INTELLIGENT OPTIMIZATION SYSTEM FORMULATED ON INDUSTRIAL INTERNET PLATFORM

2021 ◽  
Vol 71 (10) ◽  
pp. 75-79
Author(s):  
Sabuhi Farasat Rahimli ◽  

The opinion of "Industrial Internet" was first suggested by General Electric. As a modern infrastructure of the 4 -th industrial revolution, Industrial Internet has become a substantial mechanism to actualiza digital revision of industrial economy. The Industrial Internet platform is a system formulated on huge data gathering, accumulation and analysis, which is based to the necessity of digitalization, networking and philosophizing of manufacturing industry. In order to settle the problems of actual rearward industrial data, improve the capacity of data acquisition and deal with the industrial interconnection platform, the industrial intelligent optimization system generates the product services needed by industrial enterprises and realizes the object of industrial optimization. Key words: Industrial Internet; industrial intelligence; industrial mechanism

2020 ◽  
Vol 26 (9) ◽  
pp. 84-92
Author(s):  
Lo Thi Hong Van ◽  
◽  
L. Guzikova ◽  

The purpose of the study is to identify the challenges, prospects and ways for the development of the manufacturing industry in Vietnam in the context of Industry 4.0, after COVID-19. The article examines the development of the manufacturing industry in the context of Industry 4.0. The research methodology includes comparative analysis, elements of positive and normative analysis. The study is based on statistical information available within the period of writing the article (till October 1, 2020). The data of Vietnamese and international research organizations and statistics bodies, in particular, the websites of World Bank and General Statistics Office of were used. The leading role of the manufacturing industry in achieving sustainable economic development in developing countries, including Vietnam, was determined. Based on an assessment of the levels of development of the manufacturing industry in Vietnam from 2011 to 2019 and the state of production of the main manufacturing industries under the influence of the coronavirus pandemic in 2020, urgent problems of the development of the manufacturing industry in the context of Industry 4.0 in Vietnam were identified. The coronavirus pandemic, on the one hand, is seen as the reason for the slowdown in production growth in the manufacturing industry, and on the other hand, as a condition for accelerating digital transformation in industrial manufacturing enterprises. The article identifies the main challenges and prospects for the development of the manufacturing industry in Vietnam in the fourth industrial revolution. The human resource challenge for the development of manufacturing in the context of the fourth industrial revolution was identified in some specific industries such as textiles, food processing, machinery and equipment manufacturing by analyzing the Report of 2019 about Industry 4.0 Readiness of Vietnam’s industrial enterprises. The main priority areas for improving the production of the manufacturing industry in Vietnam to achieve sustainable industrial development are presented. The results of the work can be used in the development of policies for the development of the manufacturing industry not only in Vietnam, but also in other developing countries


2021 ◽  
Vol 5 (2) ◽  
pp. 49-58
Author(s):  
Kremena Marinova-Kostova ◽  
Ivaylo Kostov

Introduction. Industry 4.0 is a concept that is considered a new phase in the Industrial Revolution, closely related to the application of information technologies and the digital transformation of manufacturing. The main purpose is to be created a more holistic and more connected ecosystem, focused on supply chain management in industrial companies. Implementation of solutions in Industry 4.0 is mostly related to the concept of the Internet of Things (IoT). Mass deployment of this type of technology in industrial enterprises is the basis of the so-called Industrial Internet of Things (IIoT). Achieving interoperability in the IIoT requires the combination of two technologies: the Internet of Things and the Internet of People. Aim and tasks. This article describes the implementation of the concept of the Internet of Things in industrial enterprises, as a key technology factor for developing Industry 4.0. Results. A brief overview of the evolution of industrial production - from the beginning of the Industrial Revolution to the emergence of Industry 4.0 is made. The main principles for implementing Industry 4.0 solutions ensure that the entire production process is computerized. Industry 4.0 solutions are mostly associated with the concept of the Internet of Things (IoT) whose definition and essence are obtained in this article. Based on the various concepts of the IoT are presented solutions that can be used in the industry, namely: in consumer devices in technology used in public organizations in infrastructure applications in industrial applications, also called the Industrial Internet of Things (IIoT). Therefore, we can say that there is a significant potential for improving production processes as regards: optimization of operations, forecasting equipment support, inventory optimization, improving workers' security, shipping chain optimization, etc. Conclusions. The application of the Internet of Things in enterprises is an important and decisive step in the process of their digital transformation and transition to Industry 4.0. The interaction between humans and machines, carried out through Internet technologies, leads to the emergence of the Internet of Everything, which will be a basic concept in industrial production in the coming years. However, the role of man in the production process should not be completely eliminated, but solutions should be sought that support and intellectualize his work.


Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 274
Author(s):  
Keqin Dou ◽  
Jun Li ◽  
Yong Zhou

Accelerating the innovation and development of the Industrial Internet Platform is inevitably necessary for the integration of new-generation information technology and the manufacturing industry. It is also the key point for promoting the construction of manufacturing power and network power. In this paper, based on the comprehensive analysis of the relevant problems of China’s Industrial Internet Platform development monitoring, the development index of the Industrial Internet Platform is designed. Taking a typical domestic Industrial Internet Platform as an example, the development index of the Industrial Internet Platform in 2018, 2019, and 2020 are comprehensively calculated in this paper. The results show that China’s Industrial Internet Platform is rapidly growing in many aspects, such as industrial equipment cloud and industrial APP. There is a large space for improving the industrial knowledge accumulation reuse and the application promotion of small/medium-sized enterprises. The results in this paper can provide scientific suggestions and practical references for the government, enterprises, scientific research institutions, which is of great significance in promoting the healthiness and sustainability of the Industrial Internet Platform.


2020 ◽  
Author(s):  
Karthik Muthineni

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.


2020 ◽  
Vol 6 (3) ◽  
pp. 599-603
Author(s):  
Michael Friebe

AbstractThe effectiveness, efficiency, availability, agility, and equality of global healthcare systems are in question. The COVID-19 pandemic have further highlighted some of these issues and also shown that healthcare provision is in many parts of the world paternalistic, nimble, and often governed too extensively by revenue and profit motivations. The 4th industrial revolution - the machine learning age - with data gathering, analysis, optimisation, and delivery changes has not yet reached Healthcare / Health provision. We are still treating patients when they are sick rather then to use advanced sensors, data analytics, machine learning, genetic information, and other exponential technologies to prevent people from becoming patients or to help and support a clinicians decision. We are trying to optimise and improve traditional medicine (incremental innovation) rather than to use technologies to find new medical and clinical approaches (disruptive innovation). Education of future stakeholders from the clinical and from the technology side has not been updated to Health 4.0 demands and the needed 21st century skills. This paper presents a novel proposal for a university and innovation lab based interdisciplinary Master education of HealthTEC innovation designers.


2021 ◽  
pp. 204388692098158
Author(s):  
Dipankar Chakrabarti ◽  
Rohit Kumar ◽  
Soumya Sarkar ◽  
Arindam Mukherjee

Industrial Internet of Things emerged as one of the major technologies enabling Industry 4.0 for industries. Multiple start-ups started working in the Industrial Internet of Things field to support this new industrial revolution. Distronix, one such Industrial Internet of Things start-up of India, started operations in 2014, when companies were not even aware of Industrial Internet of Things. Distronix started executing fixed-fee projects for implementation of Industrial Internet of Things. They also started manufacturing sensors to support large customers end-to-end in their Industry 4.0 journey. With the advent of public cloud, companies started demanding pay-per-use model for the solution Distronix provided. This posed a major challenge to Distronix as they had developed technology skills focusing fixed-fee customized project delivery for their clients. The situation demanded that they change their business model from individual project delivery to creation of product sand-box with pre-registered sensors and pre-defined visualization layer to support use cases for Industrial Internet of Things implementation in multiple industry sectors. It forced Rohit Sarkar, the 26 years old entrepreneur and owner of Distronix, to upgrade capabilities of his employees and transform the business model to support pay-per-use economy popularized by public cloud providers. The case discusses the challenges Rohit faced to revamp their business model in such an emerging technology field, like, to develop new skills of the technical people to support such novel initiative, reorienting sales people towards pay as use model, developing new concept of plug and play modular product, devising innovative pricing, better alliance strategy and finding out a super early adopter.


2021 ◽  
Vol 11 (6) ◽  
pp. 2729
Author(s):  
Chien-Hua Lin ◽  
Ming-Che Lu ◽  
Su-Fen Yang ◽  
Ming-Yung Lee

Automation in the service industry is emerging as a new wave of industrial revolution. Standardization and consistency of service quality is an important part of the automation process. The quality control methods widely used in the manufacturing industry can provide service quality measurement and service process monitoring. In particular, the control chart as an online monitoring technique can be used to quickly detect whether a service process is out of control. However, the control of the service process is more difficult than that of the manufacturing process because the variability of the service process comes from widespread and complex factors. First of all, the distribution of the service process is usually non-normal or unknown. Moreover, the skewness of the process distribution can be time-varying, even if the process is in control. In this study, a Bayesian procedure is applied to construct a Phase II exponential weighted moving average (EWMA) control chart for monitoring the variance of a distribution-free process. We explore the sampling properties of the new monitoring statistic, which is suitable for monitoring the time-varying process distribution. The average run lengths (ARLs) of the proposed Bayesian EWMA variance chart are calculated, and they show that the chart performs well. The simulation studies for a normal process, exponential process, and the mixed process of normal and exponential distribution prove that our chart can quickly detect any shift of a process variance. Finally, a numerical example of bank service time is used to illustrate the application of the proposed Bayesian EWMA variance chart and confirm the performance of the process control.


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