial laser-cutting applications. Because of its quick oxidation, Al is
often laser-cut with nitrogen or air assist-gas. Titanium is usually laser-cut with an
inert assist-gas, e.g., argon, which enables finer cutting with microcracks eliminated.
Laser can cut both pure copper and copper alloys, such as bronze and brass, but
bronze is not often laser-cut because it is usually formed from castings. Oxygenassisted laser cutting of copper alloys can be performed at higher cutting speeds than
the neutral or inert gas-assisted process (Caristan, 2004). For sheet-metal cutting
operations, process planning and production planning can nowadays be automated
to some extent, so that 2D cutting operations focus on minimization of waste material (Verlinden et al., 2007). Laser-cutting techniques are largely standardized so
that various companies throughout the world achieve similar results in metal sheet
cutting in terms of efficiency, thickness, or cutting speeds.
The laser welding process is not only easily automated, but various real-time
monitoring technologies can be applied for improving welding efficiency and guaranteeing the quality of joint products. An extensive review provided by Cai, Wang
et al. (2020) distinguishes three different parts of the monitoring: pre-processing
scanning, in-process monitoring, and post-process diagnosing. The pre-process
scanning mainly focuses on the joint gap between workpieces and seam tracking
problems to ensure the central position of the laser beam spot in the gap and thus to
obtain reliable joints. The real-time in-process monitoring is concentrated on welding zone characteristics such as keyhole, molten pool, plasma, and spatters. Based on
the analysis of dynamic changes of these characteristics, the quality of a weld seam
can be adjusted using AI-based methods. The post-process diagnostics is focused on
defects like pores, cracks, spatters, surface collapses, underfills, etc., which are critical indicators of the weld seam quality. Among the various sensing techniques, the
authors present acoustic emission measurement, optical signal, and thermal signal.
Novel monitoring methods, such as X-ray imaging, in-line coherent imaging, and
magnetooptical imaging were demonstrated to achieve excellent results. However,
a welding situation can be reflected more effectively and comprehensively when