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Artificial Intelligence-driven Big Data Analytics, Real-Time Sensor Networks, and Product Decision-Making Information Systems in Sustainable Manufacturing Internet of Things

Artificial Intelligence-driven Big Data Analytics, Real-Time Sensor Networks, and Product... 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 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Economics, Management, and Financial Markets Addleton Academic Publishers

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 , Volume 16 (3): 13 – Jan 1, 2021

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1842-3191
eISSN
1938-212X
Publisher site
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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

Journal

Economics, Management, and Financial MarketsAddleton Academic Publishers

Published: Jan 1, 2021

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