scholarly journals Big Data and Artificial Intelligence in the Development of Industry 4.0; A Bibliometric Analysis

2021 ◽  
Vol 1154 (1) ◽  
pp. 012008
Author(s):  
E González-Sarmiento ◽  
J Roa-Perez ◽  
L Ortiz-Ospino
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Bibliometric Analysis ◽  
Industry 4.0

Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0

2022 ◽  
pp. 406-428
Author(s):  
Lejla Banjanović-Mehmedović ◽  
Fahrudin Mehmedović
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Manufacturing Systems ◽  
System Modeling ◽  
Big Data Analytics ◽  
Intelligent Manufacturing ◽  
Intelligent Manufacturing Systems ◽  
Intelligent Decision Making

Intelligent manufacturing plays an important role in Industry 4.0. Key technologies such as artificial intelligence (AI), big data analytics (BDA), the internet of things (IoT), cyber-physical systems (CPSs), and cloud computing enable intelligent manufacturing systems (IMS). Artificial intelligence (AI) plays an essential role in IMS by providing typical features such as learning, reasoning, acting, modeling, intelligent interconnecting, and intelligent decision making. Artificial intelligence's impact on manufacturing is involved in Industry 4.0 through big data analytics, predictive maintenance, data-driven system modeling, control and optimization, human-robot collaboration, and smart machine communication. The recent advances in machine and deep learning algorithms combined with powerful computational hardware have opened new possibilities for technological progress in manufacturing, which led to improving and optimizing any business model.

Smart Room Menggunakan Internet Of Things Untuk Efisiensi Biaya dan Keamanan Ruangan

2019 ◽  
Author(s):  
Robby Yuli Endra
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Smart Room

Revolus industry 4.0 tidak dapat dielakan, oleh sebab itu kitaharus mempersiapkan diri semaksimal mungkin. Beberapateknologi mutakhir di IR 4.0 contohnya Artificial Intelligence(kecerdasaan buatan), Big data dan Internet of Things. Buku Smart Room dengan menggunakan Internet of Things (IoT)buku yang membahas konsep otomatisasi ruangan denganmenggunakan sensor-sensor serta mikrokontroler Arduino sertapenggunaan Internet. Buku ini merupakan buku referensi hasildari penelitian penulis. Pada buku ini juga dijelaskan tahap-tahappembuatan prototype Smart Room dari tools-tools yangdigunakan, pengkodingan serta konsep dan arsitektur SmartRoom.Diharapkan buku referensi ini dapat bermanfaat di duniaakademis, sebagai bahan referensi ataupun bahan diskusi untukbelajar dan mengembang konsep Internet of Things (IoT) yanglebih luas lagi.Ucapan terima kasih tak lupa kami sampaikan kepada semua pihakyang telah membantu dalam penerbitan buku referensi ini. Tidakada gading yang tak retak, buku ini jauh dari kata sempurna olehsebab kami menerima masukan untuk penyempurnaan buku ini.

Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0

2020 ◽  
pp. 31-52 ◽  
Author(s):  
Lejla Banjanović-Mehmedović ◽  
Fahrudin Mehmedović
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Manufacturing Systems ◽  
System Modeling ◽  
Big Data Analytics ◽  
Intelligent Manufacturing ◽  
Intelligent Manufacturing Systems ◽  
Intelligent Decision Making

Intelligent manufacturing plays an important role in Industry 4.0. Key technologies such as artificial intelligence (AI), big data analytics (BDA), the internet of things (IoT), cyber-physical systems (CPSs), and cloud computing enable intelligent manufacturing systems (IMS). Artificial intelligence (AI) plays an essential role in IMS by providing typical features such as learning, reasoning, acting, modeling, intelligent interconnecting, and intelligent decision making. Artificial intelligence's impact on manufacturing is involved in Industry 4.0 through big data analytics, predictive maintenance, data-driven system modeling, control and optimization, human-robot collaboration, and smart machine communication. The recent advances in machine and deep learning algorithms combined with powerful computational hardware have opened new possibilities for technological progress in manufacturing, which led to improving and optimizing any business model.

scholarly journals Corporate governance for trillion dollar opportunities

2017 ◽  
Vol 13 (3) ◽  
pp. 19-27 ◽  
Author(s):  
Hugh Grove ◽  
Maclyn Clouse
Keyword(s):  
Artificial Intelligence ◽  
Corporate Governance ◽  
Big Data ◽  
Boards Of Directors ◽  
Industry 4.0 ◽  
The Internet ◽  
Technological Changes ◽  
Corporate Executives ◽  
Challenges And Opportunities ◽  
The Internet Of Things

Boards of Directors will have to play a key role in the technological survival and development of companies by asking corporate executives about their plans and strategies for these emerging technological changes and challenges. Key challenges and opportunities discussed in this paper, with corresponding corporate governance implications, included Big Data, Artificial Intelligence (AI) with Industry 4.0, AI with the Internet of Things (IoT), Deep Learning, and Neural Networks. Survival should not be the goal, but it may be the necessary first step for today’s companies. Potential winners seizing these trillion dollar opportunities will be company executives and Boards of Directors who can incorporate these technological changes into specific new business models, strategies, and practices. While the awareness on boards regarding risks originating from disruptive innovation, cyber threats and privacy risks has been increasing, Boards of Directors must equally be able to challenge executives and identify opportunities and threats for their companies. This shift for companies is not only about digital technology but also cultural. How can people be managed when digital, virtual ways of working are increasing? What do robotics and Big Data analysis mean for managing people? One way to accelerate the digital learning process has been advocated: the use of digital apprentices for boards. For example, Board Apprentice, a non-profit organization, has already placed digital apprentices on boards for a year-long period (which helps to educate both apprentices and boards) in five different countries. Additional plans and strategies are needed in this age of digitalization and lifelong learning. For example, cybersecurity risks are magnified by all these new technology trends, such as Big Data, AI, Industry 4.0, and IoT. Accordingly, the main findings of this paper are analysing the challenges and opportunities for corporate executives, Boards of Directors, and related corporate governance concerning the driving force of Big Data, Artificial Intelligence with Industry 4.0, Artificial Intelligence with the Internet of Things, Deep Learning, and Neural Networks.

Balancing Exploration and Exploitation Through Customer Development Model

2021 ◽  
pp. 839-852
Author(s):  
Krishna Raj Bhandari
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Best Practices ◽  
Industry 4.0 ◽  
Development Model ◽  
Exploration And Exploitation ◽  
Customer Development

Balancing exploration and exploitation in entrepreneurial ventures enabled by Industry 4.0 has not been the focus of the existing literature. It is because the phenomenon is emerging and the focus has been to use practitioners' best practices in studying such phenomenon. In this chapter, the author combines the literature in balancing exploration and exploitation with the practitioners' best practices such as customer development model and lean startup. The author proposes that the existing models are good in principle but in order to really solve the problem in such an uncertain environment driven by big data, cloud computing, internet of things (IoT), and artificial intelligence, managers need to embed optimization algorithms in their decision making.

Relationships between industry 4.0, sustainable manufacturing and circular economy: proposal of a research framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Surajit Bag ◽  
Jan Harm Christiaan Pretorius
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Circular Economy ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Sustainable Manufacturing ◽  
Big Data Analytics ◽  
Content Type ◽  
Research Framework ◽  
Challenges And Opportunities

Purpose The digital revolution has brought many challenges and opportunities for the manufacturing firms. The impact of Industry 4.0 technology adoption on sustainable manufacturing and circular economy has been under-researched. This paper aims to review the latest articles in the area of Industry 4.0, sustainable manufacturing and circular economy and further developed a research framework showing key paths. Design/methodology/approach Qualitative research is performed in two stages. In the first stage, a review of the extant literature is performed to identify the barriers, drivers, challenges and opportunities. In the second stage, a research framework is proposed to integrate Industry 4.0 technology (big data analytics powered artificial intelligence) adoption, sustainable manufacturing and circular economy capabilities. Findings This research extends the knowledge base by providing a detailed review of Industry 4.0, sustainable manufacturing, and circular economy and proposes a research framework by integrating these three contemporary concepts in the context of supply chain management. Through an exploration of this integrative research framework, the authors propose a future research agenda and seven research propositions. Research limitations/implications It is important to understand the interplay between institutional pressures, tangible resources and human skills for Industry 4.0 technology (big data analytics powered artificial intelligence) adoption. Industry 4.0 technology (big data analytics powered artificial intelligence) adoption can positively influence sustainable manufacturing and circular economy capabilities. Managers must also put more attention to sustainable manufacturing to develop circular economic capabilities. Social implications Factory workers and the local communities generally suffer from various adverse effects resulting from the traditional manufacturing process. The quality of the environment is deteriorating to such an extent that people even staying miles away from the factory are also affected due to environmental pollution that is generated from factory operations. Hence, sustainable manufacturing is the only choice left to manufacturers that can help in the transition to a circular economy. The research framework can help firms to enhance circular economy capabilities. Originality/value This review paper contains the most updated work on Industry 4.0, sustainable manufacturing and circular economy. It also proposes a research framework to integrate these three concepts.

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