Smart Industrial Value Creation, Cyber-Physical Production Networks, and Real-Time Big Data Analytics in Sustainable Internet of Things-based Manufacturing Systems.

AuthorChessell, Darren
  1. Introduction

    The glocalization of cutting-edge systems is triggered by non-linear and dynamic operations of knowledge creation, sharing, and utilization. (Panori et al., 2020) Smart products can network with production facilities and can handle their own manufacturing flow. (Jasko et al., 2020) Smart and wireless sensor networks configure cyber-physical systems. (Zhou et al., 2020)

  2. Conceptual Framework and Literature Review

    The shift of cutting-edge systems in the direction of cyber-physical ones is associated with upsides brought about when digital networking and e-tools are harnessed in the operations of innovation. (Panori et al., 2020) In Industry 4.0, manufacturing execution systems have to manage swift transfers of heterogeneous unstructured and structured data (Andrei et al., 2016a, b; Connolly-Barker et al., 2020; Kliestik et al., 2020a, b, c; Nica et al., 2018; Popescu et al., 2017) that is to be turned into valuable designed information instantaneously. (Jasko et al., 2020) Manufacturing and enterprise applications configure smart networked systems. (Zhou et al., 2020) Notwithstanding a growing demand for computerized process surveillance and condition supervision in production settings (Andrei et al., 2020; Englund, 2019; Kovacova et al., 2019; Mihaila et al., 2016; Popescu et al., 2018), personnel as regards manual commands of operations, assessments of situations, and consistency of diagnoses (Clark, 2020; Kliestik et al., 2018; Lazaroiu et al., 2020a, b, c; Peters et al., 2020; Smith, 2020) may be disregarded so as to ensure an effective and sustainable smart manufacturing. (Iber et al., 2020)

  3. Methodology and Empirical Analysis

    Using and replicating data from CompTIA, Deloitte, EY, IW Custom Research, Kronos, MHI, PwC, and SME, we performed analyses and made estimates regarding the link between smart industrial value creation, cyber-physical production networks, and real-time big data analytics. Data were analyzed using structural equation modeling.

  4. Results and Discussion

    Cutting-edge cyber-physical systems are harnessed by heterogeneous nodes configuring digital entities, collaboration takes place across physical and digital realms, and intricate approaches assisted by software can be used to gain insights from big data analytics. (Panori et al., 2020) Manufacturing execution systems have to manage the data flows required in cyber-physical production systems. (Jasko et al., 2020) Huge volumes of data are produced in a shared manner and cross-domain information has to be distributed and inspected consistently and adequately to articulate a robust supply chain management. (Zhou et al., 2020) While the bio- and circular economy displays perspectives of sustainable subsistence strategies, the biological transformation designs a mechanism of change that is valid for data-driven sustainable smart manufacturing. (Miehe et al., 2020) (Tables 1-11)

    Cutting-edge innovations are configured by how systems of breakthroughs articulate online, leading to the setting up of cyber-physical manufacturing systems in which joint effort networks, platforms, and big data analytics further groundbreaking mechanisms, capabilities, and performance. (Panori et al., 2020) A cyber-physical system is an entity having a particular computing capacity and integrated software, and, by use of Industry 4.0 wireless networks, the manufactured goods can eventually be smart. (Jasko et al., 2020) Cyber-physical systems develop on a robust interaction between computational and physical elements. (Zhou et al., 2020) Networked Industry 4.0 plants are significantly contingent upon cutting-edge embedded Internet of Things sensors and fog and cloud computing. (Priya and Rekha, 2020) Established modes of production considerably hinder the expectations of next generations to sustainably fulfill their material demands. (Miehe et al., 2020)

    Manufacturing execution systems should link all elements of cyber-physical systems in a coherent, secure, and reliable fashion to facilitate first-rate computerized smart solutions, while semantic metadata can offer contextual input to reinforce interoperability and modular advancement. (Jasko et al., 2020) Cyber-physical systems and smart applications considerably develop on the performance and extension of physical and wireless sensor networks. (Zhou et al., 2020) Internet of Things-based real-time production logistics assimilates groundbreaking technologies, organizational notions and management standards bolstering a financially rewarding, responsive, robust, and sustainable network, big data-driven and vigorously and constitutively adjustable to alterations in the demand and supply setting by swift reorganization and redistribution of its elements and capabilities. (Ivanov et al., 2020) Being cognizant of the consequences that a local failure can...

To continue reading

Request your trial