# Effect of Scanning Strategy in the L-PBF Process of 18Ni300 Maraging Steel

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

#### 1.1. Effect of Energy Input in L-PBF Processing

#### 1.2. The Shortcomings of Andrew Number as a Sufficient Measure for Process Control

^{3}. Furthermore, it has been concluded that the manufacturing time is influenced by laser speed and layer thickness, with the layer thickness having a more significant impact on the manufacturing time than the laser speed [16].

^{3}. Considering a volume of 10

^{−6}m

^{3}, the total length of the scanned tracks could easily reach 3 km. Hence, there is a high probability of defect formation within the process [46]. The scanning strategy primarily affects the distribution of heat and temperature. Generally, shorter scan vectors are beneficial to reduce residual stresses and improve mechanical properties [23,39,40,47]. Island, helix and fractal scanning strategies usually have a shorter scan vector. Scanning direction and sequences are also important [48] and the right choice could reduce heat accumulation and temperature gradient. Sometimes, remelting is beneficial to obtain fine microstructure, good mechanical properties and reduced residual stresses [49,50,51,52].

## 2. Experimental

#### 2.1. Materials

^{®}1556.074), whose nominal and certified chemical compositions (wt.%) are reported in Table 1.

_{50}= 12 µm and the diameter corresponding to 95% cumulative particle size distribution was D

_{95}= 21 µm. The powders were characterized by an apparent density equal to 3.50 g/cm

^{3}(ASTM B 212) and flowability in the range 15–25 s/50 g (ASTM B 213), as reported in the datasheet from Höganäs.

#### 2.2. Process Planning and Variation

^{3}and P = 160 W respectively, based on the results of previous optimization and investigations. Scanning speed (v) and hatch spacing (h) were changed in a dependent way to keep constant the energy density. Three scanning strategies, schematically shown in Figure 2, were considered: parallel stripes (a), chessboard (b) and hexagonal (outside-in verse) (c). The stripes scanning pattern is conventional and straightforward, the chessboard pattern involves two types of regions with 90° symmetry and the hexagonal pattern has a 60° symmetry. Regarding the hexagonal strategy, the outside-in method was chosen because it could theoretically lead to compressive and beneficial residual stresses in the as-built specimens [53].

#### 2.3. Characterization

#### 2.3.1. Sample Dimension

#### 2.3.2. Average Surface Roughness Ra

#### 2.3.3. Density

#### 2.3.4. Microscopy

#### 2.3.5. Nano Hardness

## 3. Results

#### 3.1. External Diameter

#### 3.2. Average Surface Roughness Ra

#### 3.3. Density

#### 3.4. Nano-Hardness

## 4. Discussion

#### 4.1. External Diameter

#### 4.2. Average Surface Roughness Ra

#### 4.3. Density

#### 4.4. Nano-Hardness

## 5. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Appendix A. Details of the ANOVA Analysis

#### Appendix A.1. ANOVA Analysis of the External Diameter

(a) ANOVA for Reduced Linear model Response 1: Diam (Ave). | ||||||

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Comment |

Model | 0.0185 | 2 | 0.0092 | 4.65 | 0.0197 | significant |

D-Scan pattern | 0.0185 | 2 | 0.0092 | 4.65 | 0.0197 | significant |

Residual | 0.0476 | 24 | 0.002 | - | - | - |

Cor Total | 0.0661 | 26 | - | - | - | - |

(b) ANOVA Quality measures for Reduced Linear model Response 1: Diam (Ave). | ||||||

Entity | Value | Entity | Value | |||

Std. Dev. | 0.0445 | R^{2} | 0.2793 | |||

Mean | 10.22 | Adjusted R^{2} | 0.2192 | |||

C.V.% | 0.4358 | Predicted R^{2} | 0.0878 | |||

- | - | Adeq Precision | 3.9327 |

^{2}equal to 0.0878 and the Adjusted R

^{2}equal to 0.2192, so, being the difference less than 0.2, there is no significant effect from grouping the results.

^{2}, equal to 0.2793.

- -
- SP is 1 for the stripes pattern, otherwise it is equal to 0.
- -
- CP is 1 for the chessboard pattern, otherwise it is equal to 0.
- -
- HP is 1 for the hexagonal scanning strategy, otherwise it is 0.

**Figure A1.**Statistical quality assertion: (

**a**) Half-Normal plot vs. Externally studentized residuals for random error check, (

**b**) Residuals vs. predicted value for independent residuals, (

**c**) Residual vs. run for the absence of variation from printing location, (

**d**) Cook’s distance plot for identification of outliers and (

**e**) Box-Cox plot to identify any need of a transformation of the response.

#### Appendix A.2. ANOVA Analysis of the Average Surface Roughness Ra

(a) ANOVA for Reduced Linear model Response 1: Average surface roughness Ra. | ||||||

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Comment |

Model | 31.78 | 2 | 15.89 | 7.44 | 0.0031 | significant |

D-Scan pattern | 31.78 | 2 | 15.89 | 7.44 | 0.0031 | significant |

Residual | 51.26 | 24 | 2.14 | - | - | - |

Cor Total | 83.03 | 26 | - | - | - | - |

(b) ANOVA Quality measures for Reduced Linear model Response 1: Average surface roughness Ra. | ||||||

Entity | Value | Entity | Value | |||

Std. Dev. | 1.46 | R^{2} | 0.3827 | |||

Mean | 15.28 | Adjusted R^{2} | 0.3312 | |||

C.V.% | 9.56 | Predicted R^{2} | 0.2187 | |||

- | - | Adeq Precision | 5.4346 |

^{2}equal to 0.2187 and the Adjusted R

^{2}equal to 0.3312, so, being the difference less than 0.2, there is no significant effect from grouping the results. However, the Adeq Precision is equal to 5.435, exceeding the required threshold of 4.

_{a}) (µm) was:

- -
- SP is 1 for the stripes pattern, otherwise it is equal to 0.
- -
- CP is 1 for the chessboard pattern, otherwise it is equal to 0.
- -
- HP is 1 for the hexagonal scanning strategy, otherwise it is 0.

**Figure A2.**Statistical quality assertion: (

**a**) Half-Normal plot vs. Externally studentized residuals for random error check, (

**b**) Residuals vs. predicted value for independent residuals, (

**c**) Residual vs. run for the absence of variation from printing location, (

**d**) Cook’s distance plot for identification of outliers and (

**e**) Box-Cox plot to identify any need of a transformation of the response.

#### Appendix A.3. ANOVA Analysis of the Density

^{2}equal to 0.7200 and the Adjusted R

^{2}equal to 0.8188, so, being the difference less than 0.2, there is no significant effect from grouping the results. The density model had an R

^{2}equal to 0.8815, which is relatively high, and the Adeq Precision equal to 12.916.

(a) ANOVA for Reduced Linear model Response 1: Density. | ||||||

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Comment |

Model | 0.1642 | 9 | 0.0182 | 14.06 | 3.12 × 10^{−6} | Significant |

A-v | 0.0008 | 1 | 0.0008 | 0.593 | 0.4518 | Hierarchy |

B-h | 3.74 × 10^{−8} | 1 | 3.74 × 10^{−8} | 0 | 0.9958 | Hierarchy |

C-rot. | 0.0003 | 1 | 0.0003 | 0.2337 | 0.635 | Hierarchy |

D-Scan pattern | 0.1074 | 2 | 0.0537 | 41.35 | 2.95 × 10^{−7} | Significant |

BD | 0.0086 | 2 | 0.0043 | 3.3 | 0.0614 | Not insignificant |

CD | 0.0108 | 2 | 0.0054 | 4.16 | 0.0339 | Significant |

Residual | 0.0221 | 17 | 0.0013 | - | - | - |

Cor Total | 0.1863 | 26 | - | - | - | - |

(b) ANOVA Quality measures for Reduced Linear model Response 1: Density. | ||||||

Entity | Value | Entity | Value | |||

Std. Dev. | 0.036 | R^{2} | 0.8815 | |||

Mean | 7.94 | Adjusted R^{2} | 0.8188 | |||

C.V.% | 0.4535 | Predicted R^{2} | 0.72 | |||

- | - | Adeq Precision | 12.9156 |

^{3}) was:

- -
- SP is 1 for the stripes pattern, otherwise it is equal to 0.
- -
- CP is 1 for the chessboard pattern, otherwise it is equal to 0.
- -
- HP is 1 for the hexagonal scanning strategy, otherwise it is 0.

**Figure A3.**Statistical quality assertion: (

**a**) Half-Normal plot vs. Externally studentized residuals for random error check, (

**b**) Residuals vs. predicted value for independent residuals, (

**c**) Residual vs. run for the absence of variation from printing location, (

**d**) Cook’s distance plot for identification of outliers and (

**e**) Box-Cox plot to identify any need of a transformation of the response.

#### Appendix A.4. ANOVA Analysis of the Nano-Hardness

^{2}equal to 0.0670 and the Adjusted R

^{2}equal to 0.3878. The difference is more than 0.2, highlighting a large block effect. Adeq Precision measures the signal to noise ratio and a ratio greater than 4 is desirable. The ratio of 6.333 indicates an adequate signal, so the model can be used to navigate the design space.

(a) ANOVA for Reduced Linear model Response 1: Nano-hardness. | ||||||

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Comment |

Model | 3.23 | 6 | 0.5391 | 3.75 | 0.0116 | Significant |

A-v | 0.0008 | 1 | 0.0008 | 0.0055 | 0.9414 | Hierarchy |

C-rot. | 0.048 | 1 | 0.048 | 0.3332 | 0.5702 | Hierarchy |

D-Scan pattern | 0.8881 | 2 | 0.4441 | 3.09 | 0.068 | Not insignificant |

AC | 1.7 | 1 | 1.7 | 11.78 | 0.0026 | significant |

C^{2} | 0.6021 | 1 | 0.6021 | 4.18 | 0.0542 | Not insignificant |

Residual | 2.88 | 20 | 0.1439 | - | - | - |

Cor Total | 6.11 | 26 | - | - | - | - |

(b) ANOVA Quality measures for Reduced Linear model Response 1: Nano-hardness. | ||||||

Entity | Value | Entity. | Value | |||

Std. Dev. | 0.3794 | R^{2} | 0.5291 | |||

Mean | 4.41 | Adjusted R^{2} | 0.3878 | |||

C.V.% | 8.6 | Predicted R^{2} | 0.067 | |||

- | - | Adeq Precision | 6.3327 |

- -
- SP is 1 for the stripes pattern, otherwise it is equal to 0.
- -
- CP is 1 for the chessboard pattern, otherwise it is equal to 0.
- -
- HP is 1 for the hexagonal scanning strategy, otherwise it is 0.

**Figure A4.**Statistical quality assertion: (

**a**) Half-Normal plot vs. Externally studentized residuals for random error check, (

**b**) Residuals vs. predicted value for independent residuals, (

**c**) Residual vs. run for the absence of variation from printing location, (

**d**) Cook’s distance plot for identification of outliers and (

**e**) Box-Cox plot to identify any need of a transformation of the response.

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**Figure 2.**Graphical representation of the studied scanning strategies: (

**a**) parallel stripes, (

**b**) chessboard and (

**c**) hexagonal.

**Figure 3.**(

**a**) Shape and dimensions (mm) of L-PBF specimens of prints 1, 2 and 3; (

**b**) Graphical representation of the support structure.

**Figure 4.**External diameter (average values and standard deviation) of the as-built specimens belonging to different sets of prints 1, 2 and 3.

**Figure 5.**The average surface roughness Ra (average values and standard deviation) of the as-built specimens belonging to different sets of prints 1, 2 and 3.

**Figure 6.**Density (average results and standard deviation) of the as-built specimens belonging to different sets of prints 1, 2 and 3.

**Figure 7.**Mounted samples showing different porosity content of specimens belonging to prints 1, 2 and 3, produced with (

**a**) hexagonal, (

**b**) chessboard and (

**c**) parallel stripes strategies.

**Figure 8.**Optical micrographs of unetched L-PBF 18Ni300 as-built samples printed with (

**a**) hexagonal, (

**b**) parallel stripes and (

**c**) chessboard strategies.

**Figure 9.**Nano-hardness (average values and standard deviation) of the as-built specimens belonging to different sets.

**Figure 11.**Influence of the scanning strategy on the average surface roughness Ra (µm) of the specimens.

**Figure 12.**Influence of the scanning strategy on the density (g/cm

^{3}) considering: (

**a**) the scan pattern, (

**b**) the process parameters and the stripes patten, (

**c**) the process parameters and the chessboard pattern, (

**d**) the process parameters and the hexagonal pattern.

**Figure 13.**(

**a**) Average nano-hardness (GPa) depending on the scanning strategy; (

**b**) Influence of the interaction between the scanning speed and the interlayer rotation on the nano-hardness (GPa).

**Table 1.**Nominal and certified composition (wt.%) of the 18Ni300 maraging steel powders produced by Höganäs (Amperprint

^{®}1556.074).

Ni. | Co | Mo | Ti | Al | C | Mn | N | O | P | S | Si |
---|---|---|---|---|---|---|---|---|---|---|---|

17.0–19.0 | 8.5–10.0 | 4.50–5.20 | 0.50–1.00 | 0.05–0.15 | <0.03 | <0.15 | <0.02 | <0.035 | <0.010 | <0.010 | <0.10 |

18.5 | 9 | 4.84 | 0.64 | 0.07 | <0.01 | 0.03 | 0 | 0.034 | 0.005 | 0.002 | <0.01 |

Entity, (Unit) | Value |
---|---|

Energy density, E (J/mm^{3}) | 89 |

Laser power, P (W) | 160 |

Layer thickness, t (mm) | 0.04 |

Scan speed, v (mm/s) | variable |

Hatch spacing, h (mm) | variable |

Inter-layer rotation, angle (°) | variable |

Stripes | Chessboard | Hexagonal | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|

set | v (mm/s) | h (mm) | Angle (°) | set | v (mm/s) | h (mm) | Angle (°) | set | v (mm/s) | h (mm) | Angle (°) |

Strip1 | 995 | 0.045 | 45 | Chess1 | 995 | 0.045 | 45 | Hex1 | 995 | 0.045 | 45 |

Strip2 | 746 | 0.060 | 45 | Chess2 | 746 | 0.060 | 45 | Hex2 | 746 | 0.060 | 45 |

Strip3 | 597 | 0.075 | 45 | Chess3 | 597 | 0.075 | 45 | Hex3 | 597 | 0.075 | 45 |

Strip4 | 995 | 0.045 | 67 | Chess4 | 995 | 0.045 | 67 | Hex4 | 995 | 0.045 | 67 |

Strip5 | 746 | 0.060 | 67 | Chess5 | 746 | 0.060 | 67 | Hex5 | 746 | 0.060 | 67 |

Strip6 | 597 | 0.075 | 67 | Chess6 | 597 | 0.075 | 67 | Hex6 | 597 | 0.075 | 67 |

Strip7 | 995 | 0.045 | 90 | Chess7 | 995 | 0.045 | 90 | Hex7 | 995 | 0.045 | 90 |

Strip8 | 746 | 0.060 | 90 | Chess8 | 746 | 0.060 | 90 | Hex8 | 746 | 0.060 | 90 |

Strip9 | 597 | 0.075 | 90 | Chess9 | 597 | 0.075 | 90 | Hex9 | 597 | 0.075 | 90 |

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## Share and Cite

**MDPI and ACS Style**

Rivalta, F.; Ceschini, L.; Jarfors, A.E.W.; Stolt, R.
Effect of Scanning Strategy in the L-PBF Process of 18Ni300 Maraging Steel. *Metals* **2021**, *11*, 826.
https://doi.org/10.3390/met11050826

**AMA Style**

Rivalta F, Ceschini L, Jarfors AEW, Stolt R.
Effect of Scanning Strategy in the L-PBF Process of 18Ni300 Maraging Steel. *Metals*. 2021; 11(5):826.
https://doi.org/10.3390/met11050826

**Chicago/Turabian Style**

Rivalta, Francesco, Lorella Ceschini, Anders E. W. Jarfors, and Roland Stolt.
2021. "Effect of Scanning Strategy in the L-PBF Process of 18Ni300 Maraging Steel" *Metals* 11, no. 5: 826.
https://doi.org/10.3390/met11050826