Sensor-based and Cognitive Assistance Systems in Industry 4.0: Big Data Analytics, Smart Production, and Sustainable Value Creation.

• Author: Dolan-Canning, Rebecca

1. Introduction

   Industry 4.0 enhances adjustability in production, thus resulting in an additional customization of manufactures, the machines interacting for the implementation of production plan. (Bag et al., 2018) Industry 4.0 reinforces backshoring by supplying a more significant output and flexibility which provides an impulse for companies to establish production in the vicinity of their customers. (Dachs et al., 2019) Industry 4.0-enabling technologies that bolster data and knowledge distribution are growing, while organizational advancement can sustain their performance. (Li et al., 2019a)

2. Conceptual Framework and Literature Review

   Industry 4.0-enabled supply chain innovation increases the preliminary interest in productivity enhancements in supply chain operations in relation to scalability and adjustability. (Hahn, 2019) Internet-of-Things based manufacturing systems put into action swift decisions, while placing reliance on the design and associated intelligence firmly established into the system. (Oztemel and Gursev, 2018) Manufacturing settings can take advantage of cloud technology and more thoroughly carry out swift alterations in market demands, by adopting heterogeneous cloud deployment patterns and by virtualizing manufacturing operations and resources into services. (Pedone and Mezgar, 2018) Organizational and managerial routines at the company process and supply chain level (Hyers and Kovacova, 2018; Makrakis, 2017; Nica, 2018; Popescu Ljungholm, 2018; Radulescu, 2018) have a direct effect on the putting into practice of Industry 4.0 technologies, despite the fact that at the human resource level (Kanovska, 2018; Mihaila et al., 2018; Petcu, 2018; Popescu, 2018; Sanda and Krupka, 2018) they function as a moderator. (Agostini and Filippini, 2019)

3. Methodology and Empirical Analysis

   Building my argument by drawing on data collected from BDO, Deloitte, HIS, IFR, and PwC, I performed analyses and made estimates regarding key impacts of Industry 4.0 at the organizational level (%), top barriers to Industry 4.0 implementation (%), advanced technologies manufacturers are using now (%), and strategies for employee adoption of advanced technologies (%). Structural equation modeling was used to analyze the collected data.

4. Results and Discussion

   Industry 4.0-associated technologies may open up environmentally-sustainable manufacturing. (de Sousa Jabbour et al., 2018) Because the exponential volumes of industrial information develop on the operating stages, the big data analytics can systematize the digital resources and derive important observations from them. (Li et al., 2019b) Humans are valuable in the manufacturing sector as its sophistication boosts in an Industry 4.0 environment, chiefly as a...