Incorporation of Artificial Intelligence and Smart Factories in Domestic Manufacturing Industries

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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Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots

Social Sciences ◽

10.3390/socsci8050143 ◽

2019 ◽

Vol 8 (5) ◽

pp. 143 ◽

Cited By ~ 13

Author(s):

Rabab Benotsmane ◽

György Kovács ◽

László Dudás

Keyword(s):

Artificial Intelligence ◽

Industry 4.0 ◽

Optimal Operation ◽

Added Value ◽

Smart Factory ◽

Motion Path ◽

Robot Arm ◽

Quantitative Research Methods ◽

Smart Factories

Smart Factory is a complex system that integrates the main elements of the Industry 4.0 concept (e.g., autonomous robots, Internet of Things, and Big data). In Smart Factories intelligent robots, tools, and smart workpieces communicate and collaborate with each other continuously, which results in self-organizing and self-optimizing production. The significance of Smart Factories is to make production more competitive, efficient, flexible and sustainable. The purpose of the study is not only the introduction of the concept and operation of the Smart Factories, but at the same time to show the application of Simulation and Artificial Intelligence (AI) methods in practice. The significance of the study is that the economic and social operational requirements and impacts of Smart Factories are summarized and the characteristics of the traditional factory and the Smart Factory are compared. The most significant added value of the research is that a real case study is introduced for Simulation of the operation of two collaborating robots applying AI. Quantitative research methods are used, such as numerical and graphical modeling and Simulation, 3D design, furthermore executing Tabu Search in the space of trajectories, but in some aspects the work included fundamental methods, like suggesting an original whip-lashing analog for designing robot trajectories. The conclusion of the case study is that—due to using Simulation and AI methods—the motion path of the robot arm is improved, resulting in more than five percent time-savings, which leads to a significant improvement in productivity. It can be concluded that the establishment of Smart Factories will be essential in the future and the application of Simulation and AI methods for collaborating robots are needed for efficient and optimal operation of production processes.

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La industria 4.0 en el mantenimiento industrial

Revista de Ingeniería Industrial ◽

10.35429/jie.2019.7.3.17.24 ◽

2019 ◽

pp. 17-24

Author(s):

Manuel Meraz-Mendez ◽

Claudia Lerma-Hernández ◽

Guadalupe Corral-Ramírez

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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Recent Advances of Artificial Intelligence in Manufacturing Industrial Sectors: A Review

International Journal of Precision Engineering and Manufacturing ◽

10.1007/s12541-021-00600-3 ◽

2021 ◽

Author(s):

Sung Wook Kim ◽

Jun Ho Kong ◽

Sang Won Lee ◽

Seungchul Lee

Keyword(s):

Artificial Intelligence ◽

Public Interest ◽

Industry 4.0 ◽

Manufacturing Industries ◽

Human Beings ◽

Precision Engineering ◽

Daily Lives ◽

Industrial Sectors ◽

Recent Advances ◽

Traditional Manufacturing

AbstractThe recent advances in artificial intelligence have already begun to penetrate our daily lives. Even though the development is still in its infancy, it has been shown that it can outperform human beings even in terms of intelligence (e.g., AlphaGo by DeepMind), implying a massive potential for its broader application in various industrial sectors. In particular, the growing public interest in industry 4.0, which focuses on revolutionizing the traditional manufacturing scene, has stimulated a deeper investigation of its possible applications in the related industries. Since it has several limitations that hinder its direct usage, research on the convergence of artificial intelligence with other engineering fields, including precision engineering and manufacturing, is ongoing. This overview looks to summarize some of the important achievements made using artificial intelligence in some of the most influential and lucrative manufacturing industries in hopes of transforming the manufacturing sites.

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Opportunities and directions for digital economy development in Russia and blocking factors of its development

Actual Problems of Russian Law ◽

10.17803/1994-1471.2019.100.3.045-066 ◽

2019 ◽

pp. 45-66

Author(s):

A. A. Petrov

Keyword(s):

Artificial Intelligence ◽

Manufacturing Industry ◽

Industrial Revolution ◽

Digital Technologies ◽

Digital Economy ◽

Cyberphysical Systems ◽

World Community ◽

The Usa ◽

Blocking Factors ◽

Smart Factories

The paper shows the importance of the 4th Industrial Revolution and its product — the digital economy — in the development of mankind, its dual impact on the welfare and labor market of a specific people, the country, as well as the world community as a whole. The author examines the consequences of introduction of artificial intelligence, cyberphysical systems in production processes. Also, the paper analyzes the German program “Industry 4.0” shifting a German manufacturing industry on a digital basis through the use of digital technologies and setting up smart factories. The author summarizes the digital programs of the USA, Great Britain, Japan. The possibilities and problems of development and blocking of digital economy in Russia are shown. The author describes such basic components of the digital economy as blockchain, cyberphysical systems, digitalization, big data, artificial intelligence. He considers adverse consequences of the digital economy, factors blocking its development, as well as possible ways of their neutralization and elimination.

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Recent Development of Automation in Vehicle Manufacturing Industries

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.f1083.0486s419 ◽

2019 ◽

Vol 8 (6S4) ◽

pp. 410-413 ◽

Cited By ~ 1

Keyword(s):

Artificial Intelligence ◽

Manufacturing Industry ◽

Motor Vehicle ◽

Manufacturing Industries ◽

Research Trend ◽

Future Research ◽

Automation System ◽

Safety Feature ◽

Final Assembly ◽

Wheel Loading

This paper presents the application of automation in different areas of motor vehicle manufacturing industry such as; robotic wheel loading, defect tracking in process, automated machine adjustment and restructuring, decision making, multi arm operation, final assembly and most important safety feature. In this work explore the present automation application and also find out the better way to implement in future to minimize the human efforts and time. These technologies based on the automation and artificial intelligence that will helps to make the process more efficient, stable and flexible. Moreover, aspects of changeability and adaptiveness of automation system have to be considered. The aim of this study to identified the opportunities and scope for future research trend in the field of automobile industries.

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Automation 4.0

Advances in Computational Intelligence and Robotics - Driving Innovation and Productivity Through Sustainable Automation ◽

10.4018/978-1-7998-5879-9.ch002 ◽

2021 ◽

pp. 29-49

Author(s):

Craig Eric Seidelson

Keyword(s):

Artificial Intelligence ◽

Industry 4.0 ◽

Industrial Robots ◽

The Other ◽

Intelligent Machines ◽

Level Of Automation ◽

Other Hand ◽

The World ◽

The One ◽

Smart Factories

Factories have employed automation for nearly 100 years. With the launch of Industry 4.0 in 2011, operations have expanded their use of robots on an unprecedented scale. As of 2017, there were roughly 2 million industrial robots in use globally. By 2030, it's estimated that 20 million manufacturing jobs around the world could be replaced by robots. Yet, substantial hurdles remain before predicted level of automation can be realized. On the one hand, smart factories are almost exclusively multibillion-dollar enterprises. Their costs are simply too high for most manufacturers. On the other hand, intelligent machines are limited in what they can do because so many of the engineering tasks required to support them are still being done by people. Widespread use of automation requires expanding the use of artificial intelligence to manage data, create drawings, evaluate designs, and program machines.

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Talk to me

Mechanical Engineering ◽

10.1115/1.2016-nov-1 ◽

2016 ◽

Vol 138 (11) ◽

pp. 32-37

Author(s):

Alan S. Brown

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Operating System ◽

Natural Language ◽

Product Design ◽

Voice Recognition ◽

Radio Stations ◽

Learning Software ◽

Smart Cars ◽

Smart Factories

This article explores the collaboration of artificial intelligence and voice recognition in day-to-day living. As everyday products grow smarter and more capable, voice promises to simplify how we communicate with smart cars, smart homes, smart offices, and smart factories. Instead of mastering one new app after another, voice could make it simpler to command them all. Incorporating voice interfaces is expected to transform product design. Voice recognition is also expanding its beachhead in physical products. Many new cars use voice to place calls, set the GPS, write and receive texts, change radio stations, and adjust the temperature. The machine learning software behind voice recognition analyzes data from actual interactions to improve its performance. It is expected that by coupling natural language requests to the deepest workings of the operating system, we may soon have new types of products that will give anyone access to features that only a professional could manipulate.

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