Industrial internet of things for smart manufacturing applications using hierarchical trustful resource assignment

Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Duan Pingli ◽  
Bala Anand Muthu ◽  
Seifedine Nimer Kadry

BACKGROUND: The manufacturing industry undergoes a new age, with significant changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices, which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. OBJECTIVES: The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing Algorithm (TCA) based on Vickrey Clarke-Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. RESULTS: Finally, experimental findings demonstrate that when the IIoT equipment and gateways are valid, the utilities of each participant are improved. CONCLUSION: This is an easy and powerful method to guarantee that intelligent manufacturing components genuinely work for their purposes, which want to integrate each element into a system without interactions with each other.

2020 ◽  
Vol 1 (2) ◽  

Manufacturing is the way of transforming resources into products or goods which are required to cater to the needs of the society. It constitutes the foundation of any nation’s economic development. This paper reviews emerging technologies in manufacturing. These technologies include artificial intelligence, smart manufacturing, robotics, automation, 3D printing, nanotechnology, industrial Internet of things, and augmented reality. The use of these technologies will have a profound impact on the manufacturing industry. They have the potential to transform manufacturing as we know it. They should be at the core of any manufacturing upgrading effort.


2021 ◽  
Vol 14 (10) ◽  
pp. 1
Author(s):  
Jui-Lung Chen ◽  
Shih-Hsuan Yang

Recently, many manufacturing industries have been facing challenges such as rising material costs, small-volume and large-variety products, shortened production cycles, increased labor costs and longer after-sales service times, which is a very tough challenge for most small and medium-sized component manufacturing suppliers. In addition to the current hot topics in the manufacturing industry - Smart Manufacturing (Industry 4.0) and lean production management, if small and medium-sized enterprises are not able to adjust the pace of manufacturing timely and find a suitable production model, they will soon be overwhelmed by the torrent of the era of speed and accuracy. In the face of the dramatic changes in the industry structure, the company can deploy the global expansion of overseas customers in advance, and adjust to apply and implement a flexible manufacturing model system through the introduction of the Industrial Internet of Things and flexible manufacturing production management. In order to meet the market needs, the manufacturing industry is gradually oriented towards customized production and the rapid development of new products. To meet such stringent requirements, flexible manufacturing becomes one of the necessary ways for enterprises to consider their development models. Therefore, the efficiency and reliability of work can be improved through the Industrial Internet of Things that facilitates machine-to-machine communication, cloud-based big data and learning and imitations of smart robots. This study is an in-depth study of a company that is currently in the process of digital transformation, collecting relevant information and reviewing the analysis to find a suitable smart manufacturing solution for the company and to explore the impact of the COVID-19 pandemic on the strategic development of the company. The findings can provide a significant reference for homotypic companies in the development of their business strategies.


Author(s):  
Vishwas D. B. ◽  
Gowtham M. ◽  
Gururaj H. L. ◽  
Sam Goundar

In the era of mechanical digitalization, organizations are progressively putting resources into apparatuses and arrangements that permit their procedures, machines, workers, and even the products themselves to be incorporated into a solitary coordinated system for information assortment, information examination, the assessment of organization advancement, and execution improvement. This chapter presents a reference guide and review for propelling an Industry 4.0 venture from plan to execution, according to base on the economic and scientific policy of European parliament, applying increasingly effective creation forms, and accomplishing better profitability and economies of scale may likewise bring about expanded financial manageability. This chapter present the contextual analysis of a few Industry 4.0 applications. Authors give suggestions coordinating the progression of Industry 4.0. This section briefly portrays the advancement of IIoT 4.0. The change of ubiquitous computing through the internet of things has numerous difficulties related with it.


2018 ◽  
Vol 10 (10) ◽  
pp. 100 ◽  
Author(s):  
Thomas Usländer ◽  
Thomas Batz

The emerging Industrial Internet of Things (IIoT) will not only leverage new and potentially disruptive business models but will also change the way software applications will be analyzed and designed. Agility is a need in a systematic service engineering as well as a co-design of requirements and architectural artefacts. Functional and non-functional requirements of IT users (in smart manufacturing mostly from the disciplines of mechanical engineering and electrical engineering) need to be mapped to the capabilities and interaction patterns of emerging IIoT service platforms, not to forget the corresponding information models. The capabilities of such platforms are usually described, structured, and formalized by software architects and software engineers. However, their technical descriptions are far away from the thinking and the thematic terms of end-users. This complicates the transition from requirements analysis to system design, and hence the re-use of existing and the design of future platform capabilities. Current software engineering methodologies do not systematically cover these interlinked and two-sided aspects. The article describes in a comprehensive manner how to close this gap with the help of a service-oriented analysis and design methodology entitled SERVUS (also mentioned in ISO 19119 Annex D) and a corresponding Web-based Platform Engineering Information System (PEIS).


Author(s):  
Yu. MELESHKO

The article considers the problems of the development of the industrial Internet of things in the Republic of Belarus as one of the system-forming technologies in the industrial sector. Based on the analysis of terminological features of the Internet of things, the concept and main characteristics of the industrial Internet of things are revealed. The economic consequences of using this technology in industrial production are shown. The formation and development of the Internet market of things in the Republic of Belarus in the context of its infrastructure component, spheres of use, main producers and consumers is considered. The factors preventing the wider use of the Internet of things in the industry of Belarus, and the development prospects of the market under consideration are revealed.


2021 ◽  
Vol 16 (92) ◽  
pp. 72-81
Author(s):  
Emil A. Gumerov ◽  
◽  
Tamara V. Alekseeva ◽  

Cyber-physical systems are a means of effectively managing industrial applications of the Internet of things. Physical layer cyber-physical system implements the control devices of the industrial Internet of things and intelligent algorithms digital system level provide management and information security applications. Effective management and information security determine the success of the industrial Internet of things, so the research topic is relevant. The purpose of this article is to develop an optimal architecture of a cyber-physical system based on the principles of data processing at the place of their occurrence and the application of a control action at the place of the problem occurrence. The authors were faced with the task of exploring all the possibilities associated with the application of the proposed principles and developing an optimal application architecture for the industrial Internet of things. In the study proposed the concept of intelligent application of industrial Internet of things, which enables processing of continuously generated data in their source and provides application control action to the location of the problem. The proposed solution: a) increases the information security of the industrial application of the Internet of things (data is not transmitted over the network) and b) prevents an attack on the software of the Industrial application of the Internet of things. The solution can be used by developers of industrial IoT systems to effectively launch and implement projects


2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Zhenzhong Zhang ◽  
Wei Sun ◽  
Yanliang Yu

With the vigorous development of the Internet of Things, the Internet, cloud computing, and mobile terminals, edge computing has emerged as a new type of Internet of Things technology, which is one of the important components of the Industrial Internet of Things. In the face of large-scale data processing and calculations, traditional cloud computing is facing tremendous pressure, and the demand for new low-latency computing technologies is imminent. As a supplementary expansion of cloud computing technology, mobile edge computing will sink the computing power from the previous cloud to a network edge node. Through the mutual cooperation between computing nodes, the number of nodes that can be calculated is more, the types are more comprehensive, and the computing range is even greater. Broadly, it makes up for the shortcomings of cloud computing technology. Although edge computing technology has many advantages and has certain research and application results, how to allocate a large number of computing tasks and computing resources to computing nodes and how to schedule computing tasks at edge nodes are still challenges for edge computing. In view of the problems encountered by edge computing technology in resource allocation and task scheduling, this paper designs a dynamic task scheduling strategy for edge computing with delay-aware characteristics, which realizes the reasonable utilization of computing resources and is required for edge computing systems. This paper proposes a resource allocation scheme combined with the simulated annealing algorithm, which minimizes the overall performance loss of the system while keeping the system low delay. Finally, it is verified through experiments that the task scheduling and resource allocation methods proposed in this paper can significantly reduce the response delay of the application.


2020 ◽  
Vol 05 (01) ◽  
pp. 33-163 ◽  
Author(s):  
Yong Chen

Industrial information integration engineering (IIIE) is a set of foundational concepts and techniques that facilitate the industrial information integration process. In recent years, many applications of the integration between Internet of Things (IoT) and IIIE have become available, including industrial Internet of Things (IIoT), cyber-physical systems, smart grids, and smart manufacturing. In order to investigate the latest achievements of studies on IIIE, this paper reviews literatures from 2016 to 2019 in IEEEXplore and Web of Science. Altogether, 970 papers related to IIIE are grouped into 27 research categories and reviewed. The results present up-to-date development of IIIE and provide directions for future research on IIIE.


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