Sustainable Industry 4.0: Product Decision-Making Information Systems, Data-driven Innovation, and Smart Industrial Value Creation.

Author:Lafferty, Clive
  1. Introduction

    Industry 4.0 is adequate for advancing a groundbreaking creation of manufacturing systems that incorporate and integrate real-time information between the physical objects and the cyber computational realm. Elaborate engineering issues have to be remedied in partnership by collaborative groups with heterogeneous computational software and physical systems. (Xu et al., 2018) Unsatisfactory layout design diminishes the rigorousness in manufacturing of commodities and intensifies the production time. (Kumar et al., 2018)

  2. Conceptual Framework and Literature Review

    The embracing of inexpensive technological groups (e.g. cloud computing), leads to swifter and more affordable production processes enhancements (Bratu, 2018; Carter and Yeo, 2018; Hardingham et al., 2018; Mihaila et al., 2018; Popescu Ljungholm, 2017, 2018) without reshaping transactions between manufacturers and customers. (Moeuf et al., 2018) In a cloud manufacturing setting, a distribution and service platform for integrating regional production resources and accomplishing adequate sharing and exemplary administrations can be set up. Merging the logistics enhancement technology with proficiency in investigating the teamwork mode between multi-plants and logistics companies, a cutting-edge cloud manufacturing service platform can be established. (Zhang et al., 2019) A layout design developed on wide-ranging big data is more coherent and valid in the current competitive market. Because of dissimilarities in product demands, fluctuating product mix, and inclusion or removal of commodities, layout of sector should be resilient and sustainable. (Kumar et al., 2018)

  3. Methodology and Empirical Analysis

    Building my argument by drawing on data collected from British Science Week, Business Insider, Deloitte, PwC, Statista, and YouGov, I performed analyses and made estimates regarding the main areas of interest for manufacturers within Industry 4.0 (%), how Industry 4.0 is delivering revenue, cost and efficiency gains (%), U.S. adults who feel the following ways about artificial intelligence (%), and Industry 4.0 value creation (%). Structural equation modeling was used to analyze the collected data.

  4. Results and Discussion

    The initial phase for evolving into Industry 4.0 is the advancement of an overarching strategic protocol that thoroughly determines and organizes every operation a manufacturing firm should take, in addition to the calendar, expenses, and upsides...

To continue reading