Industry 4.0-based Manufacturing Systems: Smart Production, Sustainable Supply Chain Networks, and Real-Time Process Monitoring.

Author:Tuffnell, Caryl
 
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  1. Introduction

    Having a significant extended strategic effect on worldwide industrial advancement, Industry 4.0 can impressively boost the entire degree of computerization, industrialization, and manufacturing digitization to attain superior coherence, proficiency, and competitiveness. (Xu et al., 2018) Industry 4.0 is the main driver in the framework of digital and automated manufacturing setting, encompassing an array of technologies to facilitate the buildout of the value chain, giving rise to diminished manufacturing lead times, and enhanced product quality and organizational effectiveness. (Kamble et al., 2018)

  2. Conceptual Framework and Literature Review

    Industry 4.0 addresses the continuous digitization and the consolidation of digital industrial ecosystems by pursuing thoroughly integrated solutions. (Xu et al., 2018) As the business approach of small and medium-sized enterprises is frequently developed on resilience, responsiveness, and customer contiguity, Industry 4.0 is irresistible in respect of possibly supplying a more smoothrunning flow of data and consequently superior planning and control operations. (Moeuf et al., 2018) With sensor automation and radio-frequency technique, Internet of Things technology can connect lines of work, machines, devices, installations, vehicles, robots, and individuals to produce big data across the entire factory. (Zhang et al., 2019)

  3. Methodology and Empirical Analysis

    Building our argument by drawing on data collected from BCG, Deloitte, PwC, and Statista, we performed analyses and made estimates regarding Industry 4.0 across the value chain (%), revenues from artificial intelligence for enterprise applications market worldwide (from 2018 to 2025, in million U.S. dollars), and Industry 4.0 framework and contributing digital technologies (%). Multivariate statistics techniques have been applied for data analyses (e.g. structural equation modeling).

  4. Results and Discussion

    Industry 4.0 tools may mobilize the implementation of a cutting-edge generation of proposals. Data-driven analysis may be adopted to upgrade the sustainable ways out meant to cut down the resource and emission volumes of industrial systems. (Tseng et al., 2018) Computer systems having outstanding capacity can incorporate the network data of workforce, machines, and devices so as to handle and supervise production process elaborately. (Zhang et al., 2019) Developed economies have adequately utilized digital technology to set...

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