Sensor Networks and Intelligent Automation Systems for Big Data-driven Smart Manufacturing in Cyber-Physical Connected Environments.

Author:Hyers, Douglas
 
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  1. Introduction

    Cyber-physical systems offer a prompt access to data in production settings derived from shared intelligence for smart objects. (Yao et al., 2019) Overfull bandwidth and information loss curb the advancement of smart manufacturing. (Tao et al., 2019a) Smart manufacturing and Industry 4.0 production sites assimilate the concrete and decision-making features of manufacturing operations so as to attain their decentralization and self-governance. (Rossit et al., 2019)

  2. Conceptual Framework and Literature Review

    Cyber--physical integration represents a necessary condition for smart manufacturing (Tao et al., 2019b), whose advancement is generally influenced by data. (Kusiak, 2019) For a smart factory, actual supervision, simulation, and prediction of production processes (Kovacova and Kliestik, 2017; Lazaroiu et al., 2017; Mihaila et al., 2018; Nica et al., 2018; Nica, 2018a, b; Valaskova et al., 2018) are essential in enhancing the manufacturing efficiency and adjustability. (Ding et al., 2019) Smart manufacturing systems collect instantaneous data that furthers the precision of decision making, optimizes the coherence and performance of the industrial unit, and boosts overall output. (Qu et al., 2019)

  3. Methodology and Empirical Analysis

    Using and replicating data from Accenture, Deloitte, Management Events, and PwC, I performed analyses and made estimates regarding current state of customer experience management (%), Industry 4.0 investments broken down by steps of the value chain (%, priorities), degree of digitization of the value chain by industry sector (%), top challenges in changing strategy and in preparing the workforce for Industry 4.0 (%), and worker time potentially augmented/automated by intelligent technologies (%). The results of a study based on data collected from 4,400 respondents provide support for my research model. Using the structural equation modeling and employing the probability sampling technique, I gathered and analyzed data through a self-administrated questionnaire.

  4. Results and Discussion

    Smart manufacturing concerns assimilating cutting-edge big data technologies and groundbreaking manufacturing technologies to enhance business efficiency, boost customer contentment, and improve market competitiveness. (Li et al., 2019) Smart manufacturing is a production pattern developed on cyber-physical systems that is connected to the Internet of Things, cloud computing, and big data. (Yao et al., 2019) Cyber-physical integration and networking are pivotal to accomplishing smart manufacturing. (Yang et al., 2019) (Tables 1-8)

  5. Conclusions and Implications

    In smart manufacturing, employees are confronting a growing...

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