Sustainable Internet-of-Things-based Manufacturing Systems: Industry 4.0 Wireless Networks, Advanced Digitalization, and Big Data-driven Smart Production.

• Author: Lafferty, Clive

1. Introduction

   Cutting-edge Industry 4.0 technologies enable companies to diminish the volume of resources misdirected and the emissions, bringing forth a prevailing low-carbon upside in addition to a decrease of the marginal production expense. (Liu and De Giovanni, 2019) The transformative capacity that functions within Industry 4.0, digitalization, and digital twins is instrumental in enhancing operational performance and cutting down process safety accidents. (Lee et al., 2019) Industry 4.0 can offer cost benefits of mass manufacturing with the adjustability of a small-batch producer. (Dachs et al., 2019)

2. Conceptual Framework and Literature Review

   The socially impacted undertakings in Industry 4.0 entail collection investment and dimension of the customer market that regulates the product returns, shaping the competitive reverse logistics system. (Dev et al., 2020) Integrated high tech and networks supervise via sensors and coordinate via actuators the physical operations (Andrei et al., 2016; Mengoli et al., 2017; Nica, 2018a, b; Sandal and Krupka, 2018), commonly with input loops where physical operations and data processing shape each other. (Delicato et al., 2019) The production tools can make decisions in real time and clarify with the end user the alterations that can be implemented, in conformity with the assigned work streaming through the manufacturing system. (Rossit et al., 2019) Assimilating industrial automation systems leads to significant and groundbreaking characteristics via networking with team members (Ionescu, 2018; Nica, 2015; Popescu et al., 2017a, b; Valaskova et al., 2018), and assists in generating links between the cyber and physical realms. (Buchi et al., 2020) Repetitive and physically challenging tasks are handled by assistance systems, resulting in growing demands in respect of human resources' mental processes and performance. (Veile et al., 2019) Becoming competent at a distinct level is not instrumental as a mediator in the influence of Industry 4.0-based technologies on operational effectiveness. (Tortorella et al., 2020)

3. Methodology and Empirical Analysis

   Using and replicating data from Capgemini, DAA, IoT Analytics GmbH, The Manufacturer, McKinsey, Oracle, PwC, US BLS, and WEF, I performed analyses and made estimates regarding smart factory transformation approach taken by players in different categories (%) and drivers of technological change and time to impact on employee skills (%). Data were analyzed using structural equation modeling.

4. Results and Discussion

   With the swift advancement of Industry 4.0, cutting-edge technologies (e.g., big data, Internet of Things, and cloud computing) are progressively being applied, while established industrial production technologies will steadily develop or be replaced. (Lu et al., 2019) Industry 4.0 facilitates the monitoring of manufacturing operations by supplying instantaneous integration of flows and by furthering the fashioning of distinctive and custom-tailored commodities. (Moeuf et al., 2019) A digital...