Assessment of Dredging cost through Comparative Analysis A case study of Dredging System in Lagos Metropolis (Published)
Globally, dredging removes sediment from sea, river, and lake beds and moves it. Both descriptive and inferential statistical methods were used to organize and analyze the data. This study found that the conventional dredge (CD) has a higher production capacity than the transporter dredge (TD), but a higher production cost. Both traditional and transporter dredging methods cost about the same per unit volume to mine sand. TD manufacturing at Nidest Integrated Company costs and volume are slightly higher than CD in the first two months. In six months, the CD had a total cost/volume of ₦3849 for sand dredging, while the TD had ₦3268. Prime Engineering Company has a total cost/volume of ₦3121 for CD and ₦2664 for TD. Except for the CD at Nidest Company, the cost/volume drops over time. CDs cost more per volume than TDs for both suppliers. The independent t-test supports the null hypothesis, showing that CD and TD companies produce the same volume and cost. Prime Engineering Company’s Pearson correlation investigation showed a substantial positive and statistically significant correlation (R = 0.909, N = 6, p-value = 0.012) between transporter and conventional dredgers. However, Nidest Company had a weak positive and non-significant connection between TD and CD (R = 0.571, N = 6, p-value = 0.236). The findings imply that TD is cheaper than CD, despite CD’s higher daily manufacturing capacity.
Keywords: Comparative Analysis, Mining, Sand, dredge, operation improvement
Comparative Analysis of Economic and Profitability of Artisanal Gold Mining in Part of Niger and Osun States, Nigeria (Published)
Comparative analysis of economic and profitability of artisanal gold mining in part of Niger and Osun states was carried out to assess the cost of production, assess the production rate of alluvial and elluvial gold deposits in the study areas, determine the concentrates of alluvial and elluvial gold deposits in the study areas, compare the concentrates of alluvial and elluvial gold deposits in the study areas and determine the level of profitability in the study areas. The concentration of alluvial gold deposits was carried out using FAS – 121 Au Fire Assay, 50 g Fusion, AAS Trace Level analytical method while that of the elluvial gold deposits was carried out using FAS – 425 Au Fire Assay, 50 g Fusion, Gravimetric analytical method. The cost of production for alluvial gold deposits in Osun state were computed to be N30,000.00, N38,000.00 and N27,000.00 at Isereyun, Samuaye and Okere Oloja Villages respectively while that of elluvial gold deposits in Niger state were computed to be N125,000.00, N98,000.00 and N95,000 at Tutugo, Paiko and Bosso Villages respectively. The comparison of gold concentration in the two states shows that the elluvial gold deposits in Niger state has higher concentrates than the alluvial gold deposits in Osun state which could be due to the fact that elluvial deposits are mostly host rock for gold deposits. The level of profitability in alluvial gold deposits in Osun state ranges from 300% and 400% after the cost of production while that of elluvial gold deposits in Niger state ranges 300%, 400% and 500% after the cost of production. With the level of profitability of the alluvial and elluvial deposits, it can be observed that the profitability for all locations were close but there were differences in the cost of production.
Keywords: Gold, Mining, Nigeria, Profitability, artisanal, fire assay
Prediction of Gold associated Mineral worth: An application of mathematically driven artificial neural network technique (Published)
The elemental composition of other associate minerals existing with gold is a significant asset that defines the amount of additional economic contribution that can be obtained from the gold tailings. The elemental composition is a needed factor in increasing the economic value of gold run-off and getting a clear estimation for the quantity of value-added elements in each tonne of gold sand scooped during the separation process. In this study, the artificial neural network (ANN) modeling technique was used to develop an economic worth prediction model for 10 gold-associated minerals. The developed models have a 1:7:10 architecture and were trained using the ANN Bayesian regularization training algorithm. According to the root mean square error values, the results revealed that the predicted values of the associated minerals are closer to the measured values. Also, the developed model prediction performance was found to be appropriate for the estimation of gold-associated mineral economic benefits based on the high coefficient of determination and variance account. The model performance evaluation results show that the developed ANN models are suitable for economic estimation of gold-associated mineral worth.
Keywords: Artificial Intelligence, Gold, Mining, Nigeria, machine learning algorithms, mineral economics