chunk1

ABSTRACT. We develop a conceptual framework based on a systematic and comprehensive literature review on artificial intelligence-driven big data analytics, real-time sensor networks, and product decision-making information systems in sustainable manufacturing Internet of Things. Building our argument by drawing on data collected from Management Events and McKinsey, we performed analyses and made estimates regarding how reliable and resilient smart factories develop on deep learning-based autonomous assembly systems. The data for this research were gathered via an online survey questionnaire. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: artificial intelligence; sustainability; manufacturing; Internet of Things

How to cite: Adams, D., and Krulicky, T. (2021). “Artificial Intelligence-driven Big Data Analytics, Real-Time Sensor Networks, and Product Decision-Making Information Systems in Sustainable Manufacturing Internet of Things,” Economics, Management, and Financial Markets 16(3): 81–93. doi: 10.22381/emfm16320215.

Received 12 April 2021 • Received in revised form 1 September 2021
Accepted 13 September 2021 • Available online 18 September 2021

Donald Adams
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Cognitive Labor Institute,
New York City, NY, USA
(corresponding author)
Tomas Krulicky
This email address is being protected from spambots. You need JavaScript enabled to view it.
The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceské Budejovice, Czech Republic

Home | About Us | Events | Our Team | Contributors | Peer Reviewers | Editing Services | Books | Contact | Online Access

© 2009 Addleton Academic Publishers. All Rights Reserved.

 
Joomla templates by Joomlashine