Industrial Internet Technologies Research Articles

Research on key technologies for industrial field communication quality analysis

With the widespread application of intelligent manufacturing and industrial internet technologies, higher requirements for the reliability, stability and robustness of industrial communication networks have been put forward. To achieve these requirements, the detecting and evaluating diagnostic technology for industrial field communication is essential. This paper analyzes the key technologies and difficulties of detecting and evaluating diagnostic technology from the four aspects of access, collection, communication and evaluation & diagnosis and proposes some feasible solutions to provide a new perspective for further in-depth research.

Research on 5G Security Technology for Industrial Internet

5G network has great application potential in the field of industrial Internet. However, the current lack of development of 5G network in the field of security technology restricts its application on the Industrial Internet. In this article, the author combines the industry’s needs for Industrial Internet security, and summarizes the research status of 5G network security technology, gives the development direction of three 5G network security technologies with development potential. This paper found that due to the three end-to-end characteristics of the Industrial Internet: physical security, information security, and system self-healing, there are security requirements; the other three 5G network security technologies, namely lightweight encryption mechanism, physical layer security technology and network slicing security technology will help 5G network be more widely used in the Industrial Internet field.

On the Intelligent Manufacturing

With the German "Industry 4.0" strategy and the American industrial internet technology, as well as the "Made in China 2025" plan proposed by China, countries around the world are paying more and more attention to the transformation and development of a new round of manufacturing industries. Intelligent manufacturing is bound to trigger a new industrial revolution and make a huge leap in manufacturing. Intelligent manufacturing is a manufacturing technology that conforms to the new development situation of the manufacturing industry, and it is also one of the important development strategies for countries to strive to become a manufacturing power. This article starts with the development process of the manufacturing industry, briefly introduces the historical development stage of the manufacturing industry and the current situation of intelligent manufacturing, and further analyzes the future of intelligent manufacturing.

Research on 5G+MEC Industrial Internet Technology Testing Platform

The 5G+MEC Industrial Internet technology test platform is committed to the application of 5G technology in industrial scenarios. The test platform is supported by 5G+MEC as the technical architecture, and is integrated with machine vision, AR, AGV and other applications; The test platform adopts a modular design. Starting from the test scenarios of the manufacturing process such as interaction, customization, and production, some technologies are transformed into mature solutions through testing, which shortens the application cycle of new technologies and promotes the development of the Industry. Internet.

Innovative Development of a Human-Centered Economy in the Context of Overcoming the Pandemic

The article examines the theoretical and practical aspects of the innovative development of the human-centered economy in the context of overcoming the pandemic. The relevance of the study is confirmed by the fact that the world of high technologies, accelerated development and violent digitalization creates new rules of life. To the traditional risks that influenced humanity and caused crises in the past, the study adds new ones related to privacy of personal data and cybersecurity, artificial intelligence and new jobs, instant information dissemination and manipulation of public opinion, inequality of opportunities and environmental threats. It is concluded that the pandemic has become a powerful trigger for innovation. Social distancing technologies, which were especially popular during the coronavirus outbreak, are at the peak of demand. The pandemic has also adjusted the logic of providing government support to technology entrepreneurs. Among the priorities is support for domestic digital services that improve the quality of life online and provide social distancing. In conclusion, it was concluded that each crisis is unique, just as unique are the recipes for overcoming it, and each new wave brings new recipes to the entrepreneur and investor's piggy bank of how to build a sustainable business that is not afraid of threats of any type - from financial to biological. To protect oneself technologically from the shocks associated with the crisis, maximum digitalization of business processes and the use of modern business models, industrial automation using industrial Internet technologies, predictive analytics, the use of the most modern digital sales channels, and investments in personnel development are required. These and many other factors make up a modern sustainable business model.

Industry 4.0 Development Prospects and Introduction Readiness into Russian Enterprises

Today the competitiveness of the Russian economy is closely dependent on the successful introduction of new digital technologies into the domestic industry. In the study, the authors analysed features of the industrial revolution in Russia and other countries. It was discovered that the industrial Internet is currently underutilized in the Russian market. However, one of its notable characteristics is the dominance of the industrial segment in the Russian Internet of Things, which indicates promising development prospects for the industrial Internet technology in Russia. The authors also analysed readiness of Russian enterprises to introduce Industry 4.0 technologies. Although the enterprises clearly expressed their readiness to implement digital technologies, there are some objective difficulties that set back the process. The main obstacles that prevent the integration of the industrial Internet into the Russian industry are insufficient flexibility of enterprises, a lack of developed digital business models of companies, a shortage of skilled personnel, and limited funding. In the conclusion, the authors set some objectives that need to be addressed in order to facilitate the development of the industrial Internet in Russia based on the findings of the study.

Research on Open Mining Intelligent Equipment Based on Internet

Based on the establishment of mines, the use of advanced industrial Internet technology, based on the solid model and block model, using 3DMine smart equipment software to study the intelligent collection equipment of open pit mines, through the intelligent research of equipment, research and development It has developed advanced quota intelligent equipment, including intelligent sorting system and intelligent collection device system, etc., and discussed the influence and application of different intelligent equipment in the state of open pit mine. The preliminary design provides a technical plan and decision basis for smart equipment.

A research on remote fracturing monitoring and decision-making method supporting smart city

Based on the investigation of the development of fracturing monitoring at home and abroad, this paper studies the mechanism of fracturing fluid injection and fractures monitoring, and puts forward a remote fracturing monitoring and decision-making method suitable for conventional wells. Firstly, combined with the dynamic monitoring model of fracturing fluid, many parameters are optimized and analyzed. The velocity monitoring of fracturing fluid is realized by constructing the average velocity formula of fracturing fluid, and its approximate position is calculated. After analyzing the limitations of traditional models, the monitoring model of the unsteady friction resistance is established by summarizing the existing models and fitting the weight function by the gradient descent method. In this paper, the relationship between the pressure-time curve and crack is studied. Then the pressure curve is optimized by OPTICS algorithm improved by the adjacency list, and conduct the unsupervised learning about the stress data. By using computers, the pressure data can be clustered automatically. The classification is rapid and more accurate than the manual classification, which improves the intelligence and accuracy of data analysis, and realizes more accurate and intuitive monitoring of fractures than before. At the same time, the relationship between the city and well sites is analyzed in this paper. Combined with WITS acquisition and industrial Internet technology, the real-time data of the well site is remotely transmitted to the headquarters, which makes it possible to monitor fracturing in the city far from the well site, so that the combination of city and industry is no longer restricted by geographical location. It is beneficial to give full play to the role of industry in promoting urban development and promote the sustainable development of the city. Surface monitoring instruments have been fully utilized by using this method. This method of remote monitoring of fracturing promotes the development of intelligent city and provides a method for builders to ensure the construction safe and to make abnormal early warning of on-site fracturing.

Protection of Sensitive Data in Industrial Internet Based on Three-Layer Local/Fog/Cloud Storage

Industrial Internet technology has developed rapidly, and the security of industrial data has received much attention. At present, industrial enterprises lack a safe and professional data security system. Thus, industries urgently need a complete and effective data protection scheme. This study develops a three-layer framework with local/fog/cloud storage for protecting sensitive industrial data and defines a threat model. For real-time sensitive industrial data, we use the improved local differential privacy algorithm M-RAPPOR to perturb sensitive information. We encode the desensitized data using Reed–Solomon (RS) encoding and then store them in local equipment to realize low cost, high efficiency, and intelligent data protection. For non-real-time sensitive industrial data, we adopt a cloud-fog collaborative storage scheme based on AES-RS encoding to invisibly provide multilayer protection. We adopt the optimal solution of distributed storage in local equipment and the cloud-fog collaborative storage scheme in fog nodes and cloud nodes to alleviate the storage pressure on local equipment and to improve security and recoverability. According to the defined threat model, we conduct a security analysis and prove that the proposed scheme can provide stronger data protection for sensitive data. Compared with traditional methods, this approach strengthens the protection of sensitive information and ensures real-time continuity of open data sharing. Finally, the feasibility of our scheme is validated through experimental evaluation.

Low-Power Distributed Data Flow Anomaly-Monitoring Technology for Industrial Internet of Things.

In recent years, the industrial use of the internet of things (IoT) has been constantly growing and is now widespread. Wireless sensor networks (WSNs) are a fundamental technology that has enabled such prevalent adoption of IoT in industry. WSNs can connect IoT sensors and monitor the working conditions of such sensors and of the overall environment, as well as detect unexpected system events in a timely and accurate manner. Monitoring large amounts of unstructured data generated by IoT devices and collected by the big-data analytics systems is a challenging task. Furthermore, detecting anomalies within the vast amount of data collected in real time by a centralized monitoring system is an even bigger challenge. In the context of the industrial use of the IoT, solutions for monitoring anomalies in distributed data flow need to be explored. In this paper, a low-power distributed data flow anomaly-monitoring model (LP-DDAM) is proposed to mitigate the communication overhead problem. As the data flow monitoring system is only interested in anomalies, which are rare, and the relationship among objects in terms of the size of their attribute values remains stable within any specific period of time, LP-DDAM integrates multiple objects as a complete set for processing, makes full use of the relationship among the objects, selects only one “representative” object for continuous monitoring, establishes certain constraints to ensure correctness, and reduces communication overheads by maintaining the overheads of constraints in exchange for a reduction in the number of monitored objects. Experiments on real data sets show that LP-DDAM can reduce communication overheads by approximately 70% when compared to an equivalent method that continuously monitors all objects under the same conditions.

EATDDS: Energy-aware middleware for wireless sensor and actuator networks

According to Object Management Group organization, Data Distribution Service (DDS) middleware is the leading technology for Industrial Internet of Things (IIoT). Therefore, using DDS-based middleware for Wireless Sensor/Actuator Networks (WSAN) will extremely ease the development and integration of WSAN applications into IIoT, which has an effective impact on improving the productivity and saving the cost. However, applying such technology over WSAN significantly affects the energy consumption. In this work, an energy-aware middleware for WSAN is developed based on DDS standard, which is called EATDDS. Furthermore, developing this middleware leads to a major enhancement into TOSSIM simulator; in which an Online Energy Model (OEM) is developed to make TOSSIM capable of developing and testing energy-aware protocols. The model is validated by comparing it against POWERTOSSIM. Our results show that EATDDS is efficient and can be accommodated with limited system resources.

Implementation of the intellectual technologies into the management system of the modern enterprise: theoretical basis

The issues of implementation of the intellectual technologies into the management system of the modern enterprise are investigated in this article. Intellectualization is viewed as the main background for this process. In the article authors examine different types and directions of the intellectualization process (intellectualization of the society, of the economy and of the labour activity). And we see that these directions have different results of their activity. The impact of the intellectualization of the society is viewed at the macro level and influence living conditions, societies’ development and so on. The impact of the economy intellectualization is viewed at the meso level, that means the economic and productive development of the scope of some branches. And the impact of the labour activity intellectualization is viewed at the micro level, when it influence certain branch, enterprise or even personnel of the company. In the article the factors of influence on the intellectualization process are viewed. Among them we can highlight next factors: labour, scientific, educational, managerial, socio-cultural, informational and communicational. They create the background for the effective realization of the intellectualization process.Also it is analyzed the concept of intellectual technologies. The authors adhere to the classification, in which three types of intellectual technologies are proposed. They are operational technologies, industrial internet technologies and informational technologies. The main advantages of the implementation of intellectual technologies into the business practice are overviewed.Thus, we can approve that the implementation of the intellectual technologies creates the new quality of the business activity, has the great impact on the state and its population.

A Performance Evaluation Concept for Production Systems in an SME Network

Industrial internet technologies offer new possibilities for information sharing, data integration platforms and communication interfaces in most SME manufacturing networks. To collaborate efficiently and maintain competitiveness, performance level of individual companies’ production system needs to be known and visible within the network. A current lack of harmonized evaluation methods demands to define a performance evaluation approach for production systems in a network. We developed a performance evaluation concept for production systems in an SME’s network that is based on identified key performance indicators and their real-time visualization. A case study demonstrated the relevance and feasibility of the proposed concept, which uses internet of things technologies.

A Collaboration-Oriented M2M Messaging Mechanism for the Collaborative Automation between Machines in Future Industrial Networks.

Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines. However, manufacturing IIoT applications have specificities that distinguish them from many other internet of things (IoT) scenarios in machine communications. By highlighting the key requirements and the major technical gaps of M2M in industrial applications, this article describes a collaboration-oriented M2M (CoM2M) messaging mechanism focusing on flexible connectivity and discovery, ubiquitous messaging, and semantic interoperability that are well suited for the production line-scale interoperability of manufacturing applications. The designs toward machine collaboration and data interoperability at both the communication and semantic level are presented. Then, the application scenarios of the presented methods are illustrated with a proof-of-concept implementation in the PicknPack food packaging line. Eventually, the advantages and some potential issues are discussed based on the PicknPack practice.

Collaborative service-component integration in cloud manufacturing

The Industrial Internet technologies are anticipated to enable agile manufacturing processes in response to the growing demand for personalised products/services with shorter lifecycles. This trend has resulted in a gradual transformation of traditional ‘tree-like’ and monolithic systems into complex networks of self-contained and autonomous ‘components’ (a.k.a., Internet of things) and ‘services’ (a.k.a., Internet of services). Cloud Manufacturing is an emerging concept that enables modularisation and service-orientation in the context of manufacturing, in which systematic orchestration, matching, and sharing of services and components are the key. This work develops a framework for dynamic integration of manufacturing services and components in a collaborative network of organisations. The framework dynamically recommends the best matching of services, components and organisations, as well as the best collaboration decisions in terms of sharing (shareable) services and/or components between organisations. The problem is formulated as a bi-objective mixed-integer program, and solved via an efficient socio-inspired tabu search. The objectives of the model are to increase service level and enhance collaboration through maximising service fulfilment and minimising unnecessary sharing of services/components, respectively. Numerical experiments are conducted to demonstrate the benefits of the developed framework for efficient and optimal (re)configuration of collaborative networked organisations, addressing the Industry 4.0 demand for agility through modularisation and service-orientation.

Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges

This paper provides an overview of the Industrial Internet with the emphasis on the architecture, enabling technologies, applications, and existing challenges. The Industrial Internet is enabled by recent rising sensing, communication, cloud computing, and big data analytic technologies, and has been receiving much attention in the industrial section due to its potential for smarter and more efficient industrial productions. With the merge of intelligent devices, intelligent systems, and intelligent decisioning with the latest information technologies, the Industrial Internet will enhance the productivity, reduce cost and wastes through the entire industrial economy. This paper starts by investigating the brief history of the Industrial Internet. We then present the 5C architecture that is widely adopted to characterize the Industrial Internet systems. Then, we investigate the enabling technologies of each layer that cover from industrial networking, industrial intelligent sensing, cloud computing, big data, smart control, and security management. This provides the foundations for those who are interested in understanding the essence and key enablers of the Industrial Internet. Moreover, we discuss the application domains that are gradually transformed by the Industrial Internet technologies, including energy, health care, manufacturing, public section, and transportation. Finally, we present the current technological challenges in developing Industrial Internet systems to illustrate open research questions that need to be addressed to fully realize the potential of future Industrial Internet systems.

Asian Industrial Internet Strategies: Building Blocks for E-Commerce

The advent of the Industrial Internet technologies in Asia has altered the dynamics of the manufacturing sector requirements for competitive success. In examining many of the fundamental building block concepts deemed the ’required knowledge’ of e-commerce, be it production-related or market-related information (Glazer, 1999), the paper focuses on the development of an Industrial-focused strategic Internet initiative. In an industry where the consulting dollars may be as high as the software dollars, the key concept of an industrial Internet strategy is in viewing information as an enterprise-wide, multi-tier communications asset (Hoske, 1999). The Industrial Internet reaches not only from the front office to the factory floor, but from the factory floor to an authorized lap top anywhere in the world. Although there is an abundance of importance being placed in recent literature on sales force automation (SFA) and customer relationship management (CRM) software, advances in factory supply chain management software and systems offerings may prove to be of a more highly critical value. For reemerging Asian industrialists, too much importance cannot be placed upon their propensity for assimilating vital industrial Internet technologies, and transforming the vicissitudes of e-commerce markets toward the fulfillment of their own competitive advantage.