Industrial Internet of Things for smart manufacturing applications using hierarchical trustful resource assignment

2020 ◽  
Vol 160 ◽  
pp. 423-430
Author(s):  
Xiaoxiao Xu ◽  
Mingdan Han ◽  
Senthil Murugan Nagarajan ◽  
Prathik Anandhan
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.


Author(s):  
Rinki Sharma

Over the years, the industrial and manufacturing applications have become highly connected and automated. The incorporation of interconnected smart sensors, actuators, instruments, and other devices helps in establishing higher reliability and efficiency in the industrial and manufacturing process. This has given rise to the industrial internet of things (IIoT). Since IIoT components are scattered all over the network, real-time authenticity of the IIoT activities becomes essential. Blockchain technology is being considered by the researchers as the decentralized architecture to securely process the IIoT transactions. However, there are challenges involved in effective implementation of blockchain in IIoT. This chapter presents the importance of blockchain in IIoT paradigm, its role in different IIoT applications, challenges involved, possible solutions to overcome the challenges and open research issues.


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).


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.


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.


Author(s):  
Shreyas S

Abstract: Smart Manufacturing systems are regarded as the fourth revolution in the manufacturing industry, which is shaped by widespread deployment of sensors and Internet of Things. The present work constitutes of ‘Development of Industrial Internet of Things (IIoT) Dashboard for ‘Overall Equipment Effectiveness’ (OEE) Monitoring of CNC Machine Tools’ for a legacy CNC machine which is converted to smart machine. Data fetched from the CNC controllers through OPCUA is sent to the connected cloud database which will be imported into PowerBI desktop and the data has been classified and processed according to the requirement to develop a data modelling architecture of OEE, the Working status of the machine is visualized by Creating Monitoring and Performance charts and graphs of different design in Microsoft PowerBI Desktop. The Advanced visualizations constitutes od various features along with different analysing capabilities that results is creating reports which enumerates the state of OEE as a Key Performance Indicator (KPI). As Microsoft Power BI pertains a set of pre-established steps for data processing, the situation designated may constitute a limitation to automatic data refresh, leading to a do-over to verify, the specific interval of time, the conformity of data so they can be imported into the system. Keywords: Industrial Internet of Things (IIoT), Open Platform Communications United Architecture (OPCUA), Computer Numerical Control (CNC), Overall Equipment Effectiveness (OEE), Key Performance Indicator (KPI).


Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 368 ◽  
Author(s):  
Roberto Contreras-Masse ◽  
Alberto Ochoa-Zezzatti ◽  
Vicente García ◽  
Luis Pérez-Dominguez ◽  
Mayra Elizondo-Cortés

Industry 4.0 is having a great impact in all smart efforts. This is not a single product but is composed of several technologies, one of them being Industrial Internet of Things (IIoT). Currently, there are very varied implementation options offered by several companies, and this imposes a new challenge to companies that want to implement IIoT in their processes. This challenge suggests using multi-criteria analysis to make a repeatable and justified decision, requiring a set of alternatives and criteria. This paper proposes a new methodology and comprehensive criteria to help organizations to take an educated decision by applying multi-criteria analysis. Here, we suggest a new original use of PROMETHEE-II with a full example from weight calculation up to IIoT platform selection, showing this methodology as an effective study for other organizations interested in selecting an IIoT platform. The criteria proposed stands out from previous work by including not only technical aspects, but economic and social criteria, providing a full view of the problem analyzed. A case of study was used to prove this proposed methodology and finds the minimum subset to reach the best possible ranking.


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.


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