Smart Manufacturing Technologies: Data-driven Algorithms in Production Planning, Sustainable Value Creation, and Operational Performance Improvement.

• Date: 01 June 2019
• Author: Whittle, Therese

1. Introduction

   Organizations should give thought to Industry 4.0 rigorously while advancing their planned projects as established production business patterns do not satisfy the demands of the cutting-edge technologies. (Sung, 2018) Breakthrough manufacturing and logistics systems, Industry 4.0 networks, and supply chains are confronted with escalated unpredictability and risks, various feedback patterns, and underlying forces. (Ivanov et al., 2018)

2. Conceptual Framework and Literature Review

   Industry 4.0 strategies may shape the entire business system through reorganizing the procedures of designing, manufacturing, distributing, and getting rid of products (Grossman, 2018; Ionescu, 2018; Lazaroiu, 2018; Meila, 2018a, b; Neary et al., 2018; Popescu Ljungholm, 2018), assisting industries to integrate environmental protection and monitoring approaches in addition to processing safety procedures in the direction of sustainable supply chains. (Luthra and Mangla, 2018) As a lesser amount of workers are in contact with equipment throughout the production process, there is an increasing demand for manufacturing supervision. (Roman-Ibanez et al., 2018) In the smart industry, incessant overseeing of the equipment condition is key in pursuing the decision-making approach. (Dinardo et al., 2018) A mix of centralized and shared decision making in monitoring may be instrumental in obtaining an enhanced and steady logistics performance. (Bendul and Blunck, 2019)

3. Methodology and Empirical Analysis

   Using and replicating data from BI Intelligence, Capgemini, Deloitte, eMarketer, Forbes, PwC, Statista, and Zebra Technologies, we performed analyses and made estimates regarding industries targeted by machine learning application developers (%), the main areas of interest for manufacturers within Industry 4.0 (%), retailers planning to invest in artificial intelligence and Internet of Things technologies by 2021 (%), and benefits of implementing artificial intelligence (%). Data collected from 4,400 respondents are tested against the research model by using structural equation modeling.

4. Results and Discussion

   The service-based model of cloud computing facilitates teamwork and information transfer on superior level, with more advanced productivity and simultaneously reducing expenses. (Pedone and Mezgar, 2018) Smart objects (e.g. machines, components, and products), should be allocated assignments of manufacturing supervision so as to achieve greater adjustability and thus more significant logistics performance, but insufficient data and diminished computation...