Transferability of the working envelope approach for parameter selection and optimization in thin wall WAAM

Although there is a direct relationship between wire feed speed (WFS) and mean current (I_m) in GMA, the CMT welding equipment does not follow the same relation throughout the whole operational range. Thus, the working envelope inside the operational map was built as a function of WFS instead of I_m (more commonly used). Moreover, since set directly in the power source interface, WFS is a more accessible parameter for the operator when compared to I_m, which is a consequence of the WFS together with other variables. A theory described by Yehorov et al. [17] was considered to determine the operating ranges of WFS. The authors claim that high arc pressure should be avoided to prevent the molten pool from running down during thin wall deposition. Thus, lower current levels, still capable of guaranteeing the coalescence between layers, should be privileged in parameterizations. Therefore, preliminary tests were carried out to set WFS so that the I_m values do not surpass 170 A. The three levels of target WFS (WFS_target) were 3, 4 and 5 m/min, which resulted in I_m values of around 120, 145 and 170 A, respectively.

To determine the travel speed (TS) range for each WFS_target, two acceptance criteria were used. The criteria were based on the surface aspects of the walls deposited in preliminary tests: top surface humps and lateral sagging. Periodic humps throughout the longitudinal direction of the beads usually occur when exceeding TS value is reached (upper range limit). The lower limit of TS was defined based on the slowest possible speed that could be used without lateral sagging. To minimize irregularities and establish more conservative limits, the found lower and upper limits of TS were incremented and decremented in 5.0 cm/min, respectively. The higher the WFS level, the higher the current (arc pressure) and the deposition rate (molten pool volume). Therefore, the lower limits of TS were not the same at each WFS set, increasing according to each level to avoid lateral sagging. The upper limits of TS, in turn, which prevents humping formation, also increased. Yuan et al. [18] claimed that the humping formation is correlated to a strong molten metal flow with high momentum, mainly affected by arc pressure, electromagnetic force and Marangoni force. As discussed by the authors, the increase in current (due to WFS) leads to a higher arc pressure and, consequently, to a greater impulse on the metal flow, facilitating the humping formation. However, a deeper melt pool is also obtained, which may dissipate the metal flow and, hence, the humps. This statement was based on their results, which showed that a short and deep molten pool is less prone to this defect than a long and shallow pool. Thus, since the TS upper limits were increased with the WFS level, it was assumed in this current work that the metal flow dissipation effect due to a deeper pool was predominant. The experimental planning matrix to build the reference working envelope for the AWS ER70S-6 wire, taken from the above considerations, is presented in Table 2. To ensure uniform distribution within each of the WFS operating ranges, the four selected levels of TS were equally divided.

The experimental design for the combinations of WFS and TS will lead naturally to different wall thicknesses. To satisfy the methodological proposal, substrates with the same width as the wall to be built were used and positioned with the narrower side facing up (as afore seen in Fig. 3). However, commercial bars covering all wall widths are not available. Trying to maintain the heat flow the more uniform as possible throughout the deposited layers, the difference in width between the substrate and the wall must be the lowest possible. One solution would be to machine down each bar to the desired thickness. However, alternatively, few layers with intermediate widths were deposited over the substrates face before the actual walls, following the same strategy adopted by Dahat et al. [14], including a theoretical approximation proposed to predict the wall widths as a function of the deposition parameters. Therefore, only two different widths of cold-rolled steel bars, 150 x 50 x 7.9 mm and 150 x 50 x 6.3 mm, were employed as substrates. The commercial bar widths were selected to minimize the number of intermediate layers required, aiming at the smallest possible difference between substrate and wall widths. The following criteria were considered to deposit intermediate layers:

All the deposited walls were digitalized through a metrology-grade 3D scanner (HandySCAN 3D^TM). The three geometrical features were measured based on the digital mesh of each wall, via dedicated software (VXElements). They are the external wall width (WW_ext), which corresponds to the broadest distance found between the wall sides, the effective wall width (WW_eff), which is the smallest distance between the wall sides, and the surface waviness (SW) calculated as the difference between WW_ext and WW_eff divided by two. For better sampling, the wall sides were split into two meshes and point-by-point measurements of distance between the two surfaces were taken. Figure 4 illustrates a schematic of the procedure used to quantify the geometrical features. The wall ends (arc start and arc ending regions) were discarded (Fig. 4a), since they tend to be unstable regions. Thus, only a central part of the walls, however long enough (28 x 90 mm), was considered for measurement. Based on the analysis of the WFS signals, a few regions with significantly deviated values was observed, probably due to the control made by CMT to compensate for variations in arc length caused by irregularities throughout the deposition of a layer. To avoid the influence of such non-common regions in the geometry assessment, the aforementioned central regions of the walls were divided into three equally spaced slices (28 x 30 mm each) along the wall length (Fig. 4b) and some outliers resultant from these WFS variations were neglected. In Fig. 4c, for instance, the external width value of 9.5 mm was not considered, since it corresponds to an outlier. In this way, for the given example, the largest width registered was 8.6 mm. Based on this methodology for each slice, a single value of WW_ext, WW_eff and SW was taken, representing the corresponding average value of each measurement. The layer heights (LH) were quantified by measuring the total wall heights with a Vernier calliper, at five different positions, and then dividing by the number of deposited layers.

One cross-section was taken from each wall from the validation (AWS ER70S-6) and the transferability (AWS ER90S-B3) trials. The cross-sections were ground, polished and etched with Nital 5% during 20 s. Micrographs and microhardness measurements were taken over three distinct regions of the wall: top, middle and bottom. A vertical line of equally spaced indentations (0.25 mm) was made with 0.1 kg load (HV_0.1) and 15 s of holding time in each region. Additionally, chemical composition analysis was carried out on different samples with a fluorescence x-ray spectrometer (XRF—Olympus Vanta C series).

Figure 5 presents the surface aspect obtained for each of the twelve walls deposited to build the reference working envelope, using the experimental design shown in Table 2. For a same target wire feed speed (WFS_target) level, the conditions with slower actual travel speeds (TS_actual) presented poorer surface aspects (more irregularities). In this case, lower TS entails larger molten pool volumes for a same arc pressure (same current and arc length), making the weld pool more prone to lateral sagging and resulting in irregularities, corroborating the hypothesis proposed by Yehorov et al. [17]. Although lower levels of WFS (lower currents) prevent excessive arc pressure, higher levels can be used when combined with faster TS levels. Dirisu et al. [19], for example, managed to build walls with a WFS of 6.5 m/min and a TS of 40.0 cm/min, also using the CMT process and the AWS ER70S-6 wire. However, it must be taken into account that this choice could result in a narrower TS working range since the arc pressure would be higher.

Table 3 presents the acquisition data from each wall deposited to build the reference working envelope. It is possible to notice that the average values of mean WFS (WFS_m) were similar for each target level, except when slower TS values were used (mainly with WFS of 5 m/min). Since walls with slower TS presented more irregular geometries, more significant variations in WFS were probably imposed by the CMT equipment to maintain constant arc length, resulting in the observed deviations. Mean current (I_m) and RMS current (I_rms) values were similar to those observed for WFS since both have a direct correlation. Moreover, mean and RMS voltage values (U_m and U_rms, respectively) remained at the same level for a given WFS_target, independently of the TS, showing the good performance of the synergy line in keeping arc length constant. The average values of mean arc energy per unit of length (E_m), in turn, varied mainly due to the wide variations adopted for TS, and on a minor scale due to the variations in average power for a given WFS.

Table 4, in turn, presents the resultant geometrical features of the walls, namely, external wall width (WW_ext), effective wall width (WW_eff), layer height (LH) and surface waviness (SW). As seen, the standard deviations did not exceed 0.2 mm, indicating good reliability regardless of the geometric characteristic evaluated. Finally, Fig. 6a shows the working envelopes for WW_ext and WW_eff, whilst Fig. 6b presents the working envelope for LH, both with their respective mean values and iso-WFS_target curves. Analyzing Fig. 6a for a given WFS and TS, the effective wall widths are always less than the external wall widths. As the effective width is taken in the valleys established between two layers, a deviation between WW_ext and WW_eff was already expected. The size of these valleys depends on the dilution, which in welding is defined as the percentage of base metal that blends with the added material (wire) composition. In this condition, the effective width values would only approximate the external width value when the dilution between the layers is such as to significantly reduce the formation of valleys in the side surface of the walls. Thus, in cases where dilution is low, more profound valleys tend to form, always leading to less effective widths than the external ones. As expected, Fig. 6b shows that the layer height decreases as TS is increased for the same WFS, since this variation reduces the amount of material deposited per unit of length. Nevertheless, when WFS is increased for a same TS, the opposite behaviour happens, leading to higher layer heights.

Surface waviness (SW) is another geometrical feature that can be adopted as a function of WFS and TS in a working envelope approach. Figure 7a presents the average values for SW and its fitting curves, whereas Fig. 7b shows a representation of the same data in the form of a 2D response surface made via a commercially available statistical analysis software package. A prediction equation (Eq. 1) was determined by the software to visually express the SW data as a contour plot. It is worth mentioning that the SW assessed in this work does not include the formation of humps and considers only the surface finish in the side of the walls. One must remember that an operating range of travel speed was established to avoid such irregularities. By analyzing Fig. 7a, one can see that when the same level of WFS is considered, surface waviness tends to reduce with increasing TS. On the other hand, this behaviour is not straightforward for faster WFS, like 5 m/min. Since the differences obtained between a given test and its adjacent ones are minimal (only about 0.1 mm), the trends carry some degree of uncertainty, justifying the difference in waviness trends at the three WFS levels. However, in general, as it can be seen through the contour lines in Fig. 7b, greater waviness occurs for lower TS and higher WFS (larger molten pool volume and higher arc pressure), and a smoother surface for the other way around (smaller molten pool volume and low arc pressure), respecting the limits of TS for high and low WFS.

Three walls were deposited with different combinations of WFS_target and TS aiming at a target effective width of 4.5 mm (arbitrarily chosen) to validate the reference working envelope. The values of WFS and TS (in the second and third columns in Table 5) were defined by interpolation within the reference working envelope (Fig. 6a) from the target effective wall width. As evidenced, none of the combinations coincided with those used to build the working envelope (Table 2), a principle of validation approaches. All other parameters were kept the same as in the construction of the reference working envelope. The remaining columns of Table 5 show the predicted and measured external wall width (WW_ext), effective wall width (WW_eff), layer height (LH) and surface waviness (SW). The predicted WW_ext and LH were also reached by interpolation in the envelopes of Fig. 6a, b, respectively. The predicted SW was obtained by using Eq. (1). Table 6, in turn, contains the deviations between predicted and measured values. Within the geometric features assessed, WW_ext had the highest deviations between the measured and predicted values, varying at around ± 0.3 mm. All the other features presented deviations between ± 0.1 mm. These low deviations indicate the robustness of the working envelope approach (the fact that the deviations present no tendencies concerning being greater or less than the predicted values also suggests statistical reliability).

As shown in Fig. 8, the arc energies per unit of length calculated for Table 5 trials (in which different WFS and TS combinations reaching the same target effective width) were very similar (considering the standard deviations amongst layers). The wall geometries were practically the same (suggesting that the heat flow through the wall was similar). This behaviour was expected, since heat flux is the most important governing parameter to define the geometrical wall features. Accordingly, the thermal cycles experienced by the layers probably followed the same tendency (all facts indicating a strong correlation between arc energy and heat input). Consequently, no significant differences in microstructures were observed in the samples built in the validation trials, as shown in Fig. 9. However, it is well known that microstructure is governed by arc energy and thermal cycle and by chemical composition. In this sense, chemical composition analysis was carried out with a fluorescence x-ray spectrometer (XRF) to assess the possible influence of the deposition parameters over the burning losses of elements. In phase with the previous results, Table 7 suggests no significant variations (or trends) when chemical compositions were quantified over the extreme WFS and TS conditions. One can also assume that no chemical variation occurred between the walls from the validation trials.

Naturally, microstructure changes were observed between the top layer and the remaining layers that underwent thermal retreatment from multiple thermal cycles. This behaviour was also observed by Aldalur et al. [20] and Kozamernik et al. [21] when using WAAM with the same ER70S-6 wire. To illustrate this behaviour, Fig. 10 presents macro and micrographs for the intermediate condition within the validation trials. As seen, no imperfections are observed. It can be noticed that the last deposited layer, which corresponds to a region not subject to reheat from the following layers (region 1), presents large columnar grains composed majorly by grain boundary ferrite (PF(G)) and acicular ferrite (AF). Region 2 illustrates that the fusion line is not easily perceived by optical microscope. Typical microconstituents of primary solidification zones are presented, such as grain boundary ferrite (PF(G)), acicular (AF), side plate ferrite (FS(A)) and some veins of polygonal ferrite (PF). Both the middle (region 3) and bottom regions of the wall (region 4) do not present major differences in microstructure between themselves and contain mainly polygonal ferrite. It can be said that these regions experience a similar thermal history based on the microstructure. However, it is worth noting that the microstructures of regions 1 and 2 occur only at the top surface of a thin wall and can be easily machined out if it is the case. The principal volume of a wall will be composed of microstructures illustrated in regions 3 and 4, as long as the thermal management during the building keeps the same interlayer temperature. Notwithstanding, regions 1 and 2 turn to be relevant in short walls concerning mechanical functionality. This is the reason to present this microstructural feature in the current study.

Figure 11 presents the microhardness profiles from the validation trials. There is no significant variation of the mean hardness when the three parametric conditions are compared (coherent with the microstructural features), as presented in Fig. 12. The average microhardness at the multi heat-treated regions is around 185 HV, within a narrow range of between 170 and 200 HV. The top region, in turn, shows a broader variation (of between 170 and 245 HV) as a consequence of the different ferrite morphologies typical of primary solidification. As evidenced in Fig. 13, the higher microhardness values in the top region are associated with regions rich in acicular ferrite.

Three walls were deposited to assess the transferability of parameters from an existing working envelope when changing the feedstock, now using a high strength low alloy steel wire (AWS ER90S-B3). The same parameter combinations (columns 2 and 3 of Table 5) used for the reference envelope validation were replicated. Consequently, a similar estimated wall width as the walls for the reference envelope validation is expected at the outset. Thus, the following discussions are based on the comparison between the walls built for both transferability and validation of the reference envelope. In this context, Fig. 14 presents the appearance of the walls, in which no significant changes in the surface aspect are noticed when contrasting walls made with the same wire. However, more regular surfaces were achieved with the AWS ER90S-B3 wire when compared to AWS ER70S-3. It is also noticeable in this figure that WFS matches the target values for both wires, indicating that the walls were deposited with the same set of parameters.

Table 8 presents the predicted and measured geometric features, namely, external wall width (WW_ext), effective wall width (WW_eff), layer height (LH) and surface waviness (SW). Table 9 presents the deviations (measured values minus the predicted ones). It can be verified that the external wall widths were always narrower and heights taller than expected, a difference not so significant when effective width is taken into account. Surface waviness was always less than predicted, reaching deviations of up to -0.3 mm, quantifying the best surface finish observed for the builds with the AWS ER90S-B3 wire, shown in Fig. 14. Since there is a difference in chemical composition between both materials, divergences could be expected.

To better understand how the physical properties of the molten pool could have changed between the wires, Table 10 presents the chemical compositions for both materials. These correspond to the mean values shown in Table 7 for the AWS ER70S-6 wire and the mean values obtained for the walls deposited with the AWS ER90S-B3 wire, which will be presented later (Table 11). Deng et al. [22] proposed Eq. (2) to estimate the dynamic viscosity (η) of liquid steels as a function of the chemical elements, where T corresponds to the temperature within an optimum range between 1463 and 1723 K. The authors verified that the dynamic viscosity increases as the Si and Ti contents are increased, whilst an inverse effect is caused by increasing contents of Mn, P and S. Thus, although AWS ER90S-B3 has a lower Si content compared to AWS ER70S-6 (0.40 wt% on average), which would lead to a decrease in viscosity, the lower Mn content (0.72 wt%) would overcome this effect and cause the AWS ER90S-B3 molten pool to have a higher viscosity, resulting in higher resistance to movement induced by arc pressure and, as a consequence, the resultant bead would be narrower (wall width) and taller (layer height). It is worth mentioning that, as shown in the referred equation, Mn content has a higher coefficient when compared to Si content, indicating that Mn has a stronger effect over molten metal viscosity. Besides that, the existence of some surface-active agent (S, O, Se and Te), even in small amounts, could change wettability and lead to changes in molten pool geometry. For instance, Keene et al. [23] observed large variations in surface tension between 316 stainless steel grades with a difference of 139 ppm (0.0139%) of S. Finally, both viscosity and surface tension are highly dependent on temperature, so possible changes in thermal diffusivity between the materials may also affect the wall geometry.

To discuss the effect of the feedstock on arc physic aspects, Fig. 15 presents the average values from the main process parameters monitoring (mean and RMS current, mean and RMS voltage). Slightly higher mean and RMS current can be seen in the walls built with AWS ER90S-B3 (Fig. 15a, b), although the same WFS and TS had been set. This means that a higher current is needed to melt the AWS ER90S-B3 wire at the same melting rate. To investigate this behaviour, mean values of arcing time (t_arc) and short-circuiting time (t_sc) were calculated through the electric signal data from five layers, using a home-developed software (CURTOWELD), registered by Vilarinho and Araújo [24]. The synergy line of CMT imposed on these materials 50% of arcing and short-circuiting times, but with different durations. For the AWS ER70S-6 wire, t_arc and t_sc presented the same value equal to 6.3 ms, while with AWS ER90S-B3, they were equal to 6.0 ms. As a result, the short-circuiting frequency with ER90S-B3 (82.9 Hz) was slightly higher than with ER70S-6 (79.8 Hz). A slight increasing shifting between current and voltage waveforms from both wires can be seen in Fig. 16, due to the difference in short-circuiting frequency. As noticed in Fig. 16, the currents at arcing and short-circuiting times are similar to the two wires.

Short-circuit frequency by itself does not justify the higher current levels for AWS ER90S-B3 to maintain the same melting rate (same WFS). For this to happen, it would be necessary that the t_arc/t_sc ratio be greater for the low alloy steel wire, which does not occur. However, this current related behaviour can be discussed with the aid of the equation for melting rate in short-circuiting metal transfer (Eq. 3), detailed in Jorge et al. [25]. In this equation, MR is the melting rate, α and β are constants that depend on electrode polarity, shielding gas composition, wire material, ρ is the electric resistivity of the wire, L is the electrified wire free extension, S is the cross-section area of the wire, I_m is the mean current, I_rms the root mean square of current, t_arc is the arcing time and t_sc is the short-circuiting time.

Knowing that the same melting rate was achieved for a given combination of WFS and TS (Fig. 14b) and considering that the arc length was the same for both wires (intrinsic due to the use of the same synergic line), the higher current with AWS ER90S-B3 can be justified by the following hypothesis: a) cross-section area (S) wire is larger; b) a lower electrical resistivity (ρ); c) α and β values become lower. The first hypothesis was confirmed by measuring the wire diameters with a micrometer (seven measurements in each wire) and the results showed that the diameters were 1.17 ± 0.01 mm and 1.15 ± 0.0 mm, respectively, for AWS ER90S-B3 and AWS ER70S-6 (leading to areas of 4.30 e 4.15 mm²). One evidence that could lead to the conclusion that the low alloy steel wire attains lower electrical resistivity (ρ) would come from the marginally lower mean and RMS voltages (Fig. 15c, d) when this wire was used. The third hypothesis, related to the constant α e β, was not possible to be assessed in this work. Whatever the reason or combination, it is demonstrated that the two wires had different arc physics properties, not only different chemical compositions. Hence, their use to demonstrate the potential of parameter transferability of the approach working envelope is assured.

Closing the analysis of the electrical signals, Fig. 17 demonstrates that, similar to the validation trials (Fig. 8), no significant difference amongst the arc energies per unit of length is observed amongst the 3 walls employed to achieve the same effective wall width (4.5 mm) with AWS ER90S-B3 as feedstock (considering the standard deviations). However, other combinations of WFS and TS might deliver different results. Therefore, it was not surprising that the wall geometries were practically the same, as seen in Tables 8 and 9. Furthermore, according to Table 11, no variation in the deposited chemical composition was observed either. As a consequence of the similarity between the results of arc energy, geometry and chemical composition, no significant differences in microstructures were observed amongst the samples built in the transferability trials, as shown in Fig. 18.

The same analysis applied to the reference working envelope towards the variation of microstructure and hardness along the wall building direction was replicated to the trials with the AWS ER90S-B3 wire. The condition with WFS = 3.8 m/min and TS = 38.5 cm/min is taken as an example and macro and micrographs from this trial are shown in Fig. 19. As seen, no imperfections are observed. Contrasting with the walls made of C-Mn steel (AWS ER70S-6), no significant changes in macro and microstructure are noticed even between the top layer and the remaining layers. More significant formation of tempered martensite is possible in the transition between the last two layers deposited (region 2), the middle of the wall (region 3) and in the bottom (region 4) when compared to the top layer (region 1). This is reasonable since these regions are subject to reheating by deposition the following layers and could be tempered. However, to correctly affirm the above, a more thorough microstructure investigation should be carried out, which is out of this work context. In this case, it can be affirmed only that microstructure is composed mainly of martensite, tempered martensite and bainite, which is in accordance with the findings of Dirisu et al. [19] and Sharma and Shahi [26] for AWS ER90S-B3.

Microhardness values ranged within 270 and 420 HV for the AWS ER90S-B3 walls, as can be seen in Fig. 20. A cyclic behaviour, indicated by red arrows, was identified. Depending on the peak temperatures and cooling rates of the multiple thermal cycles experienced, each region may present a higher or lower formation of martensite/bainite and lead to the observed result. The average microhardness values were around 335 HV, as shown in Fig. 21 with the respective standard deviations. As a whole, there are differences in the metallurgical architecture between the walls for the envelope validation and the walls for evaluating the parameter transportability because the feedstocks are different. But the transportability of the parameters showed to be feasible.

To investigate the complementary objective as to the possibility of optimizing parameter selection for a same target width, Fig. 22 presents the reference working envelope for effective wall width considering arc energy per unit of length (E), surface waviness (SW) and active deposition time (t_ad) as responses. It must be highlighted that active deposition times were determined considering a wall with 140 mm in length, with a total height of 40 mm. First, the number of necessary layers was found by dividing 40 mm by the layer heights achieved for each WFS and TS combination (Table 4). Next, the number of layers for each condition was multiplied by the wall length (140 mm), considering the distances travelled. These distances were finally divided by the travel speeds, resulting in active deposition times (not considering dwell times).

Second-order models, defined in Eq. (4), were used to plot the contour lines. Aiming at improving the variability proportion that can be quantified for each model (R²), the significance level of each term of the model was evaluated through ANOVA and the less significant terms (p-values>0.05) were discarded. Equations (5), (6) and (7) present the models used to develop the surfaces in Fig. 22 and their respective R² and adjusted R². According to Montgomery [27], adjusted R² corresponds to a variation of R² that is adjusted to the model’s size, that is, the number of factors. R² higher than 0.95 means that 95% of the data variability can be explained by the models. Figure 22 also displays the respective observed-by-predicted charts on the right side of each contour plots. These charts are helpful to detect misspecifications in the structural model. Ideally, values should lie roughly along a 45-degree line. Predictions that are outside the interval are denoted as outliers. A high proportion of outliers suggests misspecifications in the model. Moreover, the distribution of the observations should be symmetrical around to the corresponding predicted values.

where f(x,y) is the predicted or expected value, i.e. the regression function of the independent variables “x” and “y” (which in this case correspond to travel speed and effective wall width); “A” corresponds to the intercept (predicted value when all of the independent variables are equal to zero); and “B”, “C”, “D”, “E” and “F” are the estimated regression coefficients.

Figure 22a suggests that variations in WFS and TS tend to slightly affect arc energy per unit of length for a given effective width, mainly when lower width values are considered. For instance, when using the prediction equation to determine the arc energy per unit of length (Eq. 5) for a WW_eff of 4.0 mm and considering TS at 40.0 and 57.0 cm/min (close to the envelope boundaries), the predicted values of E are equal to 274 and 277 J/mm, respectively, resulting in a difference (ΔE) of only 3 J/mm. On the other hand, when a wall width of 6.5 mm is admitted, and considering TS at 16.0 and 22.0 cm/min (again close to the envelope boundaries), the predicted values of E are 731 and 701 J/mm, respectively, resulting in a ΔE of 30 J/mm. As already evidenced, variations in E between 339 and 348 J/mm (ΔE = 9 J/mm) for AWS ER70S-6 (Fig. 8) and between 344 and 347 J/mm (ΔE = 3 J/mm) for AWS ER90S-B3 (Fig. 17) were not enough to significantly change microstructure or microhardness profiles for a target width of 4.5 mm. Although this difference can become larger for higher widths, it is still unlikely that they are sufficient to lead to significant changes in microstructure and mechanical properties. Hence, for the reference working envelope, or a potential working envelope (AWS ER70S-6) considering the transferability to AWS ER90S-B3, it can be stated that, for a given target width, variations in WFS and TS do not significantly affect microstructure and microhardness.

Figure 22b shows that employing lower values of WFS and TS results in smaller SW and, consequently, better surface finishing for a same effective wall width. Considering Eq. (6) and taking, for instance, 4.0 mm as WW_eff and values of TS equal to 40.0 and 57.0 cm/min (values close to the envelope boundaries), the resulting SW are 0.5 and 0.8 mm, respectively, resulting in a difference (ΔSW) of 0.3 mm. If a WW_eff of 6.5 mm is taken, with TS values of 16.0 and 22.0 cm/min (again close to the envelope boundaries) the resultant SW will be 0.9 and 1.0 mm, respectively, resulting in a ΔSW of 0.1 mm. This means that for larger widths, the surface finish deteriorates. However, it is less affected by the WFS/TS combination. It is important to draw attention to the fact that the low adjusted R² of Eq. (6) may become feasible if the correspondent contour plot represents this quantity. The observed-by-predicted chart for SW shows that the values lie reasonably along a 45-degree line and that the deviations are lower than 15%. Moreover, the distribution of the observations is symmetrical around the corresponding predicted values. All of this gives statistical confidence to the estimator, even with a relatively low adjusted correlation coefficient.

Finally, Fig. 22c indicates that by employing higher values of WFS and TS, for a given target width, active deposition time (t_ad) becomes shorter. Elapse times may be in the opposite direction at first sight. However, the reader must remember that for this material and power source, arc energy presents low changes for a given wall width (elapse time is roughly proportional to arc energy). Changes in the desired width also influence the deposition times found for different WFS and TS combinations. Based on Eq. (7), taking WW_eff as 4.0 mm and TS at 40.0 and 57.0 cm/min, the resulting t_ad are 7.4 and 4.3 minutes, respectively, resulting in a difference (Δt_ad) of 3.1 min. When the WW_eff of 6.5 mm is taken, with TS varying from 16.0 to 22.0 cm/min, the resulting t_ad are 11.5 and 8.5 min, respectively, resulting in a Δt_ad of 3.0 min. Although the t_ad does not take dwell times (necessary to reach the interlayer temperatures of 30 °C) into consideration, the deposition times can be considered proportional to the total construction time if a same target width is admitted.

In summary, the approach applied in this work to optimize parameter selection allowed not only for visualization of the effects of each parameter over operational features desired for a same effective width, but also a quantification through equations. Computational optimization routines could be used to generate the optimum combination between TS and WFS for a desired wall width using arc energy, surface waviness, active deposition time and others, as an objective function or as restrictors. For instance, one could wish to find TS and WFS to build a wall with a determined width to provide at the same time the shortest active time, with a minimum surface waviness and with arc energy higher than a given value. Nevertheless, it must be highlighted that the interactions here discussed cannot be stated straightforward for working envelopes using other processes or materials. However, they worked well between the two materials evaluated.