# Efficiency of ancient iron production: A case study from the Kaniasso district, Ivory Coast (11 th -19 th century)

Melissa Morel, Vincent Serneels, Caroline Robion-Brunner, Hélène Timpoko

Kiénon Kabore

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Melissa Morel, Vincent Serneels, Caroline Robion-Brunner, Hélène Timpoko Kiénon Kabore. Efficiency of ancient iron production: A case study from the Kaniasso district, Ivory Coast (11 th -19 th century). Journal of Archaeological Science: Reports, 2024, 10.2139/ssrn.4828551. http://hal-04810563

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# Efficiency of ancient iron production: A case study from the Kaniasso district, Ivory Coast
(11th-19th century)

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Mélissa Morel (morel.melissa@protonmail.com), Vincent Serneels, Caroline Robion-Brunner, Hélène Timpoko Kiénon Kabore

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**Abstract**: This study explores the management of mostly two smelting technical, KAN1 and KAN3, in the Kaniasso district, northwest Ivory Coast. In-depth chemical analyses, using X-ray Fluorescence, were conducted on slag and ore samples. Subsequently, mass balance calculations were carried out to estimate the metal production. This research introduces a new comparative approach, encompassing the technical, economic, and social dimensions of efficiency. By examining the KAN1 and KAN3 traditions, the study highlights their distinct metallurgical practices, emphasizing differences in furnace management and variable technical efficiency.

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**Keywords**: Iron metallurgy, Smelting, Slag, Efficiency, Ivory Coast.

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## 1. Introduction

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Colonial and post-colonial ethnographical records from Africa show a great diversity in the morphology of the furnaces and in their implementation (Cline, 1937; Celis, 1991). This diversity is not only associated to the metallurgists' choices and expertise, but also to broader cultural dimensions shared by the community. Indeed, each cultural group has its own know-how, its own rule-and-value systems and produces a certain amount of iron according to their needs. It results particular technical traditions adapted to each cultural group (Lemonnier, 2010).

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History of techniques teaches us that technical traditions may or may not change through time, showing the different mechanisms at play behind the processes of innovation (borrowing/non-borrowing) and diffusion of material culture. However, the circumstances that motivate or slow down technology changes are still poorly understood (Killick, 2015; Robion-Brunner, 2020). Until now, there
27 is indeed no satisfactory approach to classify and compare iron smelting techniques. Some authors 28 suggested initially comparing the shape of smelting furnaces (Forbes, 1950; Coghlam, 1956), while 29 others proposed adding functional details to the comparison, such as ventilation and slag type 30 (Tylecote, 1987; Cleere, 1972; Pleiner 1978). We propose here to use the concept of efficiency to 31 compare techniques and understand the reasons driving technical transitions or ruptures. 32

This study focuses on smelting within the *chaîne opératoire*, drawing on data collected between 2013 32 and 2017 as part of the research project 'Origin and Development of Iron Metallurgy in Burkina Faso 33 and Côte d'Ivoire' (Serneels et al. 2013; Serneels et al., 2015). Led by Vincent Serneels and Hélène 34 Timpoko Kiénon-Kaboré, the project examines metallurgical remains from the Kaniasso district in 35 northwest Ivory Coast, encompassing traditions referred to as KAN1, KAN2, and KAN3. This case study 36 offers an opportunity to explore efficiency in comparing these technical traditions. 37

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## 2. The Kaniasso district and the three smelting techniques 39

The Siola and Doumbala sites, situated approximately 60 km north of Odienne in the north-western 40 region of Côte d'Ivoire (Figure 1- A), were investigated in this project. These sites present three distinct 41 technical traditions—KAN1 (11th-13th centuries), KAN2 (16th-17th centuries), and KAN3 (17th-19th 42 centuries)—spanning approximately a millennium. Excavations in 2012 and 2014 (Serneels et al., 2013; 43 Serneels et al., 2015) allowed for quantification and dating, with reliable furnace morphology 44 reconstruction (Figure 1—B). 45

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A

<figure><img src="image_1.png" /></figure>

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<figure><img src="image_2.png" /><figcaption>Figure 1: A. Map showing the location of the Kaniasso district in Côte d'Ivoire. B. Pictures and schemes of the excavated furnaces from the three identified techniques from Kaniasso (from Serneels et al., 2013).</figcaption></figure>

KAN1, active between the 11th and 13th centuries, features small elliptical slag heaps associated with large, repeatedly operated furnaces. Pillars that create multiple openings for tuyeres placement, outline an elliptical depression. Tuyeres form a significant portion of the furnace building materials.

KAN2 technical tradition (16th-17th centuries) consist of irregular spreads of internal slag blocks, forming small uneven mounds. The furnaces are subcircular constructions placed on large. The furnaces have several openings as well as a west-facing door. The pillars supporting these openings are reinforced with segments of used tuyères.

KAN3, operational from the 17th to 19th centuries, is identified by large annular heaps of internal slag blocks. The furnaces, situated on circular pits, feature pillars and large used tuyères providing external

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support. Although the upper part is not well-preserved, fragments suggest a relatively narrow chimney diameter of only 30 cm. The estimated total height of the construction ranges from 2 to 2.5 meters.

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## 3. Materials and Methods

This study relies on data gathered between 2013 and 2017 by Madalina Bonta, who conducted the majority of the laboratory work. Initially, she conducted a comprehensive study of slag morphology for each technical tradition. Subsequently, she selected a set of samples for global bulk analysis.

We use the X-ray Fluorescence (XRF) data obtained from 109 slag samples and 28 potential ore samples (Table 1). The slag samples were carefully selected to analyze, for each slag heap, representative pieces of the assemblage as well as a few unusual pieces. The analyses were conducted using a PW2400 X-ray Fluorescence Spectrometer. The program was calibrated using 40 international reference materials (Pfeifer et al., 1992). Both major components (Si, Ti, Al, Fe, Mg, Ca, Na, K and P) and 41 trace elements were measured on pressed powder pellets. The analytical error is below 10% relative. Measurements below 2 ppm are not considered.

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<table><caption>Table 1: Summary table of slag and ore samples analysed by XRF. Unprocessed raw data are available on request from the authors.</caption><thead><tr><th>Site</th><th>Technique</th><th>Slag samples</th><th>Ore samples</th></tr></thead><tbody><tr><td rowspan="3">Siola</td><td>KAN1</td><td>19</td><td rowspan="3"></td></tr><tr><td>KAN2</td><td>6</td></tr><tr><td>KAN3</td><td>14</td></tr><tr><td rowspan="3">Doumbala</td><td>KAN1</td><td>53</td><td>12</td></tr><tr><td>KAN2</td><td>6</td><td></td></tr><tr><td>KAN3</td><td>11</td><td>2</td></tr><tr><td></td><td>Geological</td><td></td><td>14</td></tr><tr><td></td><td></td><td><strong>109</strong></td><td><strong>28</strong></td></tr></tbody></table>

## 4. Results

### 4.1. Relationship between ore and slag

One of the first step to study a metallurgical production is to identify which ore was used. It is difficult to establish that an iron-rich rock was used as an ore. First, archaeological evidence of ore extraction

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is often challenging to find, mainly because later activities may have erased ancient traces, or because small-scale extraction leaves only few evidence. Too few prospecting efforts invest energy in identifying ores. Moreover, iron-rich rocks found on production sites are not necessarily ores; on the contrary, they may be rocks rejected by the metallurgists because of their poor quality. It is thus necessary to compare the slag and the ore chemical composition. Relationships between the bulk chemical composition of slag and ore samples can be established by comparing ratios between different chemical elements (Coustures et al., 2003; Desaulty et al., 2008).

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### 4.1.1. Smelting technique KAN1

The KAN1 technical tradition has various slag morphologies: external tapped slags (TS - n = 50), sandy-clay slags (SCS - n = 9), internal furnace bottom slags (BFS - n = 4), and a few slags with a mixed morphology (n = 5). Samples from eight different slag heaps were analyzed (Doumbala - F206, F301, F401, F409; Siola - F1302, 2000F1, 2000F3, 2000F4).

The compositions of KAN1 slags vary, but the internal variability within a heap is less pronounced than the overall variability across all KAN1 slags. Two distinct groups of chemical compositions emerge, with heaps F206 and F1302 on the one hand, and all the other heaps on the other hand. Heap F1302 is the oldest dated of the KAN1 technique (990-1040 cal AD). Unfortunately, heap F206 is not dated, but it is located away from the other KAN1 heaps in Doumbala. There are no marked compositional differences between Siola and Doumbala (Figure 2-A). KAN1 slags are characterized by remarkably high contents of manganese oxide (MnO) and barium (Ba), regardless of slag morphology (Table 2). It is likely that these high manganese oxides contents come from external additions to the ore, but more analyses are needed.

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<table><caption>Table 2: Bulk chemical compositions of the smelting slags and archaeological ores from F301 (KAN1). The results of the mass balance calculations are added at the end of the table.</caption><thead><tr><th>Sample</th><th>DMB251</th><th>DMB252</th><th>DMB253</th><th>DMB254</th><th>DMB255</th><th>DMB256</th><th>DMB257</th><th>DMB258</th><th>DMB353</th></tr><tr><th></th><th>TS</th><th>TS</th><th>TS</th><th>TS</th><th>TS</th><th>TS</th><th>TS</th><th>TS</th><th>Ore</th></tr></thead><tbody><tr><td>SiO<sub>2</sub> (wt.%)</td><td>23.82</td><td>22.35</td><td>24.26</td><td>22.52</td><td>24.24</td><td>24.42</td><td>21.92</td><td>26.87</td><td>9.37</td></tr><tr><td>TiO<sub>2</sub> (wt.%)</td><td>0.24</td><td>0.22</td><td>0.23</td><td>0.26</td><td>0.24</td><td>0.25</td><td>0.24</td><td>0.15</td><td>0.13</td></tr><tr><td>Al<sub>2</sub>O<sub>3</sub> (wt.%)</td><td>8.36</td><td>6.92</td><td>7.46</td><td>7.64</td><td>8.34</td><td>8.79</td><td>7.17</td><td>6.39</td><td>17.43</td></tr><tr><td>Fe<sub>2</sub>O<sub>3</sub>tot (wt.%)</td><td>58.00</td><td>62.48</td><td>62.15</td><td>49.00</td><td>57.56</td><td>56.74</td><td>66.76</td><td>63.36</td><td>71.01</td></tr><tr><td>MgO (wt.%)</td><td>0.69</td><td>0.48</td><td>0.75</td><td>0.42</td><td>0.69</td><td>0.75</td><td>0.45</td><td>0.50</td><td>1.39</td></tr><tr><td>MnO (wt.%)</td><td>5.53</td><td>4.08</td><td>1.32</td><td>15.10</td><td>5.68</td><td>5.67</td><td>0.78</td><td>0.75</td><td>0.07</td></tr><tr><td>CaO (wt.%)</td><td>0.78</td><td>1.21</td><td>1.94</td><td>1.30</td><td>0.75</td><td>0.77</td><td>1.02</td><td>0.47</td><td>0.03</td></tr><tr><td>Na<sub>2</sub>O (wt.%)</td><td>0.03</td><td>0.03</td><td>0.01</td><td>0.06</td><td>0.04</td><td>0.03</td><td>0.02</td><td>0.01</td><td>0.00</td></tr><tr><td>K<sub>2</sub>O (wt.%)</td><td>1.00</td><td>0.81</td><td>0.91</td><td>0.92</td><td>0.96</td><td>1.01</td><td>0.74</td><td>0.65</td><td>0.06</td></tr><tr><td>P<sub>2</sub>O<sub>5</sub> (wt.%)</td><td>0.58</td><td>0.64</td><td>0.42</td><td>0.49</td><td>0.55</td><td>0.60</td><td>0.47</td><td>0.50</td><td>0.24</td></tr><tr><td>SUM</td><td>107.03</td><td>105.47</td><td>103.30</td><td>117.44</td><td>106.88</td><td>106.92</td><td>102.39</td><td>102.35</td><td>99.92</td></tr><tr><td>SiO<sub>2</sub>:Al<sub>2</sub>O<sub>3</sub></td><td>2.85</td><td>3.23</td><td>3.25</td><td>2.95</td><td>2.91</td><td>2.78</td><td>3.06</td><td>4.21</td><td>3.91</td></tr><tr><td>Ba (ppm)</td><td>5738</td><td>3943</td><td>1079</td><td>17859</td><td>5959</td><td>5826</td><td>1052</td><td>1149</td><td>240</td></tr><tr><td>Ce (ppm)</td><td>84</td><td>49</td><td>114</td><td>0</td><td>81</td><td>19</td><td>0</td><td>126</td><td>469</td></tr><tr><td>Co (ppm)</td><td>347</td><td>367</td><td>329</td><td>337</td><td>262</td><td>309</td><td>249</td><td>329</td><td>298</td></tr><tr><td>Cr (ppm)</td><td>273</td><td>270</td><td>1316</td><td>165</td><td>267</td><td>292</td><td>165</td><td>91</td><td>287</td></tr><tr><td>Rb (ppm)</td><td>59</td><td>43</td><td>53</td><td>49</td><td>69</td><td>62</td><td>38</td><td>33</td><td>13</td></tr><tr><td>S (ppm)</td><td>153</td><td>154</td><td>201</td><td>113</td><td>144</td><td>163</td><td>447</td><td>54</td><td>81</td></tr><tr><td>Sr (ppm)</td><td>73</td><td>99</td><td>94</td><td>124</td><td>76</td><td>72</td><td>58</td><td>29</td><td>0</td></tr><tr><td>Th (ppm)</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>V (ppm)</td><td>89</td><td>121</td><td>114</td><td>81</td><td>102</td><td>85</td><td>88</td><td>24</td><td>131</td></tr><tr><td>W (ppm)</td><td>267</td><td>254</td><td>78</td><td>212</td><td>182</td><td>282</td><td>78</td><td>212</td><td>77</td></tr><tr><td>Zr (ppm)</td><td>204</td><td>202</td><td>176</td><td>171</td><td>206</td><td>213</td><td>152</td><td>132</td><td>39</td></tr><tr><td colspan="10">Calculated Amount of Material for 100g of Slag</td></tr><tr><td>Ore (g)</td><td>271</td><td>224</td><td>241</td><td>251</td><td>270</td><td>285</td><td>231</td><td>206</td><td></td></tr><tr><td>Slag (g)</td><td>100</td><td>100</td><td>100</td><td>100</td><td>100</td><td>100</td><td>100</td><td>100</td><td></td></tr><tr><td>Iron (g)</td><td>128</td><td>95</td><td>106</td><td>121</td><td>128</td><td>137</td><td>97</td><td>84</td><td></td></tr><tr><td>Yield (%)</td><td>76</td><td>68</td><td>71</td><td>78</td><td>76</td><td>77</td><td>67</td><td>65</td><td></td></tr></tbody></table>

Comparing the chemical compositions of different slag morphologies reveals that SCS pieces have significantly different compositions than other morphologies (Figure 2-C). These samples show higher silica contents (over 50 wt.% SiO₂) and lower iron oxide contents (less than 50 wt.% SiO₂) than other morphologies. SCS samples are thus entirely excluded from the ore comparisons. Samples from other morphologies are less variable, except for alumina contents. As TS is the most characteristic morphology of this technique, we will use these samples to advance our considerations on ores.
116 Ore stocks were found only near three KAN1 slag heaps (F206, F301, F409). Direct comparisons were 117 initially made with slags from the corresponding heap. In the case of heaps F206 and F409, the 118 SiO₂:Al₂O₃ ratios of the analyzed samples are incompatible with any KAN1 slag (Figure 2-C). They likely 119 represent residues from visual sorting of the ore, where metallurgists rejected gangue too poor in iron 120 oxides. The same situation applies for one ore sample from heap F301. Another sample from F301 has 121 ratios compatible with slags but iron oxide contents are too low. Finally, sample DMB351 has iron oxide 122 contents high enough to be used as ore, along with ratios between major and trace elements 123 compatible with slags.

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<figure><img src="image_3.png" /></figure>

B Boxplot showing the variability of the SiO₂:Al₂O₃ ratio for KAN1 and KAN3

<figure><img src="image_4.png" /></figure>

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<figure><img src="image_5.png" /><figcaption>Slag and ore from KAN1</figcaption></figure>

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<figure><img src="image_6.png" /><figcaption>Slag and ore from KAN3</figcaption></figure>

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Figure 2: A. Bivariate diagram Al₂O₃-SiO₂ for the bulk composition of slag samples for the KAN1, KAN2 and KAN3 technical traditions. B. Boxplot illustrating the variability of the SiO₂:Al₂O₃ ratio for the KAN1 and KAN3 slags. C. Bivariate diagram Al₂O₃-SiO₂ for the bulk composition of slag and ore samples for KAN1. D. Bivariate diagram Al₂O₃-SiO₂ for the bulk composition of slag samples for KAN3.

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4.1.2. Smelting tradition KAN2

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The KAN2 tradition is the one in which the fewest samples could be analysed. The samples are all
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bottom furnace slag (BFS - n = 12) coming from 3 different slag heaps (Doumbala - F201; Siola - F1253,
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F1265). The chemical compositions of the KAN2 samples are homogeneous. Unlike the KAN1 samples,
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the manganese oxide and barium contents are very low. It is difficult to draw conclusions from so little
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data. But the variability of slag coming from the same site (DMB or SLA) is lower than the overall
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variability (Figure 2-A). Moreover, no ore fragment has been found on KAN2 smelting workshops. It is
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therefore not possible to know with any certainty the chemical composition of the ores used. The data
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on KAN2 is unfortunately insufficient to be discussed further in the article.
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4.1.3. Smelting tradition KAN3

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Slag samples from four slag heaps (Doumbala - F102, F110; Siola - F1102, F1103) were analyzed for the
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KAN3 technical tradition. The majority of KAN3 slag samples are fragments from large internal bottom
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furnace slag (BFS - n = 23). Some other samples have a different macroscopic appearance, such as a
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porous or stratified texture (Atypical - n = 3). Comparing the chemical compositions of these two slag
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categories, we cannot consider them similar, leading to the exclusion of atypical slag from the dataset.
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The analyzed KAN3 BFS samples show very similar compositions to KAN2 samples (Figure 2-A). The
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KAN3 BFS compositions are extremely variable, even within a same slag heap (Figure 2-B and D).
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Ore deposits were found only at the vicinity of F110. Two samples were analyzed, one immediately
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excluded due to low iron oxide content and excessive silica content (Table 3). Sample DMB323 has an
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SiO₂:Al₂O₃ ratio compatible with F110 slags, although this ratio varies significantly (Figure 2-D). Ratios
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of minor and trace elements are also compatible.
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The significant variability observed in the chemical composition of F110 slag cannot be only explained
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by wall contamination (Morel and Serneels, 2021). A more reasonable explanation is substantial
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variability in ore deposits. Moreover, the ores used within the same metallurgical workshop are more
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diverse for KAN3 than for KAN1 (Figure 2-B). In both cases, they use the same type of ore, likely
157 ferruginous sandstone, given the highly similar chemical compositions of major and trace elements,  
158 highlighting different ore supply management strategies.

<table><caption>Tableau 3: Bulk chemical compositions of the smelting slags and archaeological ores from F100 (KAN3). The results of the mass balance calculations are added at the end of the table.</caption><thead><tr><th>Sample</th><th>DMB122<br>Bloc</th><th>DMB123<br>Bloc</th><th>DMB124<br>Bloc</th><th>DMB125<br>Bloc</th><th>DMB121O<br>Bloc</th><th>DMB121F<br>Bloc</th><th>DMB321<br>Ore</th><th>DMB323<br>Ore</th></tr></thead><tbody><tr><td>SiO<sub>2</sub> (wt.%)</td><td>29.74</td><td>32.58</td><td>37.69</td><td>44.29</td><td>34.16</td><td>29.32</td><td>44.22</td><td>21.70</td></tr><tr><td>TiO<sub>2</sub> (wt.%)</td><td>0.11</td><td>0.09</td><td>0.05</td><td>0.11</td><td>0.08</td><td>0.07</td><td>0.02</td><td>0.04</td></tr><tr><td>Al<sub>2</sub>O<sub>3</sub> (wt.%)</td><td>6.88</td><td>6.68</td><td>2.88</td><td>5.24</td><td>4.63</td><td>4.44</td><td>1.25</td><td>2.63</td></tr><tr><td>Fe<sub>2</sub>O<sub>3tot</sub> (wt.%)</td><td>59.97</td><td>57.61</td><td>57.17</td><td>48.05</td><td>59.13</td><td>64.44</td><td>54.00</td><td>74.59</td></tr><tr><td>MgO (wt.%)</td><td>0.75</td><td>0.74</td><td>0.45</td><td>0.66</td><td>0.35</td><td>0.17</td><td>0.02</td><td>0.05</td></tr><tr><td>MnO (wt.%)</td><td>0.19</td><td>0.19</td><td>0.09</td><td>0.07</td><td>0.07</td><td>0.05</td><td>0.01</td><td>0.06</td></tr><tr><td>CaO (wt.%)</td><td>0.6</td><td>0.85</td><td>0.51</td><td>0.61</td><td>0.69</td><td>0.74</td><td>0.01</td><td>0.01</td></tr><tr><td>Na<sub>2</sub>O (wt.%)</td><td>0.02</td><td>0.01</td><td>0.01</td><td>0.02</td><td>0.02</td><td>0.01</td><td>0.01</td><td>0.00</td></tr><tr><td>K<sub>2</sub>O (wt.%)</td><td>0.93</td><td>0.67</td><td>0.51</td><td>0.48</td><td>0.42</td><td>0.33</td><td>0.00</td><td>0.01</td></tr><tr><td>P<sub>2</sub>O<sub>5</sub> (wt.%)</td><td>0.6</td><td>0.37</td><td>0.52</td><td>0.34</td><td>0.29</td><td>0.29</td><td>0.35</td><td>0.69</td></tr><tr><td>SUM</td><td>101.22</td><td>101.26</td><td>100.84</td><td>100.77</td><td>101.07</td><td>100.95</td><td>99.96</td><td>99.95</td></tr><tr><td>SiO<sub>2</sub>:Al<sub>2</sub>O<sub>3</sub></td><td>4.32</td><td>4.88</td><td>13.09</td><td>8.45</td><td>7.38</td><td>6.60</td><td>1.96</td><td>1.78</td></tr><tr><td>Ba (ppm)</td><td>257</td><td>168</td><td>93</td><td>89</td><td>111</td><td>0</td><td>0</td><td>135</td></tr><tr><td>Ce (ppm)</td><td>0</td><td>39</td><td>28</td><td>0</td><td>73</td><td>56</td><td>45</td><td>76</td></tr><tr><td>Co (ppm)</td><td>311</td><td>275</td><td>330</td><td>187</td><td>279</td><td>242</td><td>284</td><td>279</td></tr><tr><td>Cr (ppm)</td><td>186</td><td>172</td><td>66</td><td>53</td><td>112</td><td>153</td><td>55</td><td>31</td></tr><tr><td>Rb (ppm)</td><td>43</td><td>28</td><td>22</td><td>21</td><td>26</td><td>24</td><td>0</td><td>24</td></tr><tr><td>S (ppm)</td><td>149</td><td>47</td><td>101</td><td>122</td><td>115</td><td>39</td><td>0</td><td>11</td></tr><tr><td>Sr (ppm)</td><td>43</td><td>57</td><td>33</td><td>37</td><td>41</td><td>41</td><td>0</td><td>0</td></tr><tr><td>Th (ppm)</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>V (ppm)</td><td>74</td><td>99</td><td>44</td><td>32</td><td>65</td><td>62</td><td>55</td><td>41</td></tr><tr><td>W (ppm)</td><td>77</td><td>112</td><td>73</td><td>43</td><td>74</td><td>109</td><td>157</td><td>364</td></tr><tr><td>Zr (ppm)</td><td>75</td><td>57</td><td>29</td><td>102</td><td>53</td><td>35</td><td>0</td><td>17</td></tr></tbody></table>

<table><caption>Calculated Amount of Material for 100g of Slag</caption><tr><td>Ore (g)</td><td>148</td><td>159</td><td>163</td><td>199</td><td>156</td><td>135</td></tr><tr><td>Slag (g)</td><td>100</td><td>100</td><td>100</td><td>100</td><td>100</td><td>100</td></tr><tr><td>Iron (g)</td><td>33</td><td>40</td><td>43</td><td>68</td><td>38</td><td>24</td></tr><tr><td>Yield (%)</td><td>40</td><td>49</td><td>53</td><td>66</td><td>49</td><td>47</td></tr></table>

161
162
163
164
165

4.2. Estimation of the metal production

The quantity of produced metal can be estimated through mass balance calculations, a method detailed by several authors (Serneels, 1993; Leroy et al., 2015; Morel and Serneels, 2021). The mass balance approach is based on the principle of the conservation of mass. The mass of the materials
introduced into the furnace must be equal to the mass of the materials coming out of it. In a simplified approach, only four components will be considered to make the calculation:

$$ \text{Principle Ore} + \text{Contamination} = \text{Slag} + \text{Iron.} $$

These calculations necessitate a good understanding of the relationships between ores and slags.

Although data is also limited for the other two technical traditions, but we can nevertheless make some observations. The results of mass balances calculations for KAN1 and KAN3 are in Tables 2 and 3.

### 4.2.1. Iron production for the KAN1 smelting tradition

Only one ore sample (DMB351) compatible with KAN1 slag was recovered and can be used in mass balance calculations. Mass balance calculations for the F301 site, using DMB351 as the average ore value, lead to an estimate of 110g of iron produced per 100g of slag (Table 2). While mathematically possible, this value is exceptionally high. The ore sample DMB351 has particularly high iron content (89 wt.% $Fe_2O_{3tot}$). It is challenging to believe it represents the average ore content introduced into the furnace. With the available data, it is not possible to estimate the average composition of ores introduced into the furnace, but it is undoubtedly lower than that used in the calculations. Moreover, estimating the slag mass produced in each smelting operation for KAN1, and thus determining the mass of iron produced per operation, is difficult.

Lastly, the results of the mass balance calculations using DMB351 as a fixed ore are highly reproducible for KAN1 and show little variation from one slag to another. Reducing conditions in the KAN1 furnace seem poorly variable from one smelting operation to another.

### 4.2.2. Iron production for the KAN3 smelting tradition

Similarly, for KAN3, only one ore sample (DMB323) is compatible with F110 slag. This sample shows credible iron oxide content for an average ore (75 wt.% $Fe_2O_{3tot}$). However, due to the variability of the $SiO_2:Al_2O_3$ ratios of KAN3 slags, sample DMB323 perfectly matches only one slag sample (DMB125),
which happens also to be an extreme value. To estimate metal production for other slag pieces, theoretical ores can be modelled (Figure 2-D). For this, it can be assumed that the average iron content of the ore introduced into the furnace is the same as measured in DMB323 for all smelting operations.

The silica and alumina contents can then be recalculated while maintaining the SiO₂:Al₂O₃ ratio of the related slag sample. It should be kept in mind that these calculations only provide an estimation of productions. We could thus calculate an average of 36g of iron produced per 100g of slag (Table 3).

For KAN3, it is known that the large BFS blocks weigh approximately 300kg. According to the mass balance calculations, this would imply that metallurgists produced about 100kg of metal per smelting operation. Although it is a very significant metal mass, there are documented cases in different contexts with blooms equally heavy (Köstler, 1986; Pleiner, 2000).

## 5. Efficiency of a smelting tradition

<figure><img src="image_7.png" /><figcaption>Figure 3: Theoretical representation of the efficiency of a smelting technique and the various factors that need to be considered. The proportion between the different efficiencies (technical, economic and social) varies from one technical tradition to another.</figcaption></figure>

Efficiency is a concept that lacks clear definition in the literature, despite its common usage (Charlton et al., 2010). A technical tradition exists within the context of a human society, with implications more
complex than merely attempting to optimize production. Hence, we propose here to define the
concept of efficiency in the broadest possible framework, considering the technical, economic, and
social efficiency of a technical practice simultaneously (Morel, 2022). A number of criteria must be
estimated for each of the efficiencies (Figure 3). This paper focuses on ancient iron production, but the
same conceptual model can be applied to various types of production.

216

217 **5.1. Technical efficiency**

Technical efficiency focuses only on furnace operational considerations. The objective is to assess metallurgists' success in maximizing metallic iron extraction from their ore and their mastery of the technique. Thus, the preliminary study of ores is crucial. Evaluating technical efficiency relies on three criteria: **yield, technique optimization, and standardization**.

Much of the discussion on technical efficiency is based on phase diagrams within the chemical system of iron slag, particularly the bivariate FeO<sub>n</sub>-SiO<sub>2</sub> diagram (Kowalski et al., 2000 - see Figure 4). This diagram simplifies the system by omitting other major elements like aluminum, titanium, manganese, etc. However, the trivariate SiO<sub>2</sub>-Al<sub>2</sub>O<sub>3</sub>-FeO phase diagram could be used and allow more detailed observations.

The ore's initial chemical composition is represented by the orange point on the figure 4. During smelting, iron oxides are reduced, transforming into metal, shifting the remaining ore composition. Simultaneously, furnace temperature rises until reaching the melting point of iron-depleted ore, resulting in slag. The curve's slope, depicting ore composition evolution during smelting (Figure 4 - red line), depends on temperature rise speed, process duration, and the furnace's reducing atmosphere quality. Longer smelting before slag melting allows more iron extraction. However, for iron oxides content below 62 wt.% Fe<sub>2</sub>O<sub>3tot</sub>, the slag's melting point becomes too high for a bloomery furnace (Figure 4). Excessive iron reduction makes slag melting and separation from metal impossible. Optimal ore treatment varies for iron-rich and iron-poor ores:
236

* A high-quality ore (85 wt.% Fe₂O₃tot) can yield significant metal, requiring a slow smelting

237

process below slag melting temperatures to recover maximum metal.

238

<figure><img src="image_8.png" /><figcaption>Figure 4: SiO₂ – FeO phase diagram: Modelling of the evolution of the chemical composition of the slag (Kowalski et al., 2000) according to the initial iron content of the ore (orange point), time and the rate of temperature rise in the bloomery furnace.</figcaption></figure>

239

240

241
242

243

244

245

* In contrast, for low-quality ore (70 wt.% Fe₂O₃tot), rapid temperature rise is beneficial to reach the melting point; otherwise, the temperature becomes too high.

246

Hence, a smelter accustomed to working with poor ores may not produce more iron with a better ore.

247

248

249

The operating mode, linked to the ore type, directly influences iron quantity, yield, and technical efficiency. Therefore, addressing technical efficiency requires archaeometallurgical studies to comprehend ores, not just smelting structures.

250

251

### The yield

252

253

254

The yield is a simple initial approach to technical efficiency. It represents the ratio of iron produced per 100g of ore to the iron present in 100g of ore. This allows the assessment of the proportion of iron produced relative to the quantity of iron available in the ore, according to the formula:

255

$$ \text{Yield} = \frac{\text{FeProduced}}{\text{FeOre}} \times 100 $$

256

257

258

In the case of the F301 heap in KAN1, the yield ranges from 65% to 77% depending on the slag, which are exceptionally high values and likely need adjustment as the ore is not well-known. The F110 heap in KAN3 would have a more typical yield ranging from 40% to 53%.

259

260

### Optimization of a smelting technique

261

262

263

264

To assess how well a smelting technique optimizes the available ore, the FeOₙ-SiO₂ phase diagram can be used (Figure 4). As mentioned earlier, it is exceedingly difficult to melt slags with iron oxide content below 62 wt.% Fe₂O₃tot. Therefore, this composition is considered the technically ideal composition to achieve. The optimization of a technique can be calculated using the formula:

265

$$ \text{Optimization} = \frac{[\text{FeOn}]_{\text{ore}} - [\text{FeOn}]_{\text{slag}}}{[\text{FeOn}]_{\text{ore}} - 62} \times 100 $$
266 Applying this formula, assuming the analyzed ores indeed correspond to what was introduced into the
267 furnace, leads to an optimization of 69% for the F301 heap of the KAN1 technique, compared to 97%
268 for the average slag of the F110 heap of the KAN3 technique. As seen before, the iron oxide content
269 of the average ore for KAN1 is likely lower than that used in the calculations, so the actual optimization
270 of F301 is probably higher than calculated. Nevertheless, Figure 4 indicates that the technique used at
271 F301 is less optimized than that used at F110. These two heaps represent however extreme cases. A
272 similar approach with the other heaps tends to show that the difference of optimization is weakly
273 significant. The KAN3 tradition may be slightly more optimized in certain cases than the KAN1
274 technique.

275

276 Standardization of a smelting technique

277 The evaluation of the standardization of a smelting technique help to better understand the expertise
278 of metallurgists. The more standardized a technique, the less variable the quantity of produced metal
279 from one smelting operation to another (Morel and Serneels, 2021). A technique with a very variable
280 production would thus be considered less technically efficient than one producing consistent medium
281 quantities. To do this, we can look at the variance in metal production for each technique and compare
282 them.

283 More samples of both ore and slag would be needed to delve deeper into the standardization of
284 production for KAN1 and KAN3. However, it appears that in both cases, they involve relatively
285 consistent and reproducible productions from one smelting operation to another. When comparing
286 the variance in the amount of metal produced per 100g of slag per smelting operation, for F301 and
287 F110, no significant difference can be observed (Levene's test, p = 0.169). Therefore, it does not appear
288 that one technique is more standardized than the other.

289

290 5.2. <u>Economic efficiency</u>
Economic efficiency can be likened to the profitability of a production. Estimating the economic efficiency with the archaeological data available in this project is challenging, but a number of ideas are suggested here.

First, the **production** of iron per unit of time must be compared. This involves on-site estimation of the volume of metallurgical waste (Robion-Brunner and Serneels, 2017) and deducing the quantity of metal produced, for example, over a 100-year production period.

Next, the **ratio between costs and the value** of production must be considered (Liu et al., 2023). Evaluating the cost of production is particularly challenging due to various factors, including the availability of raw materials, as well as the number and salary of people involved at the different steps of the *chaine opératoire*. An advanced treatment of ore, such as meticulous washing, sorting, grinding, or roasting, also increases production costs. Similarly, the use of slaves reduces production costs compared with the employment of skilled free labourers. On the other hand, the value of production can be assessed through the quality of the product and its rarity, considering both the community's iron needs (agriculture, craftsmanship, daily life, weaponry, construction, and navigation) and the metal's availability.

Lastly, the **degree of specialization** of workers needs discussion. In a society with specialized workers employed full-time, there is an implied need for others to produce food for them. In other cases, production is managed during the slow agricultural periods of the year. These two cases reflect two different economical model.

<table><caption>Table 4: Estimation of the volume of slag produced for each technique and each site, as well as the overall estimation of the quantity of iron produced.</caption><thead><tr><th>Technologie</th><th>Site</th><th>Period of activity</th><th>Mass of slag (T)</th><th>Estimated total iron production (T)</th><th>Total (T)</th></tr></thead><tbody><tr><td>KAN1</td><td>Siola Doumbala</td><td>11th-13th</td><td>500<br>100-300</td><td>500<br>100-300</td><td>600-800</td></tr><tr><td>KAN2</td><td>Siola Doumbala</td><td>16th-17th</td><td>5000-10000<br>500</td><td></td><td></td></tr><tr><td>KAN3</td><td>Siola Doumbala</td><td>17th-19th</td><td>2000<br>5000-10000</td><td>700<br>1800-3500</td><td>2500-4200</td></tr></tbody></table>
We cannot make precise estimations of the economic efficiency of KAN1 and KAN3, but we can still contribute to the discussion. The KAN1 technique leads to a maximum production of 600-800 tons of metal over approximately three centuries (Table 4). Slag from the same heap have similar chemical compositions, which implies that the same deposit was exploited for a single smelting workshop, and perhaps the ore was well-sorted. If indeed the significant MnO contents found in the slags come from a flux, some workers must have been mobilized to extract it, increasing production costs.

The KAN3 tradition is a mass production system with an estimated 2500-4200 tons of iron in total over three centuries (Table 4). Such extensive production requires the extraction of a considerable extraction of ore, as can be seen from the diversification of the deposits used. The ore for KAN3 was hence more variable than for KAN1, potentially to lower production costs.

### 5.3. Social efficiency

Social efficiency is the most challenging aspect to consider in archaeological studies. It can sometimes be approached with historical or ethnographic sources, but it certainly cannot be inferred only from archaeological data. In the case of the Kaniasso district, our knowledge is simply not sufficient to evaluate the social efficiency of these technologies.

Firstly, to understand the social efficiency of a production, we must consider the **consumption** of a given society. Societies can have low or high iron consumption and very various needs (Serneels, 2004).

Then, the purpose of any production is to **meet the needs** of the community. A society with low iron consumption may not need to produce large quantities of metal. In such a case, low production can be socially efficient. Moreover, in some cases, such as during wartime when a large amount of metal is needed immediately, social efficiency takes precedence over economic efficiency: production does not necessarily have to be profitable; it must be sufficient.

Social efficiency cannot exclude the **ritual aspect** present in some technical practices, especially in iron metallurgy (Célis, 1991). Some productions are not only aimed at fulfilling metal needs because other sources of supply could be considered, but rather to preserve rituals, myths, traditions, or social positions, such as the caste system of blacksmiths.
339

340

341

342 **6. Conclusions**

343 An in-depth study of the analyses conducted on the slag from the Kaniasso district, despite being
344 limited, has helped to better define the technical traditions of KAN1 and KAN3. Therefore, beyond
345 differences in furnace shapes and the production of different slag morphology, KAN1 and KAN3
346 techniques reveal distinct production organizations.

347 This first study indeed indicates that metallurgists from the KAN1 tradition used homogeneous ores,
348 likely associated with a manganese addition that lowered the slag's melting point (Kowalski et al.,
349 2000). The technique appeared to be well-mastered, enabling significant and relatively consistent
350 production, although it was not fully optimized. The KAN3 technical tradition was a mass production
351 that yielded impressive results. Metallurgists had to exploit highly variable ore deposits to sustain such
352 production. The variability in ores likely influenced the quantity of metal produced per smelting
353 operation (Robion-Brunner, et al. 2022). Nevertheless, it seems that the KAN3 technique was slightly
354 better optimized than KAN1.

355 An efficiency-based approach is both promising and would enable a more nuanced comprehension of
356 the diversity of smelting techniques. This goes beyond a simple comparison between slag and ores,
357 prompting questions about the mastering of a technique, as well as about the societies to which they
358 belong. More complete data on the KAN2 tradition could have offered a better understanding of the
359 transition and technical choices between KAN1 and KAN2. The next step would be to apply this
360 approach to other technical traditions in different metallurgical districts to see if similar dynamics are
361 observed during technical transitions.

362 This study also highlights the importance of improving the sampling during fieldwork. Relying on
363 numerous small samples from various slag heaps does not provide sufficient statistical representativity
364 to advance meaningful insights. Furthermore, in archaeometallurgical studies, there is a crucial need
365 for a better understanding of ores, both in the field and the laboratory. An understanding of ores is
366 indispensable for meaningful reflections on production processes.

367

368 Acknowledgement

369 We would like to thank Alexandre Salzmann, Patrick Dietsche, Christoph Neururer and Ildiko
370 Katona-Serneels from the University of Fribourg (Switzerland) for technical or scientific support for
371 the laboratory work. This project could not be completed without the active participation of the
372 fieldwork team from 2013 to 2017. Thanks also to Madalina Bonta for allowing us to use her thesis
373 and field data. The project was funded as part of a Fyssen Foundation postdoctoral fellowship in
374 2023. We would like to thank the Université Toulouse Jean Jaurès and the TRACES laboratory for
375 hosting this post-doctoral project.

376

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