IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization driver under industry 4.0 model

The advance of digitalization in industry is making possible that connected products and processes help people, industrial plants and equipment to be more productive and efficient, and the results for operative processes should impact throughout the economy and the environment.Connected products and processes generate data that is being seen as a key source of competitive advantage, and the management and processing of that data is generating new challenges in the industrial environment.The article to be presented looks into the framework of the adoption of Artificial Intelligence and Machine Learning and its integration with IIoT or IoT under industry 4.0, or smart manufacturing framework. This work is focused on the discussion around Artificial Intelligence/Machine Learning and IIoT/IoT as driver for Industrial Process optimization.The paper explore some related articles that were find relevant to start the discussion, and includes a bibliometric analysis of the key topics around Artificial Intelligence/Machine Learning as a value added solution for process optimization under Industry 4.0 or Smart Manufacturing paradigm.The main findings are related to the importance that the subject has acquired since 2013 in terms of published articles, and the complexity of the approach of the issue proposed by this work in the industrial environment.

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Industry 4.0 and Developing Countries: Innovation Perspective of Ethiopia, India and Bangladesh

International Journal for Modern Trends in Science and Technology - RTT2020 ◽

10.46501/ijmtst060615 ◽

2020 ◽

Vol 6 (6) ◽

pp. 62-70

Author(s):

Amrut Rao ◽

Ravindra Pathak ◽

Ashraf Mahmud Rayed

Keyword(s):

Developing Countries ◽

Industry 4.0 ◽

Global Economy ◽

Information Technologies ◽

Technological Development ◽

Value Added ◽

Developed Countries ◽

Intelligent Manufacturing ◽

Smart Manufacturing ◽

Efficient Production

Ethiopia, India and Bangladesh are raising economic power, but have not yet integrated very much with the global economy and still have not achieved their potential in context of technology, globalization, and international competitiveness like developed countries. These countries have much strength, but at the same time , are facing many challenges in the increasingly competitive and fast changing global economy. The main key strengths of these courtiers are their large domestic market, young and growing population, a strong private sector with experience in market institutions, and a well developed legal and financial system. In today’s environment of global competition, technological development and innovation; companies, especially manufacturing, are forced to reconfigure their manufacturing and management processes. Industry 4.0 and intelligent manufacturing are part of a transformation, in which manufacturing and information technologies have been integrated to create innovative systems of manufacturing, management and ways of doing business. This system allows optimizing manufacturing, to achieve greater flexibility, efficient production processes and generate a value added proposal for their customers, as well as to provide a timely response to their market needs. The objective of this work is to explore the Industry 4.0, smart manufacturing, environment requirement and relation of innovation in perspective of developing countries.

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The next step for Artificial Intelligence in a globally connected economy

SHS Web of Conferences ◽

10.1051/shsconf/202112904001 ◽

2021 ◽

Vol 129 ◽

pp. 04001

Author(s):

Dumitru Alexandru Bodislav ◽

Florina Bran ◽

Carol Cristina Gombos ◽

Amza Mair

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Human Factor ◽

Value Added ◽

Point Of View ◽

Business Analytics ◽

Economic Point ◽

Technological Breakthrough ◽

Big Picture ◽

The Difference

Research background: This research paper represents an overview of what artificial intelligence is, what are its roots, and what is the next big thing regarding the domain. In this paper we try to highlight how the domain is growing and what is the difference between the ideology, the business factor and the human factor. We try to create a big picture on the entire phenomenon by creating a parallel between machine learning, artificial intelligence and the influence of technological breakthrough from a hardware perspective. Purpose of the article: The paper is built as a tool in understanding technology, globalization and the pathway to success and scientific glory for what can be seen as the industry of artificial intelligence. The tools presented in the research have the purpose to create an easier path to how we can develop this domain by accelerating theoretical processing and business analytics that come together to form the next level of machine learning/artificial intelligence; research and development, everything being filtered from an economic point of view. Methods: The used research method is based on fundamental analysis of the artificial intelligence domain and its purpose in the complexity of globalization and economic development. Findings & Value added: The paper tries to offer a tool for building a better understanding of the next decade in the domain of artificial intelligence.

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Artificial Intelligence as an Emerging Technology in Global Trade

10.4018/978-1-7998-8497-2.ch007 ◽

2022 ◽

pp. 98-117

Author(s):

Seema Garg ◽

Navita Mahajan ◽

Jayanta Ghosh

Keyword(s):

Artificial Intelligence ◽

International Trade ◽

Industry 4.0 ◽

Smart Manufacturing ◽

Global Trade ◽

Digital Platforms ◽

New Horizons ◽

Demand Prediction ◽

Immense Potential ◽

Chain Links

With Industry 4.0 and now 5.0 technologies, the entire globe is embracing these changes. Artificial intelligence-powered systems have immense potential to eliminate international geographical barriers and prove to influence global trade worldwide. The present study highlights how AI increases productivity, economic development, and provides international trade with new horizons. The global value chains, prediction of future trends like changes in consumer demand, risk management, supply chain links are some of the key applications of AI in the sector. AI empowers international trade negotiations to analyze economic trajectories of negotiating partners, adjustments of trade barriers at different rates and scenarios. The chapter will cover the support of AI to access global trade data, its response to diverse challenges, international expansions through digital platforms, support in translations, mechanism of demand prediction, automation of administration with increased efficiency and utility, smart manufacturing, barriers, and influences.

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INDUSTRY 4.0: A Comprehensive Review of Artificial Intelligence, Machine Learning, Big Data and IoT in Psychiatric Health Care

Lecture Notes in Networks and Systems - Proceedings of 3rd International Conference on Computing Informatics and Networks ◽

10.1007/978-981-15-9712-1_42 ◽

2021 ◽

pp. 495-504

Author(s):

Anoushka Panwar ◽

Neha Malhotra ◽

Dheeraj Malhotra

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Health Care ◽

Big Data ◽

Industry 4.0 ◽

Comprehensive Review

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The Development of Pottery Products from Nong Suea Clay

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.608.346 ◽

2014 ◽

Vol 608 ◽

pp. 346-350 ◽

Cited By ~ 1

Author(s):

Sekporn Tansripraparsiri

Keyword(s):

Research And Development ◽

Industrial Process ◽

Value Added ◽

Development Project ◽

A Value ◽

Different Types ◽

Two Temperatures ◽

Higher Temperature ◽

White Clay

The development of pottery products was emphasized as the research and development project. The main ingredient was Nong Suea clay, Pathumthani province. Normally, Nong Suea clay was used for land-fill industries. However, the way to use Nong Suea clay as materials for pottery products could be a value added technology. In addition, the pottery products created from Nong Suea clay were used as the decorative materials. From the line blend method, six mixing ingredients were focused. The researcher found that the suitable mixing ingredient was the third formula that contained Nong Suea clay (80%) and Ranong white clay (20%). This formula was processed into five types of pottery products. Two temperatures were monitored for firing. First, the temperature at 850 °C was used for three different types of pots. This product was normally shaped by hand with a throwing wheel that led to the industrial process level. Second, the temperature at 1,200 °C was used for two different types of vases. The product decorations of these groups were applied by the flowing glaze technique which was suitable for long-term research and development. The craftmen in should be highly skilled, tool uses, and higher temperature capacity of kiln.

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Tecnologías de Mantenimiento industrial en la industria 4.0

Revista de Ingeniería Tecnológica ◽

10.35429/jten.2019.9.3.20.24 ◽

2019 ◽

pp. 20-24

Author(s):

Manuel Meraz-Méndez ◽

Claudia Lerma-Hernández

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Teaching Practices ◽

Industry 4.0 ◽

Digital Technologies ◽

Industrial Maintenance ◽

Technological University ◽

Engineering Career ◽

Smart Factories ◽

Technical Area

Industry 4.0 is the incorporation of digital technologies in factories such as: artificial intelligence, machine learning, 3D printing, drones, robotics, IOT, big data, virtual reality, automation, among others, which aim to digitalize processes productive in the factories, these are also called smart factories. The objective of this article is to identify the technologies applicable to industrial maintenance in Industry 4.0, the final result of this research determine the teaching practices that must be carried out in the Industrial Maintenance Engineering career at the Technological University of Chihuahua, and how the students must be prepared with the competences and skills necessary to face this challenge, at the same time the new teaching practices and strategies that a teacher in the technical area of Industrial Maintenance must apply in laboratory practices with a focus on Industry 4.0.

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New Business and Operating Models. Optimization of a Blast Furnace in the Steel Industry. Machine Learning as a Process Optimization

10.20944/preprints202111.0416.v1 ◽

2021 ◽

Author(s):

Andrés Redchuk ◽

Federico Walas Mateo

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Blast Furnace ◽

Conceptual Framework ◽

Manufacturing Process ◽

Smart Manufacturing ◽

Key Factors ◽

Steel Company ◽

Steel Manufacturing ◽

New Business

The article takes the case of the adoption of machine learning in a steel manufacturing process through a platform provided by a novel Canadian startup, Canvass Analytics. This way the steel company could optimize the process in a blast furnace. The content of the paper includes a conceptual framework on key factors around steel manufacturing and machine learning. Method: The article takes the case of the adoption of machine learning in a steel manufacturing process through a platform provided by a novel Canadian startup, Canvass Analytics. This way the steel company could optimize the process in a blast furnace. The content of the paper includes a conceptual framework on key factors around steel manufacturing and machine learning. Results: This case is relevant for the authors by the way the business model proposed by the startup attempts to democratize Artificial Intelligence and Machine Learning in industrial environments. This way the startup delivers value to facilitate traditional industries to obtain better operational results, and contribute to a better use of resources. Conclusion: This work is focused on opportunities that arise around Artificial Intelligence as a driver for new business and operating models. Besides the paper looks into the framework of the adoption of Artificial Intelligence and Machine Learning in a traditional industrial environment towards a smart manufacturing approach.

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