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Information and Communications Technology for Industry 4.0
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Information and Communications Technology for Industry 4.0

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (20 September 2021) | Viewed by 29935

Special Issue Editor

Dr. Silvio Abrate

E-Mail Website
Guest Editor
Head of Industry 4.0, LINKS Foundation, Via P. C. Boggio 61, 10138 Torino, Italy
Interests: optical communications; telecommunications networks

Special Issue Information

Dear Colleagues,

More and more, information and communication technologies play a key role in modern industries. The ability to gather huge amounts of data in the full lifecycle of a product or in a production line enables new and more efficient processes in industries, and the provision of added-value services to customers. The complete adoption of the so-called Industry 4.0 paradigm requires a conscious introduction of several technologies: IoT, cloud computing, artificial intelligence, cyber-security, localization, augmented reality, inspection systems, etc. Therefore, the full OSI stack, from physical to application layer, is involved.

This Special Issue is focused on innovative ICT solutions specifically designed for industrial applications.

Dr. Silvio Abrate
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • IoT
  • cyber-physical systems
  • artificial intelligence
  • data science
  • cyber-security
  • communications
  • localization technologies
  • augmented reality
  • industrial automation

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Published Papers (7 papers)

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Research

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17 pages, 11721 KiB  
Article
Framework for Developing an Information Technology Maturity Model for Smart City Services in Emerging Economies: (FSCE2)
by Wilson Nieto Bernal and Keryn Lorena García Espitaleta
Appl. Sci. 2021, 11(22), 10712; https://doi.org/10.3390/app112210712 - 13 Nov 2021
Cited by 6 | Viewed by 4962
Abstract
The goal of this research is to design a framework to develop an information technology (IT) maturity model to guide the planning, design, and implementation of smart city services. The objectives of the proposed model are to define qualitatively and measure quantitatively the [...] Read more.
The goal of this research is to design a framework to develop an information technology (IT) maturity model to guide the planning, design, and implementation of smart city services. The objectives of the proposed model are to define qualitatively and measure quantitatively the maturity levels for the IT dimensions used by smart cities (IT governance, IT services, data management and infrastructure), and to develop an implementation model that is practical and contextualized to the needs of any territory that wants to create or improve smart city services. The proposed framework consists of three components: a conceptual model of smart city services, IT dimensions and indicators, and IT maturity levels. The framework was validated by applying it to a case study for the evaluation of the IT maturity levels for the city of Cereté, Colombia. Full article
(This article belongs to the Special Issue Information and Communications Technology for Industry 4.0)
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22 pages, 4237 KiB  
Article
Cloud-Based Analytics Module for Predictive Maintenance of the Textile Manufacturing Process
by Ray-I Chang, Chia-Yun Lee and Yu-Hsin Hung
Appl. Sci. 2021, 11(21), 9945; https://doi.org/10.3390/app11219945 - 25 Oct 2021
Cited by 19 | Viewed by 4546
Abstract
Industry 4.0 has remarkably transformed many industries. Supervisory control and data acquisition (SCADA) architecture is important to enable an intelligent and connected manufacturing factory. SCADA is extensively used in many Internet of Things (IoT) applications, including data analytics and data visualization. Product quality [...] Read more.
Industry 4.0 has remarkably transformed many industries. Supervisory control and data acquisition (SCADA) architecture is important to enable an intelligent and connected manufacturing factory. SCADA is extensively used in many Internet of Things (IoT) applications, including data analytics and data visualization. Product quality management is important across most manufacturing industries. In this study, we extensively used SCADA to develop a cloud-based analytics module for production quality predictive maintenance (PdM) in Industry 4.0, thus targeting textile manufacturing processes. The proposed module incorporates a complete knowledge discovery in database process. Machine learning algorithms were employed to analyze preprocessed data and provide predictive suggestions for production quality management. Equipment data were analyzed using the proposed system with an average mean-squared error of ~0.0005. The trained module was implemented as an application programming interface for use in IoT applications and third-party systems. This study provides a basis for improving production quality by predicting optimized equipment settings in manufacturing processes in the textile industry. Full article
(This article belongs to the Special Issue Information and Communications Technology for Industry 4.0)
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16 pages, 3763 KiB  
Article
Relational Positioning Method for 2D and 3D Ad Hoc Sensor Networks in Industry 4.0
by Rafaela Villalpando-Hernandez, David Munoz-Rodriguez and Cesar Vargas-Rosales
Appl. Sci. 2021, 11(19), 8907; https://doi.org/10.3390/app11198907 - 24 Sep 2021
Cited by 2 | Viewed by 1895
Abstract
Industry 4.0, or smart factory, refers to the fourth industrial revolution, as a result of which it is expected that massive sensor deployment, high device connectivity, automation, and real-time data acquisition support improve industrial processes. Sensor fault detection and operator tracking allow adequate [...] Read more.
Industry 4.0, or smart factory, refers to the fourth industrial revolution, as a result of which it is expected that massive sensor deployment, high device connectivity, automation, and real-time data acquisition support improve industrial processes. Sensor fault detection and operator tracking allow adequate performance of the sensor network supporting Industry 4.0, and sensor localization has become crucial to enable sensor fault detection. Hence, the development of new localization methods is necessary for environments where GPS localization technology is unfeasible. Furthermore, position location information (PLI) is a crucial requirement for the deployment of multiple services and applications in wireless ad hoc and sensor networks supporting Industry 4.0. Three-dimensional (3D) scenarios are considered to extend the applicability of PLI-based services. However, PLI acquisition presents several challenges within any 3D ad hoc sensor network paradigm. For instance, conventional triangulation algorithms are often no longer applicable due to the lack of direct land-fixed references and the inclusion of a third-dimension coordinate. In this paper, a PL relational searching algorithm suitable for 2D and 3D ad hoc environments was formulated in terms of a discretized searching space and a vertex weight assignment process according to distance relationships from anchor nodes to the node to be located on a feasibility space. The applicability of the proposed algorithm was examined through analytic formulation and simulation processes. Results show small distance errors (less than 1 m) are achievable for some scenarios. Full article
(This article belongs to the Special Issue Information and Communications Technology for Industry 4.0)
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18 pages, 3373 KiB  
Article
Trusted GNSS-Based Time Synchronization for Industry 4.0 Applications
by Davide Margaria and Andrea Vesco
Appl. Sci. 2021, 11(18), 8288; https://doi.org/10.3390/app11188288 - 7 Sep 2021
Cited by 5 | Viewed by 5906
Abstract
The protection of satellite-derived timing information is becoming a fundamental requirement in Industry 4.0 applications, as well as in a growing number of critical infrastructures. All the industrial systems where several nodes or devices communicate and/or coordinate their functionalities by means of a [...] Read more.
The protection of satellite-derived timing information is becoming a fundamental requirement in Industry 4.0 applications, as well as in a growing number of critical infrastructures. All the industrial systems where several nodes or devices communicate and/or coordinate their functionalities by means of a communication network need accurate, reliable and trusted time synchronization. For instance, the correct operation of automation and control systems, measurement and automatic test systems, power generation, transmission, and distribution typically require a sub-microsecond time accuracy. This paper analyses the main attack vectors and stresses the need for software integrity control at network nodes of Industry 4.0 applications to complement existing security solutions that focus on Global Navigation Satellite System (GNSS) radio-frequency spectrum and Precision Time Protocol (PTP), also known as IEEE-1588. A real implementation of a Software Integrity Architecture in accordance with Trusted Computing principles concludes the work, together with the presentation of promising results obtained with a flexible and reconfigurable testbed for hands-on activities. Full article
(This article belongs to the Special Issue Information and Communications Technology for Industry 4.0)
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25 pages, 3331 KiB  
Article
Towards a Flexible Smart Factory with a Dynamic Resource Orchestration
by Milan Pisarić, Vladimir Dimitrieski, Marko Vještica, Goran Krajoski and Mirna Kapetina
Appl. Sci. 2021, 11(17), 7956; https://doi.org/10.3390/app11177956 - 28 Aug 2021
Cited by 4 | Viewed by 2772
Abstract
Amid the current industrial revolution, a total disruption of the existing production lines may seem to be the easiest approach, as the potential possibilities seem limitless when starting from the ground up. On the business side, an adaptation of existing production lines is [...] Read more.
Amid the current industrial revolution, a total disruption of the existing production lines may seem to be the easiest approach, as the potential possibilities seem limitless when starting from the ground up. On the business side, an adaptation of existing production lines is always a preferred option. In support of adaptation as opposed to disruption, this paper presents a new approach of using production process orchestration in a smart factory, discussed in an industrial case-study example. A proposed smart factory has the Orchestrator component in its core, responsible for complete semantical orchestration of production processes on one hand, and various factory resources on the other hand, in order to produce the desired product. The Orchestrator is a complex, modular, highly scalable, and pluggable software product responsible for automatised planning, scheduling, and execution of the complete production process. According to their offered capabilities, non-smart and smart resources—machines, robots, humans—are simultaneously and dynamically assigned to execute their dedicated production steps. Full article
(This article belongs to the Special Issue Information and Communications Technology for Industry 4.0)
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15 pages, 569 KiB  
Article
Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0
by Radhya Sahal, Saeed H. Alsamhi, John G. Breslin, Kenneth N. Brown and Muhammad Intizar Ali
Appl. Sci. 2021, 11(7), 3186; https://doi.org/10.3390/app11073186 - 2 Apr 2021
Cited by 37 | Viewed by 4978
Abstract
Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that [...] Read more.
Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry. Full article
(This article belongs to the Special Issue Information and Communications Technology for Industry 4.0)
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Review

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18 pages, 2768 KiB  
Review
A Systematic Literature Review of Successful Implementation of Industry 4.0 Technologies in Companies: Synthesis of the IPSI Framework
by Olivier Cardin
Appl. Sci. 2021, 11(19), 8917; https://doi.org/10.3390/app11198917 - 24 Sep 2021
Cited by 3 | Viewed by 2687
Abstract
The Industry 4.0 paradigm refers to a large set of technologies that will transform the way that the manufacturing industry will perform. Nowadays, those technologies and the potential benefits they offer are not fully understood and mastered by companies, and the propagation of [...] Read more.
The Industry 4.0 paradigm refers to a large set of technologies that will transform the way that the manufacturing industry will perform. Nowadays, those technologies and the potential benefits they offer are not fully understood and mastered by companies, and the propagation of the associated concepts is slow. However, in the past few years, some successful implementations of Industry 4.0-compliant technologies have been seen emerging in the literature. A systematic literature study has been conducted to identify the suggested methodologies for successful implementations. Following this analysis, identified patterns are synthesized as an implementation framework denoted as IPSI (Identification–Preparation–Simulation–Implementation). This framework was synthesized so as to be used for the first implementation of technologies in a company, thus increasing the chances of acceptability of those technologies. Three case studies, concerning three different technologies in three different manufacturing fields, were chosen to be confronted by the framework and its validity on the global manufacturing field is discussed. Full article
(This article belongs to the Special Issue Information and Communications Technology for Industry 4.0)
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