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Artificial Intelligence

Implementation and Obstacles in Industry 4.0

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Handbook of Metrology and Applications

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Abstract

In the fourth industrial revolution (Industry 4.0), Artificial Intelligence (AI) had been a cognitive science that produces actual value needed for relevant data with processing capabilities and algorithms. Manufacturing in the Internet-of-Thing (IoT) era will be more efficient, better quality, easier to manage, and more transparent through integration of physical and cyber technologies in Industry 4.0-based smart factories. Factory automation relies heavily on sensors and AI to make the system intelligent. Sensor technology advancements and developments linked to Industry 4.0 serve as the backbone for the inclusive expansion of industry and the economic success of any country. It is imperative that manufacturing organizations and supply chains have access to the latest low-cost sensor technology for collecting data and putting it to good use. Standard sensor types include position sensors, flow, temperature, flow rate, pressure, and force. A wide range of fields, including motorsport, health care, manufacturing, the armed forces, and agriculture all make use of them on a day-to-day basis. Increasing efficiency through automation is the goal of Industry 4.0. The purpose of this chapter is to provide a brief overview and viewpoint on the most recent advancements in AI and the associated problems.

Attempts to define the main ideas and tools behind this new era of manufacturing in the early years of the so-called fourth industrial revolution (Industry 4.0) always ended up referring to the concept of smart machines that could communicate with each other and with the environment. When it comes to the new industry 4.0, it’s the defined cyber physical systems connected by the IoT that get all the attention. Nonetheless, several tools and applications will benefit the new industrial environment, complementing the actual formation of a smart, embedded system capable of performing autonomous tasks. And the majority of these revolutionary ideas are based on the same background theory as artificial intelligence, in which the analysis and filtration of massive amounts of incoming data from various types of sensors aids in the interpretation and recommendation of the best course of action. As a result, artificial intelligence science is well suited to the challenges that arise during the fourth industrial revolution’s consolidation. The purpose of this chapter is to provide a brief overview and viewpoint on the most recent advancements in AI and the associated problems.

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Authors and Affiliations

  1. CSIR-Advanced Materials and Processes Research Institute (AMPRI), Bhopal, India

    Kirti Soni & Nishant Kumar

  2. CSIR - National Physical Laboratory, New Delhi, India

    Anjali S. Nair

  3. Thapar Institute of Engineering and Technology, Patiala, India

    Parag Chourey, Nirbhow Jap Singh & Ravinder Agarwal

Authors
  1. Kirti Soni
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  2. Nishant Kumar
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  3. Anjali S. Nair
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  4. Parag Chourey
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  5. Nirbhow Jap Singh
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  6. Ravinder Agarwal
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Correspondence to Kirti Soni .

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Editors and Affiliations

  1. Bhabha Atomic Research Centre, Mumbai, Maharashtra, India

    Dinesh K. Aswal

  2. Physico-Mechanical Metrology, CSIR - National Physical Laboratory, New Delhi, Delhi, India

    Sanjay Yadav

  3. National Metrology Institute of Japan, National Institute of Advanced Industrial, Ibaraki, Japan

    Toshiyuki Takatsuji

  4. National Institute of Standards and Tech, Gaithersburg, MD, USA

    Prem Rachakonda

  5. Mechanical Engineering Department, National Institute of Technology, Delhi, India

    Harish Kumar

Section Editor information

  1. Mechanical Engineering Department, National Institute of Technology (NIT), Delhi, India

    Harish Kumar

  2. M M University Ambala, Ambala, India

    Dharambir Singh PhD

  3. CSIR-National Physical Laboratory, New Delhi, India

    P. K Dubey PhD

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Soni, K., Kumar, N., Nair, A.S., Chourey, P., Singh, N.J., Agarwal, R. (2023). Artificial Intelligence. In: Aswal, D.K., Yadav, S., Takatsuji, T., Rachakonda, P., Kumar, H. (eds) Handbook of Metrology and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-99-2074-7_54

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