Methods Towards Mine Internet Info In The Direction Of Guide Business Intelligence

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Methods Towards Mine Internet Info In The Direction Of Guide Business Intelligence

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Received: November 6, 2020 / Modified: December 6, 2020 / Accepted: December 8, 2020 / Published: December 10, 2020

The Industrial Internet of Things (IIoT) has the potential to improve production and business processes by enabling the extraction of valuable information from industrial processes. The mining industry, however, is very traditional and somewhat slow to change due to infrastructure limitations in communication, data management, storage, and information exchange. Most of the research efforts so far on the application of IIoT in the mining industry have focused on specific concerns such as weather monitoring, accident analysis, fleet and personnel management, tailings monitoring, and early warning system while a general IIoT architecture for the condition and general conditions included. the mining industry is still missing. This article analyzes the current state of Information Technology in the mining sector and identifies a major problem of vertical fragmentation due to the technological variety of different systems and devices offered by different vendors, preventing integration, data distribution, and communication. secure information between devices. and systems. Based on the guidelines and practices from the main IIoT standards, a high-level IIoT architecture suitable for the mining industry is then compiled and presented, solving the identified challenges and supporting automation, integrated systems, data distribution , and real-time visibility enables intelligent mining. mining situation. Remote control, data processing, and architecture integration technologies are advancing all phases of mining from exploration to innovation. Adopting this type of IIoT architecture in the mining industry provides a safer mine environment for workers, predictable mining operations, a unified environment for both traditional and modern systems and devices, automation to reduce human intervention, and enables underground monitoring. with compatible operational technology (OT) and information technology (IT). Important open research issues and directions are also studied and identified in this paper, such as mobility management, scalability, virtualization at the IIoT edge, and digital twins.

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The Internet of Things (IoT) is a technological paradigm envisioned as a global network where devices or machines can communicate [1]. IoT acts as a technological revolution that affects all application domains, including smart home, smart cities, agriculture, automobile, healthcare, industrial production, and transportation [ 2 , 3 ]. It is estimated that by 2020, 50 to 100 billion objects and smart objects will be connected to the Internet [4, 5, 6]. In this context, industries are challenged to rethink their production processes with the potential to fuel innovation in production systems at an unprecedented level [7].

The Industrial Internet of Things (IIoT), which is the application of IoT in industry, is part of the concept of Industry 4.0, which focuses on the idea of ​​continuous digitalization and the connection of all productive units [8], combining traditional forces. industry with internet technologies [9, 10]. The Industrial Internet can also be considered as the convergence of Information Technology (IT) and Operational Technology (OT) as shown in Figure 1. The IIoT is a network of physical objects, or objects, connected by electronics, sensors, and connectivity to enable it. network to achieve greater value and service by exchanging data with manufacturers, operators, and/or other connected devices [11]. Currently, many IoT technologies are being integrated into consumer applications, such as smart homes, connected cars, and smart clothes. However, industrial applications of IoT, or Industrial IoT (IIoT), are expected to have the capacity to transform many industries, including manufacturing, oil and gas, agriculture, and mining [12].

The scope of this research is the adoption of IIoT in the mining industry, especially in the case of underground mining. The specific complications and challenges in this industry are: heterogeneity where each mine has a different design according to natural conditions, heavy transport combined with very confined areas, wireless communication between shafts and stopes is not possible, explosion repetitively where the equipment will be destroyed until it runs out every time, facing drilling that is constantly changing the design, the need for failover and autonomous operations to ensure productivity and safety with catastrophic failures, etc. This difficulty is due to the need for continuous production of large volumes of ore that is extracted in order to reach the targeted goals set to ensure profitability in production. Other types of industries may catch up after production stops, while in mining lost production is usually not recovered by an additional phase of operations. The unique combination of these conditions is a motivation for research. In particular, it is complicated by the need for flexible and adaptable IIoT systems with the constant change in topology and the use of devices and machines combined with the need to ensure productivity and security, even though the connection may sometimes fail. .

In this article, we study the current practices of information technology (IT) in the mining industry and find a great difficulty of interoperability between different systems and devices. Connectivity [13] is a feature in an architecture where different systems or devices can communicate with other systems and devices to exchange, understand, and use information. The article also presents a survey of architectural models and features of some common IIoT frameworks, compares them in the perspective of the needs of the mining industry, and identifies future challenges and open issues. With advances in information technology, the mining industry is increasingly adopting digital solutions and technology. The main objective of this certification is to achieve the best solutions based on cost and production, increasing safety measures, and developing their intelligent systems. Most mining companies collect data using sensors and mobile telemetry to facilitate operational managers to improve operational efficiency. These certifications are often carried by individual mining companies to meet their specific needs and are not well standardized for universal certification in the mining industry. The operations and operation of the mining industry are different from other industries such as manufacturing, agriculture, and transportation industries, etc.

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Boliden AB [14] is a Swedish company that focuses on the production of copper, zinc, lead, gold and silver. They are among the pioneers in the digitization [15] of mining operations and are therefore representative as a basis for innovation. Boliden’s overall strategy is to create profitable growth that is adapted to new market trends and investments in competition and organic growth; and by evaluating opportunities for acquisitions. For data-driven processes, insights and decisions are becoming increasingly important. Many mining sites have very mature proprietary systems in place, but when it comes to interoperability with different systems or information sharing among departments or stakeholders, analytical capabilities, innovative IIoT practices, and architecture, improvements are needed. A strategy has been put in place and many projects are ongoing such as reporting and visualization of process data, setting up a production data platform for mines, ideas on a common data platform for materials as well as activities coordinated by automation programs. Historically, Boliden works in a decentralized model, and in terms of reporting and analytics, business areas and websites have started to coordinate activities effortlessly. Moreover, to achieve scalable and scalable systems, there is a need to analyze industry standards and practices and put them in a mining industry perspective.

Industrial IoT standards and initiatives are evolving and many industries benefit (e.g., increased efficiency, reduced errors, predictive maintenance, improved safety, and cost reduction) [16] from industrial IoT standards and guidelines such as the manufacturing industry [17, 18 ], healthcare, smart cities [ 19 ], and transportation [ 20 ]. The purpose of this article is to investigate the possibility of applying IIoT in the mining industry if these standards and initiatives provide guidelines that can benefit the mining industry. In addition, this study shows how these standard guidelines can help to solve the current problems in the mining industry, e.g.

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