The application of new technologies has a significant effect on increasing the efficiency and improving the productivity of production factors in various industries, such as the mining industry. This requires implementing correct and practical strategies, and any incorrect procedure can cause companies and businesses to waste resources. Accordingly, the main aim of this study is to determine attractive strategies for the use of so-called fourth-generation technologies (industry 4.0) in the mining sector of Iran. To do this, a multi-criteria decision-making (MCDM) problem was employed. Therefore, this study presents a new method for evaluating and prioritizing smart mine strategies using a combination of Z-number theory and fuzzy weighted Vikor technique with a fuzzy cognitive map (FCM). In this regard, questionnaires containing five strategies (options) and 11 criteria were designed and presented to a team of eight experts. The results obtained from the prioritization of the proposed hybrid model confirm that the strategy of "provision of government incentives to mines to use up-to-date technologies" is the most appropriate alternative for implementing industries 4.0 in large-scale mines in Iran. Furthermore, a parametric sensitivity analysis was performed to determine the effectiveness of the proposed strategies. Results showed that the proposed strategy is a fixed mechanism for ranking smart mining engineering strategies. Meanwhile, the weight of the strategy does not affect their ranking.

In today's highly competitive manufacturing environment, an effective supplier selection process is very important for the success of any business organization. Selection of the best supplier is always a difficult task for the purchasing manager. Suppliers have varied strengths and weaknesses which require careful assessment by the purchasing manager before selecting and ranking them. Any supplier selection procedure is to be based on the establishment of various criteria which may include quality, cost efficiency, delivery dependability, volume flexibility, information and customer service. This paper attempts to solve the supplier selection problem using two most potential multi-criteria decision-making (MCDM) approaches and compares their relative performance for a given organizational environment. The first MCDM approach is 'Vlse Kriterijumska Optimizacija Kompromisno Resenje' (Vikor), a compromise ranking method and the other one is 'ELimination and Et Choice Translating Reality' (ELECTRE), an outranking method. These two methods are used to rank the alternative suppliers, for whom several requirements are considered simultaneously. Two real-time examples are cited in order to demonstrate and validate the effectiveness and flexibility of these two MCDM methods. The rankings of the alternative suppliers as obtained using these two MCDM methods almost match with those as derived by the past researchers.

Plant location selection has invariably a significant impact on the performance of many companies or manufacturing systems. In this paper, a new integrated methodology is structured to solve this selection problem. Two well-known decision making methods, namely analytic hierarchical process (AHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (Vikor), are combined in order to make the best use of information available, either implicitly or explicitly. In addition, the Delphi method is utilized to select the most influential criteria by a few experts. The aim of using the AHP is to give the weights of the selected criteria. Finally, the Vikor method is taken into account to rank potential alternatives. Finally, an application example demonstrates the suitability of the proposed methodology.