scholarly journals Defining SMEs’ 4.0 Readiness Indicators

2020 ◽  
Vol 10 (24) ◽  
pp. 8998
Author(s):  
Nilubon Chonsawat ◽  
Apichat Sopadang
Keyword(s):  
Decision Making ◽  
Industry 4.0 ◽  
Production Efficiency ◽  
Cloud Manufacturing ◽  
Smart Manufacturing ◽  
Increase Production Efficiency ◽  
Five Dimensions ◽  
High Stage ◽  
Industrial Internet ◽  
Infrastructure System

Industry 4.0 revolution offers smart manufacturing; it systematically incorporates production technology and advanced operation management. Adopting these high-state strategies can increase production efficiency, reduce energy consumption, and decrease manufacturer costs. Simultaneously, small and medium-sized enterprises (SMEs) were the backbone of economic growth and development. They still lack both the knowledge and decision-making to verify this high-stage technology’s performance and implementation. Therefore, the research aims to define the readiness indicators to assess and support SMEs toward Industry 4.0. The research begins with found aspects that influence the SME 4.0 readiness by using Bibliometric techniques. The result shows the aspects which were the most occurrences such as the Industrial Internet, Cloud Manufacturing, Collaborative Robot, Business Model, and Digital Transformation. They were then grouped into five dimensions by using the visualization of similarities (VOS) techniques: (1) Organizational Resilience, (2) Infrastructure System, (3) Manufacturing System, (4) Data Transformation, and (5) Digital Technology. Cronbach’s alpha then validated the composite dimensions at a 0.926 level of reliability and a significant positive correlation. After that, the indicators were defined from the dimension and aspects approach. Finally, the indicators were pilot tested by small enterprises. It appeared that 23 indicators could support SMEs 4.0 readiness indication and decision-making in the context of Industry 4.0.

scholarly journals Middleware Application, Suitable to Build an Automated and Connected Smart Manufacturing Environment

2021 ◽  
Author(s):  
Muzaffar Rao ◽  
Thomas Newe
Keyword(s):  
Mobile Robots ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Manufacturing Execution System ◽  
Manufacturing Environment ◽  
Industrial Internet ◽  
A Cell ◽  
Smart Industry ◽  
Manufacturing Execution

The current manufacturing transformation is represented by using different terms like; Industry 4.0, smart manufacturing, Industrial Internet of Things (IIoTs), and the Model-Based enterprise. This transformation involves integrated and collaborative manufacturing systems. These manufacturing systems should meet the demands changing in real-time in the smart factory environment. Here, this manufacturing transformation is represented by the term ‘Smart Manufacturing’. Smart manufacturing can optimize the manufacturing process using different technologies like IoT, Analytics, Manufacturing Intelligence, Cloud, Supplier Platforms, and Manufacturing Execution System (MES). In the cell-based manufacturing environment of the smart industry, the best way to transfer the goods between cells is through automation (mobile robots). That is why automation is the core of the smart industry i.e. industry 4.0. In a smart industrial environment, mobile-robots can safely operate with repeatability; also can take decisions based on detailed production sequences defined by Manufacturing Execution System (MES). This work focuses on the development of a middleware application using LabVIEW for mobile-robots, in a cell-based manufacturing environment. This application works as middleware to connect mobile robots with the MES system.

scholarly journals Significant directions of digitalization of the Khabarovsk Territory economy in the implementation of the national program “Digital Economy”

2021 ◽  
Vol 128 ◽  
pp. 01016
Author(s):  
Luyciena Piunko ◽  
Elena Tolkacheva
Keyword(s):  
Industry 4.0 ◽  
Resource Planning ◽  
Digital Economy ◽  
Digital Transformation ◽  
International Standards ◽  
Smart Manufacturing ◽  
Computer Algorithms ◽  
Production Processes ◽  
Industrial Internet ◽  
And Control

The research is devoted to the modern development of digital transformation in the Russian economy, including in the Khabarovsk Territory; the difficulties of implementing the directions of the “Digital Economy”. In this study, an attempt is made to compare the strategic goals of the development of the “Digital Economy”, modern processes of digital transformation and such an important component of it as "Integration 4.0" related to the “industrial Internet”, digital production, intelligent components, including the collection of large amounts of data, cyberphysical systems, remote monitoring and maintenance. “Industry 4.0” accelerates production processes, increases its efficiency and the quality of manufactured goods, reduces the cost of delivery, tracks production chains, etc. Currently, the industry of Western countries uses Industry 4.0 standards at the production management level. In developed countries, such as Germany, South Korea, etc., they realize the importance of automation and computerization, which became the main tool of the third industrial revolution, and its tools for the transition to “Industry 4.0”. International standards are developed for industries that use computer algorithms to monitor and control physical things, such as equipment, robots and vehicles. Standards that work on the basis of the Industrial Internet of Things (IIoT) and cyber—physical systems — intelligent autonomous systems that define all components of the supply chain, transforming production processes into “smart” - from smart manufacturing and factories to smart warehouses and logistics. And, the same systems are associated with the previous stage of industrial production, such as enterprise resource planning (ERP). All this ensures a high level of transparency and control over the activities of the organization. At the present stage, there are excellent opportunities for the development of Industry 4.0 in Russia, but there are also difficulties, overcoming which are significant directions of the digitalization processes of the modern economy. The authors devoted their research to the analysis of such difficulties.

A Study on Deep Learning Methods in the Concept of Digital Industry 4.0

2021 ◽  
pp. 318-339
Author(s):  
Mehmet Ali Şimşek ◽  
Zeynep Orman
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Deep Learning ◽  
Industry 4.0 ◽  
Production Efficiency ◽  
Learning Technologies ◽  
High Potential ◽  
Data Sets ◽  
Learning Methods ◽  
Intelligence Studies

Nowadays, the main features of Industry 4.0 are interpreted to the ability of machines to communicate with each other and with a system, increasing the production efficiency and development of the decision-making mechanisms of robots. In these cases, new analytical algorithms of Industry 4.0 are needed. By using deep learning technologies, various industrial challenging problems in Industry 4.0 can be solved. Deep learning provides algorithms that can give better results on datasets owing to hidden layers. In this chapter, deep learning methods used in Industry 4.0 are examined and explained. In addition, data sets, metrics, methods, and tools used in the previous studies are explained. This study can lead to artificial intelligence studies with high potential to accelerate the implementation of Industry 4.0. Therefore, the authors believe that it will be very useful for researchers and practitioners who want to do research on this topic.

scholarly journals Formal Tools for Management of Manufacturing Systems: A Multi Agents System Approach

2019 ◽  
Vol 13 (5) ◽  
pp. 691-699
Author(s):  
Doriana M. D’Addona ◽  
Alessandro A. Bruzzone ◽  
◽  
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Cloud Manufacturing ◽  
Technological Innovations ◽  
Real Sector ◽  
Multi Agent System ◽  
Industrial Internet ◽  
Multi Agent ◽  
Multi Agents

To overcome the consequences of the 2008 crisis on the real sector, especially manufacturing, Industry 4.0 gives guidelines to drive production by emphasizing technological innovations, such as industrial internet, cloud manufacturing, etc. The proposed paper focuses on cognitive manufacturing within the framework of the emergent synthesis paradigm. Specifically, the structuring process by which the manufacturing assets are organized to provide the finished goods is analyzed. The study is carried out by considering the analogies between manufacturing and other inventive processes supported by formal tools such as formal languages, semantic webs, and multi agent system.

scholarly journals Secure IIoT-Enabled Industry 4.0

2021 ◽  
Vol 13 (22) ◽  
pp. 12384
Author(s):  
Zeeshan Hussain ◽  
Adnan Akhunzada ◽  
Javed Iqbal ◽  
Iram Bibi ◽  
Abdullah Gani
Keyword(s):  
Industry 4.0 ◽  
Smart Manufacturing ◽  
Detection Accuracy ◽  
Hybrid Architecture ◽  
Advanced Persistent Threats ◽  
Current State ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Detection Mechanisms ◽  
Conventional Detection

The Industrial Internet of things (IIoT) is the main driving force behind smart manufacturing, industrial automation, and industry 4.0. Conversely, industrial IoT as the evolving technological paradigm is also becoming a compelling target for cyber adversaries. Particularly, advanced persistent threats (APT) and especially botnets are the foremost promising and potential attacks that may throw the complete industrial IoT network into chaos. IIoT-enabled botnets are highly scalable, technologically diverse, and highly resilient to classical and conventional detection mechanisms. Subsequently, we propose a deep learning (DL)-enabled novel hybrid architecture that can efficiently and timely tackle distributed, multivariant, lethal botnet attacks in industrial IoT. The proposed approach is thoroughly evaluated on a current state-of-the-art, publicly available dataset using standard performance evaluation metrics. Moreover, our proposed technique has been precisely verified with our constructed hybrid DL-enabled architectures and current benchmark DL algorithms. Our devised mechanism shows promising results in terms of high detection accuracy with a trivial trade-off in speed efficiency, assuring the proposed scheme as an optimal and legitimate cyber defense in prevalent IIoTs. Besides, we have cross-validated our results to show utterly unbiased performance.

Orientation to Sustainable and Climate Adapted Agriculture with Advanced Technology in Industry 4.0 in Vietnam

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Do Thi Dung ◽  
Nguyen Hung Cuong ◽  
Do Khanh Duy ◽  
Do Thi Huong
Keyword(s):  
Rural Areas ◽  
Industry 4.0 ◽  
Production Efficiency ◽  
Agricultural Sector ◽  
Global Climate ◽  
Advanced Technology ◽  
Added Value ◽  
Global Integration ◽  
Increase Production Efficiency ◽  
Agricultural Economy

In recent years, the rural agricultural economy in Vietnam has experienced outstanding shifting progress. The paper focuses on analyzing and evaluating an overview of the agricultural economy in Vietnam in the context of global climate change and global integration during industry 4.0. The results show that many advanced and modern models of association and cooperation which are effective in agriculture and rural areas have been applied to increase production efficiency. Science and technology applied to agriculture will increase the value of the agricultural sector in Vietnam. The innovations and prosperity of agricultural infrastructure combined with the implementation of the national scheme on restructuring agricultural sectors oriented to added value increase and sustainabe development will lead to a sustainable and climate adapted agriculture.

scholarly journals Implementing a Novel Use of Multicriteria Decision Analysis to Select IIoT Platforms for Smart Manufacturing

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 368 ◽  
Author(s):  
Roberto Contreras-Masse ◽  
Alberto Ochoa-Zezzatti ◽  
Vicente García ◽  
Luis Pérez-Dominguez ◽  
Mayra Elizondo-Cortés
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Smart Manufacturing ◽  
Industrial Internet Of Things ◽  
Single Product ◽  
Technical Aspects ◽  
Promethee Ii ◽  
Industrial Internet ◽  
Weight Calculation ◽  
Multi Criteria Analysis

Industry 4.0 is having a great impact in all smart efforts. This is not a single product but is composed of several technologies, one of them being Industrial Internet of Things (IIoT). Currently, there are very varied implementation options offered by several companies, and this imposes a new challenge to companies that want to implement IIoT in their processes. This challenge suggests using multi-criteria analysis to make a repeatable and justified decision, requiring a set of alternatives and criteria. This paper proposes a new methodology and comprehensive criteria to help organizations to take an educated decision by applying multi-criteria analysis. Here, we suggest a new original use of PROMETHEE-II with a full example from weight calculation up to IIoT platform selection, showing this methodology as an effective study for other organizations interested in selecting an IIoT platform. The criteria proposed stands out from previous work by including not only technical aspects, but economic and social criteria, providing a full view of the problem analyzed. A case of study was used to prove this proposed methodology and finds the minimum subset to reach the best possible ranking.

scholarly journals Implementing a Novel Use of Multicriteria Decision Analysis to Select IIoT Platforms for Smart Manufacturing

2020 ◽  
Author(s):  
Roberto Contreras-Masse ◽  
Alberto Ochoa-Zezzatti ◽  
Vicente García ◽  
Luis Perez-Dominguez ◽  
Mayra Elizondo
Keyword(s):  
Industry 4.0 ◽  
Smart Manufacturing ◽  
Industrial Internet Of Things ◽  
Single Product ◽  
Technical Aspects ◽  
Promethee Ii ◽  
Iot Platform ◽  
Industrial Internet ◽  
Weight Calculation ◽  
Multi Criteria Analysis

Industry 4.0 is having a great impact in all smart efforts. This is not a single product, but is composed of several technologies, being one of them Industrial Internet of Things (IIoT). Currently, there are very varied implementation options offered by several companies, and this imposes a new challenge to companies that want to implement IoT in their processes. This challenge suggests to use multi-criteria analysis to make a repeatable and justified decision, requiring a set of alternatives and criteria. This paper proposes a new methodology and comprehensive criteria to help organizations to take an educated decision by applying multi-criteria analysis. Here, we suggest a new original use of PROMETHEE-II with full example from weight calculation up to IoT platform selection, showing this methodology as an effective study for other organizations interested to select an IoT platform. The criteria proposed outstands from previous work by including not only technical aspects, but economic and social criteria, providing a full view of the problem analyzed. A case of study was used to prove this proposed methodology.

scholarly journals Implementation of Industry 4.0 Revolution through Skill Development– A Blessing for Local for Vocal in Covid-19 Pandemic

2021 ◽  
Vol 10 (7) ◽  
pp. 158-169
Author(s):  
Amlan Das*
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Skill Development ◽  
Smart Manufacturing ◽  
Cognitive Computing ◽  
Manufacturing Plants ◽  
Industrial Internet ◽  
Smart Factories ◽  
The Internet Of Things

We are amidst a noteworthy change with respect to the manner in which we make items, because of the digitization of assembling. This change is convincing to the point that it is being called Industry 4.0 to speak to the fourth insurgency that has happened in assembling. Industry 4.0 is flagging an adjustment in the conventional assembling scene. Otherwise called the Fourth Industrial Revolution, Industry 4.0 envelops three mechanical patterns driving this change: network, insight and adaptable robotization. Industry 4.0 portrays the developing pattern towards computerization and information trade in innovation and cycles inside the assembling business, including: The Internet of Things (IoT), The Industrial Internet of Things (IIoT), Cyber-physical Systems (CPS), Smart Manufacturing, Smart Factories, Cloud Computing, Additive Manufacturing, Big Data, Robotics, Cognitive Computing, Artificial Intelligence and Block chain and so forth. This mechanization makes an assembling framework whereby the machines in manufacturing plants are increased with remote network and sensors to screen and picture a whole creation cycle and settle on independent choices. In this paper we are worry about how aptitude and ability of human asset can be grown with the goal that we can conquer this pandemic circumstance effectively. Delicate abilities for taking care of these forthcoming new innovation inserted framework must be taken consideration and carefully instilled by human asset with the goal that simple smooth of efficiency just as hole crossing over of flexibly and request can be conceivable. Skill development should be considered as prioritizing factor for this.

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