Laser cladding is a surface modification and advanced manufacturing process that uses a concentrated laser beam to melt deposited material together with a controlled amount of substrate material. One of its major advantages is the ability to deliver highly localized energy with relatively low overall heat input, a small heat-affected zone and limited deformation.

However, laser cladding quality depends strongly on the thermal conditions created during processing. Laser power, scanning speed and laser spot size determine how much energy reaches the processing area, while the resulting temperature field controls melt pool geometry and thermal cycles.

A numerical study using 316L stainless steel and Stellite 6 cobalt-based alloy provides a useful example of these relationships. Using an ABAQUS finite element model validated against experimental cladding geometry, the study investigated how laser power, scanning speed and multi-track processing affect the temperature field and melt pool size under relatively small heat input conditions.

What Is Heat Input in Laser Cladding?

Laser heat input describes the amount of laser energy delivered to a given processing area. In the referenced study, heat input was calculated as:

Q = P / (D × V)

where:

• Q = laser heat input, J/mm²
• P = laser power, W
• D = laser beam diameter, mm
• V = laser scanning speed, mm/s

This relationship immediately shows why laser power and scanning speed must be considered together. With the same beam diameter, increasing laser power raises heat input, while increasing scanning speed reduces it.

Heat input then affects the peak temperature, melting behavior and dimensions of the melt pool.

Why Is Temperature Control Important in Laser Cladding?

Laser cladding involves complex thermal and metallurgical processes. Heat conduction, convection, mass transfer and diffusion at the solid-liquid interface occur during formation and solidification of the melt pool.

The resulting temperature distribution directly influences the macroscopic geometry, microstructure and physical-metallurgical characteristics of the deposited layer. Numerical temperature-field analysis can therefore provide useful information for selecting and optimizing laser cladding parameters.

In practical terms, neither excessive nor insufficient thermal input is desirable. The objective is to establish a controlled melt pool capable of producing the required cladding geometry and metallurgical bonding.

Why Low Heat Input Matters in Laser Cladding

Smaller Heat-Affected Zone

Laser cladding concentrates energy within a relatively small processing region. The study shows that the material close to the laser source experiences extremely rapid heating, while regions farther from the source remain at substantially lower temperatures.

This localized thermal behavior contributes to a relatively small heat-affected region.

Controlled Thermal Influence

Reducing unnecessary heat input limits the amount of substrate exposed to high temperatures. This is particularly important when laser cladding is used for surface modification or component repair, where excessive thermal influence on the original component is undesirable.

Melt Pool Geometry Control

Heat input directly affects melt pool length, width and depth. Therefore, thermal control is also melt pool control.

The referenced simulation demonstrates that melt pool depth can be particularly sensitive to changes in laser power and scanning speed.

Numerical Simulation of the Laser Cladding Temperature Field

Numerical simulation provides a way to study temperature evolution that would otherwise be difficult to observe directly during laser processing.

Finite Element Method

The study used ABAQUS and secondary development through user subroutines to establish heat-conduction finite element models for both single-track and multi-track laser cladding.

Gaussian Heat Source Model

A Gaussian heat source model was used to represent the laser energy distribution. Process parameters were introduced through the Flux user subroutine.

Element Birth and Death Technique

For multi-track overlapping laser cladding, the researchers used an element birth and death technique to simulate the sequential formation of the deposited material.

These methods allowed the simulation to reproduce the movement of the heat source and the changing thermal field during cladding.

Materials Used in the Laser Cladding Simulation

316L Stainless Steel Substrate

The substrate material was 316L stainless steel, a material commonly used in nuclear power applications according to the study.

Its solidus and liquidus temperatures were specified as approximately 1,420°C and 1,460°C, respectively.

Stellite 6 Cobalt-Based Alloy

The laser cladding material was Stellite 6 cobalt-based alloy powder.

Its solidus temperature was 1,265°C, while its liquidus temperature was 1,354°C. Temperature-dependent thermal properties were incorporated into the finite element model.

This 316L/Stellite 6 combination provides the material basis for the simulation results discussed below.

Laser Cladding Simulation Model and Boundary Conditions

The finite element model measured 30 × 30 × 3 mm and used hexahedral elements. The minimum mesh size was:

0.3 × 0.3 × 0.2 mm

The initial temperature of both substrate and cladding layer was set to 20°C. Heat exchange with the surrounding environment was mainly represented by convection, with a convection heat-transfer coefficient of 20 W/(m²·°C).

These conditions define the specific numerical model used in the study and should not be interpreted as universal settings for every laser cladding simulation.

Process Parameters Used in the Simulation

The study investigated a relatively small heat-input range using:

Laser power: 1,100, 1,200, 1,300 and 1,400 W
Scanning speed: 6, 8 and 10 mm/s
Laser spot diameter: 2 mm

The results therefore describe the thermal behavior within this particular material system, parameter range and simulation model.

Validation of the Laser Cladding Simulation Model

A useful simulation must reasonably represent the actual process.

The researchers therefore compared the simulated melt pool geometry with an experimental cladding cross-section.

The experimental layer had a width of 2.57 mm and height of 0.74 mm, while the simulation predicted 2.59 mm and 0.70 mm, respectively.

The reported errors were:

Width error: 0.8%
Height error: 5.4%

The researchers considered this agreement sufficient to use the model for subsequent temperature-field analysis.

How Does the Temperature Field Develop During Laser Cladding?

For the single-track analysis, the study examined a case using 1,100 W laser power and 8 mm/s scanning speed.

At the beginning of cladding, the temperature in the laser interaction zone rose rapidly from 20°C to approximately 2,465°C. As processing continued, the temperature field became relatively stable, with a maximum temperature of approximately 3,210°C.

The temperature distribution spread outward in an approximately elliptical shape. The area ahead of the heat source showed a stronger temperature gradient, while temperature changes behind the moving source were more gradual.

Temperature Gradient Around the Laser Melt Pool

Temperature Ahead of the Laser

The region immediately ahead of the moving heat source experiences a sharp increase in temperature as the laser approaches.

Temperature Behind the Laser

After the laser passes, heat dissipates into the surrounding material and the temperature decreases. The thermal field therefore develops a characteristic trailing distribution behind the moving laser.

Elliptical Temperature Distribution

The temperature contours observed in the simulation spread around the cladding region in an approximately elliptical pattern.

Rapid Heating and Cooling

This behavior illustrates one of the defining thermal characteristics of laser cladding: highly localized rapid heating followed by rapid cooling after the heat source moves away.

Thermal Cycles at Different Depths

The researchers selected six virtual temperature measurement points, A through F, at 0.5 mm intervals along the depth direction.

The point nearest the cladding layer experienced the highest peak temperature. As the distance from the cladding region increased, peak temperature decreased.

The heating and cooling rates also became slower, producing smoother and less pronounced temperature peaks deeper inside the workpiece.

This illustrates how strongly the thermal influence of laser cladding decreases with distance from the processing zone.

Effect of Laser Power on Cladding Temperature

Laser power has a direct influence on energy input.

With other parameters unchanged, the simulation increased laser power from 1,100 W to 1,400 W.

Peak temperature increased from:

3,209°C → 4,012°C

The study therefore found a positive relationship between laser power and peak temperature within the investigated range.

Higher laser power transfers more energy to the material during the same period, increasing the thermal energy absorbed by the cladding region.

Effect of Laser Power on Melt Pool Size

Increasing laser power also enlarged the simulated melt pool.

An especially important observation is the much larger relative change in melt pool depth.

Within this simulation, increasing laser power affected penetration depth more strongly than melt pool width.

Why More Laser Power Is Not Always Better

Increasing power can enlarge the melt pool, but maximum power is not the objective of laser cladding.

Excessive Laser Power

The study notes that excessive laser power may overheat the cladding layer and can even result in material vaporization.

Insufficient Laser Power

If laser power is too low, penetration may be insufficient and the cladding layer may not form a satisfactory metallurgical bond with the substrate.

Laser power must therefore be selected according to the complete process rather than simply maximized.

Effect of Scanning Speed on Cladding Temperature

Scanning speed produces the opposite trend.

At a constant laser power of 1,100 W, scanning speed was increased from 6 to 10 mm/s.

Peak temperature decreased from:

3,374°C → 3,017°C

A higher scanning speed reduces the interaction time between the laser and a given processing area, reducing the amount of energy absorbed locally.

Effect of Scanning Speed on Melt Pool Size

Higher scanning speed also reduced melt pool dimensions.

Again, melt pool depth showed the strongest relative response.

Why Faster Laser Cladding Is Not Always Better

Higher processing speed can improve productivity, but speed cannot be considered independently of heat input.

If the scanning speed is too low, excessive energy absorption may raise the substrate temperature too much and cause overheating.

If scanning speed is too high, the powder and substrate may not melt sufficiently, which can negatively affect bonding and cladding quality.

Therefore, maximum cladding speed is not necessarily the best process speed.

Relationship Between Laser Power, Scanning Speed and Heat Input

The results can be summarized using the heat-input relationship:

Q = P / (D × V)

Increasing Laser Power

When spot size and scanning speed remain unchanged:

Laser Power ↑ → Heat Input ↑ → Peak Temperature ↑ → Melt Pool Size ↑

Increasing Scanning Speed

When power and spot size remain unchanged:

Scanning Speed ↑ → Heat Input ↓ → Peak Temperature ↓ → Melt Pool Size ↓

These relationships were observed within the parameter range investigated in the study.

The important engineering point is that laser power and scanning speed must be matched rather than optimized independently.

Single-Track vs Multi-Track Laser Cladding

Single-track experiments are useful for understanding fundamental process behavior, but industrial laser cladding frequently requires multiple overlapping tracks to cover a larger surface.

Multi-track processing introduces another important variable:

heat accumulation.

The thermal condition of the fifth track is not necessarily the same as that of the first track, even when identical laser parameters are used.

Heat Accumulation in Multi-Track Laser Cladding

The simulation showed progressive heat accumulation during continuous multi-track processing.

When the laser reached the midpoint of the third track, heat conduction from previous processing increased the substrate temperature from approximately 200°C to more than 300°C.

By the midpoint of the fifth track, accumulated heat had raised the substrate temperature to above 700°C.

This demonstrates why thermal history becomes increasingly important during large-area laser cladding.

Preheating Effect Between Adjacent Cladding Tracks

Each completed track leaves residual heat in the substrate.

Consequently:

Previous Track → Residual Heat → Preheating of the Next Track

The study concluded that heat absorbed during the preceding cladding track effectively preheated the material before processing of the following track, increasing both substrate and melt pool temperatures.

Therefore, multi-track cladding cannot be treated simply as a repetition of identical isolated single tracks.

Thermal Cycling in Multi-Track Laser Cladding

A material point can also experience repeated thermal cycles.

At the monitored point in the first track, temperature rapidly increased to approximately 3,250°C when the heat source approached. It then fell rapidly as the laser moved away.

Subsequent tracks generated additional temperature peaks at the same location before the temperature gradually stabilized.

This repeated heating is an important characteristic of overlapping laser cladding.

Why Multi-Track Laser Cladding Requires Thermal Management

The multi-track results demonstrate that laser parameters cannot be evaluated only from a single-track condition.

During continuous processing:

substrate temperature changes, adjacent tracks interact thermally, and repeated thermal cycles occur.

For large-area cladding, heat accumulation should therefore be considered together with laser power, scanning speed and track arrangement.

The paper does not specify a universal interpass-temperature limit, so such a value must be determined for the particular material and application.

How Numerical Simulation Helps Optimize Laser Cladding Parameters

Finite element simulation can help visualize thermal behavior that is difficult to measure throughout the entire workpiece during actual processing.

A validated model can provide information about:

• temperature distribution and peak temperature;
• melt pool length, width and depth;
• temperature gradients through the substrate;
• heating and cooling cycles;
• heat accumulation during multi-track cladding.

The study also notes that temperature-field analysis can provide a theoretical basis for subsequent calculations involving stress, strain and microstructural fields.

Simulation therefore provides a useful tool for narrowing the process-development range before experimental verification.

Key Factors for Controlling Heat Input in Laser Cladding

Laser Power

Higher power increases energy input and, within the studied conditions, increases peak temperature and melt pool dimensions.

Scanning Speed

Higher scanning speed reduces interaction time and lowers the energy absorbed per unit area.

Laser Spot Diameter

Spot diameter is included directly in the heat-input equation and influences the distribution of laser energy over the processing area.

Material Thermal Properties

Thermal conductivity, density, specific heat, solidus temperature, liquidus temperature and latent heat influence how a material responds to laser energy. The model therefore used temperature-dependent thermophysical properties for both 316L and Stellite 6.

Multi-Track Heat Accumulation

For continuous multi-track cladding, residual heat from previous tracks changes the thermal condition encountered by subsequent tracks.

These factors should be considered as an interacting system rather than isolated settings.

Practical Lessons for Laser Cladding Process Development

The numerical results provide three useful principles for laser cladding process development.

First, avoid excessive heat input. Too much energy can produce excessive temperatures and potentially cause overheating or vaporization.

Second, avoid insufficient heat input. Too little energy can produce insufficient melting and penetration, reducing the ability to form a satisfactory metallurgical bond.

Third, consider accumulated heat during continuous processing. A parameter set that works for a single track may experience different thermal conditions after multiple adjacent tracks have been deposited.

The goal is therefore not simply high power, low power, high speed or low speed. It is a stable thermal window appropriate for the material and required cladding geometry.

Limitations of Laser Cladding Temperature Simulation

Numerical simulation is useful, but its results must be interpreted within the assumptions of the model.

This study primarily established a heat-conduction finite element model for a specific 316L/Stellite 6 material system and a defined range of laser powers, scanning speeds and spot size.

Actual laser cladding involves additional physical phenomena, including melt pool convection, mass transfer and solid-liquid interface behavior. The paper identifies these complexities but does not model all of them as a complete multiphysics system.

For industrial process development, simulation should therefore be combined with experimental validation.

Conclusion

Heat input is one of the fundamental factors controlling the laser cladding process because it directly influences the temperature field and melt pool geometry.

The ABAQUS simulation of 316L stainless steel with Stellite 6 cladding showed that, within the investigated conditions:

Increasing laser power increased peak temperature and melt pool size, while increasing scanning speed reduced both. Melt pool depth showed a particularly strong response to these parameter changes.

Multi-track laser cladding introduced another important effect: thermal accumulation. Heat remaining from previous tracks preheated subsequent processing areas, while individual locations experienced repeated thermal cycles as neighboring tracks were deposited.

For practical laser cladding, this means that power and scanning speed should not be optimized independently. Laser power, scanning speed, spot size, material thermal properties and multi-track heat accumulation must be considered together to establish a stable process window with controlled thermal input and melt pool geometry.