Acta Scientific Pharmaceutical Sciences (ASPS)(ISSN: 2581-5423)

Review Article Volume 4 Issue 5

Forecasting Future of Manufacturing Systems Driven by Artificial Intelligence: Recent Progress and Future Directions

Bahman Zohuri1* and Farhang Mossavar Rahmani2

1Adjunct Professor, Golden Gate University, Ageno School of Business, Data Analytic, San Francisco, California, USA
2Professor of Finance and Director of MBA School of Business and Management, National University, San Diego, California, USA

*Corresponding Author: Bahman Zohuri, Adjunct Professor, Golden Gate University, Ageno School of Business, Data Analytic, San Francisco, California, USA

Received: March 31, 2020; Published: April 29, 2019

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Abstract

  The start of a new decade brings a new wave of technological change and unprecedented opportunities that will generate massive amounts of data at the level of Big Data (BD), spawn new threats and transform the way we do business. Dealing with such enormous data structurally or unstructured-wise and process it in real-time requires a new innovative technology such as Artificial Intelligence (AI). Today, AI is capable of learning from its experience through the element of its Machine Learning (ML) in conjunction with the Deep Learning (DL) component and using them to adjust to new input and perform human-like performance, or at least to complement and enhance human abilities. Because of this capability, it encompasses every aspect of the enterprise in the years to come. That is why we believe AI, Automation, and Analytics are central to the success of the enterprise and encompass critical business areas, including data, business processes, the workforce, and risk and reputation.

Keywords:Artificial Intelligence; Machine Learning; Deep Learning; Resilience System; Forecasting and Related Paradigm; Big Data; Fuzzy Logic; Industrial Robotics

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Citation

Citation: Bahman Zohuri.,et al. “Forecasting Future of Manufacturing Systems Driven by Artificial Intelligence: Recent Progress and Future Directions".Acta Scientific Pharmaceutical Sciences 4.5 (2020): 46-49.




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Acceptance rate32%
Acceptance to publication20-30 days

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