A causality-weighted approach for prioritizing mining 4.0 strategies integrating reliability-based fuzzy cognitive map and hybrid decision-making methods: A case study of Nigerian Mining Sector

Abstract

Nigeria's economy depends solely on crude oil with little attention to the agricultural and solid mineral sectors which were the major sources of revenue prior to the 1970s “oil boom”. However, some improvements were recently recorded from the solid mineral sector as the sector contributed meaningfully to the GDP in the last three years. The contribution of this sector is still extremely low as compared to the oil sector. Hence, there is need to explore the recent technology in improving the solid mineral contribution to GDP. This study therefore explores the application of industrial 4.0 for selecting the best strategy in the Nigerian mining sector using the extended combined compromise solution (COCOSO) technique with the fuzzy cognitive map (FCM). The fuzzy COCOSO is structured by using causal-and-effect weights. Notably, the FCM and fuzzy-COCOSO are implemented in a reliable environment as the Z-number concept is used for overcoming uncertainty of system. Ten copies of questionnaires comprising nine mining 4.0 strategies (alternatives) and 15 criteria were provided by a ten-member team of experts. The main goals in the decision system were minimising implementation costs (G1), maximising financial incomes from smart mining strategies (G2), maximising government financial support to use smart technologies (G3), minimising hazardous events (G4), and maximising safety in operations (G5), which are considered in the ZFCM topology. In the final step of research, the effectiveness and robustness of the nine proposed mining 4.0 policies were investigated by using a parametric sensitivity analysis. Based on the presented hybrid model, it is concluded that the third policy (A3, internet of things) is the best option for intelligent mining in the Nigerian mining sector. It was confirmed by an expert team that obtained results were valid and that the factors and conditions in the study area were worth evaluating and validating.