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Journals
Processes
Special Issues
Digitalized Industrial Production Systems and Industry 4.0
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Digitalized Industrial Production Systems and Industry 4.0

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Advanced Digital and Other Processes".

Deadline for manuscript submissions: closed (15 November 2021) | Viewed by 60107

Special Issue Editor

Prof. Dr. José Barbosa

E-Mail Website
Guest Editor
Research Centre in Digitalization and Intelligent Robotics (CeDRI), Polytechnic Institute of Bragança, 5300-252 Bragança, Portugal
Interests: cyber-physical systems; internet of things; multi-agent systems; holonic manufacturing systems; self-organization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are currently running a Special Issue entitled “Digitalized Industrial Production Systems and Industry 4.0”, to be published in the open access journal Processes. The submission deadline is 15 May 2021, and papers may be submitted immediately or at any point until this deadline as papers will be published on an ongoing basis.

The present Special Issue aims to present up-to-date information on the recent scientific advances in the digitalization of industrial production systems and in the application of industry 4.0 concepts. Real applications of the present topics are highly encouraged, as they would greatly inspire future application of innovative research.

Papers dealing with the following topics are especially sought (although the Special Issue is not strictly limited to these):

  • Industrial CPS and smart manufacturing
  • Architecture design and analysis
  • Industrial IoT and factory of things and internet of things
  • Modeling and control for cyber-physical systems
  • Edge computing, fog computing, and IoT/IoE
  • Machine-to-machine (M2M)/device-to-device communications and IoT/IoE
  • Cloud-IoT/IoE cyber-physical systems
  • Cyber-physical system architectures
  • Human factors and humans in the loop in CPS
  • The role of CPS in industry 4.0
  • The role of IoT in industry 4.0
  • The role of industrial agents in industry 4.0
  • Design methodology, middlewares, principles, infrastructures, and tools for IIoT
  • Application of CPS in smart domains (e.g., manufacturing, agriculture, building, etc.)
  • Industrial applications of multi-agent systems
  • Industrial agents in industry

Prof. José Barbosa
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

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

  • digitalization
  • industry 4.0
  • internet of things
  • cyber-physical systems
  • multi-agent systems
  • digital twins

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (10 papers)

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Research

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27 pages, 2103 KiB  
Article
Digitalized Automation Engineering of Industry 4.0 Production Systems and Their Tight Cooperation with Digital Twins
by Petr Novák and Jiří Vyskočil
Processes 2022, 10(2), 404; https://doi.org/10.3390/pr10020404 - 18 Feb 2022
Cited by 19 | Viewed by 5458
Abstract
Smart production systems conforming the Industry 4.0 vision are based on subsystems that are integrated in a way that supports high flexibility and re-configurability. Specific components and devices, such as industrial and mobile robots or transport systems, now pose full-blown systems, and the [...] Read more.
Smart production systems conforming the Industry 4.0 vision are based on subsystems that are integrated in a way that supports high flexibility and re-configurability. Specific components and devices, such as industrial and mobile robots or transport systems, now pose full-blown systems, and the entire Industry 4.0 production system constitutes a system-of-systems. Testing, fine-tuning, and production planning are important tasks in the entire engineering production system life-cycle. All these steps can be significantly supported and improved by digital twins, which are digitalized replicas of physical systems that are synchronized with the real systems at runtime. However, the design and implementation of digital twins for such integrated, yet partly stand-alone, industrial sub-systems can represent challenging and significantly time-consuming engineering tasks. In this article, the problem of the digital twin design for discrete-event production systems is addressed. The article also proposes to utilize a formal description of production resources and related production operations that the resources can perform. An executable version of such formalization can be automatically derived into a form of a digital twin. Such a derived digital twin can be enhanced with operation duration times that are obtained with process mining methods, leading to more realistic simulations for the entire production system. The proposed solution was successfully tested and validated in the Industry 4.0 Testbed, equipped with four robots and a transport system, which is utilized as a use-case in this article. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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21 pages, 4017 KiB  
Article
An Enabling Open-Source Technology for Development and Prototyping of Production Systems by Applying Digital Twinning
by Robert Kazała, Sławomir Luściński, Paweł Strączyński and Albena Taneva
Processes 2022, 10(1), 21; https://doi.org/10.3390/pr10010021 - 23 Dec 2021
Cited by 6 | Viewed by 3869
Abstract
This article presents the most valuable and applicable open-source tools and communication technologies that may be employed to create models of production processes by applying the concept of Digital Twins. In recent years, many open-source technologies, including tools and protocols, have been developed [...] Read more.
This article presents the most valuable and applicable open-source tools and communication technologies that may be employed to create models of production processes by applying the concept of Digital Twins. In recent years, many open-source technologies, including tools and protocols, have been developed to create virtual models of production systems. The authors present the evolution and role of the Digital Twin concept as one of the key technologies for implementing the Industry 4.0 paradigm in automation and control. Based on the presented structured review of valuable open-source software dedicated to various phases and tasks that should be realised while creating the whole Digital Twin system, it was demonstrated that the available solutions cover all aspects. However, the dispersion, specialisation, and lack of integration cause this software to usually not be the first choice to implement DT. Therefore, to successfully create full-fledged models of Digital Twins by proceeding with proposed open-source solutions, it is necessary to make additional efforts due to integration requirements. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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23 pages, 28408 KiB  
Article
Value Configurations for Data and Connectivity Solutions in Digitalized Future Factories
by Solmaz Mansoori, Iqra Sadaf Khan, Petri Ahokangas, Marja Matinmikko-Blue, Harri Haapasalo and Seppo Yrjölä
Processes 2021, 9(12), 2233; https://doi.org/10.3390/pr9122233 - 11 Dec 2021
Cited by 1 | Viewed by 3040
Abstract
The ongoing Industry 4.0 transformation places significant pressures on how businesses create and capture value. Technological advancements such as next-generation mobile communications are reshaping the business ecosystem of Industry 4.0, resulting in emerging business opportunities for new players, such as local operators, to [...] Read more.
The ongoing Industry 4.0 transformation places significant pressures on how businesses create and capture value. Technological advancements such as next-generation mobile communications are reshaping the business ecosystem of Industry 4.0, resulting in emerging business opportunities for new players, such as local operators, to collaborate and compete with mobile communications companies that are implementing I4.0. These changes raise the need to explore emerging business opportunities concerning the digitalization of future factories. New data and connectivity services are introduced to serve the needs of rapidly increasing machine-type communications that rely on connectivity, primarily through the fifth generation (5G) mobile solutions provided by local operators. Thus, this paper outlines the potential value configurations for data and connectivity solutions by identifying, matching, and bridging the utilizable resources and addressable needs within the factory processes. The research applies an exploratory approach and uses the Gioia method to analyze qualitative data of a single case. The study follows the connectivity-content-context-commerce typology (4C) of Internet business models to structure, analyze, and classify the identified needs and resources in future factories from the perspective of the local operator. The findings show that the content layer of 4C business model typology is the most dominant among data and connectivity-based needs and resources of future factories. The paper contributes by presenting four alternative value configurations for digitalization for local operators in the future factory context: the product, component, platform, and complementary businesses. The results suggest content- and context-specific businesses carries foremost business potential for local operators, however quantitative validation will bring fruitful research avenues. Multiple case studies and different data collection methods may also be considered in future studies. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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25 pages, 2511 KiB  
Article
An Effective Communication Prototype for Time-Critical IIoT Manufacturing Factories Using Zero-Loss Redundancy Protocols, Time-Sensitive Networking, and Edge-Computing in an Industry 4.0 Environment
by Kahiomba Sonia Kiangala and Zenghui Wang
Processes 2021, 9(11), 2084; https://doi.org/10.3390/pr9112084 - 21 Nov 2021
Cited by 11 | Viewed by 3832
Abstract
The Industrial Internet of things (IIoT), the implementation of IoT in the industrial sector, requires a deterministic, real-time, and low-latency communication response for its time-critical applications. A delayed response in such applications could be life-threatening or result in significant losses for manufacturing plants. [...] Read more.
The Industrial Internet of things (IIoT), the implementation of IoT in the industrial sector, requires a deterministic, real-time, and low-latency communication response for its time-critical applications. A delayed response in such applications could be life-threatening or result in significant losses for manufacturing plants. Although several measures in the likes of predictive maintenance are being put in place to prevent errors and guarantee high network availability, unforeseen failures of physical components are almost inevitable. Our research contribution is to design an efficient communication prototype, entirely based on internet protocol (IP) that combines state-of-the-art communication computing technologies principles to deliver a more stable industrial communication network. We use time-sensitive networking (TSN) and edge computing to increase the determinism of IIoT networks, and we reduce latency with zero-loss redundancy protocols that ensure the sustainability of IIoT networks with smooth recovery in case of unplanned outages. Combining these technologies altogether brings more effectiveness to communication networks than implementing standalone systems. Our study results develop two experimental IP-based industrial network communication prototypes in an intra-domain transmission scenario: the first one is based on the parallel zero-loss redundancy protocol (PRP) and the second one using the high-availability seamless zero-loss redundancy protocol (HSR). We also highlight the benefits of utilizing our communication prototypes to build robust industrial IP communication networks with high network availability and low latency as opposed to conventional communication networks running on seldom redundancy protocols such as Media Redundancy Protocol (MRP) or Rapid Spanning Tree Protocol (RSTP) with single-point of failure and delayed recovery time. While our two network communication prototypes—HSR and PRP—offer zero-loss recovery time in case of a single network failure, our PRP communication prototype goes a step further by providing an effective redundancy scheme against multiple link failures. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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18 pages, 3477 KiB  
Article
Concept and Case Study for a Generic Simulation as a Digital Shadow to Be Used for Production Optimisation
by Stefan Kassen, Holger Tammen, Maximilian Zarte and Agnes Pechmann
Processes 2021, 9(8), 1362; https://doi.org/10.3390/pr9081362 - 3 Aug 2021
Cited by 13 | Viewed by 5080
Abstract
Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production [...] Read more.
Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production systems are in line with the call of Industry 4.0 for substantial and frequent changes. Creating simulation models for those systems requires high effort and in-depth knowledge of production processes. In the current literature, digital twins promise several advantages for production optimisation and can be used to simulate production systems, which reduce necessary physical test runs and related costs. While most companies are not able to create digital twins yet, companies using enterprise resource planning (ERP) systems have the general capability to create digital shadows. This paper presents a concept and a case study for a generic simulation of production systems in AnyLogic™ to create digital shadows as the first step towards a full digital twin. The generic simulation visualises production systems automatically and displays key performance indicators (KPIs) for the planned production program, using representational state transfer (REST) interfaces to extract product and production data from an ERP system. The case study has been applied in a learning factory of the University of Applied Life Sciences Emden/Leer. The results prove the presented concept of the generic simulation and show the limits and challenges of working with generic simulation models. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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13 pages, 3238 KiB  
Article
The Use of a Genetic Algorithm for Sorting Warehouse Optimisation
by Patrik Grznár, Martin Krajčovič, Arkadiusz Gola, Ľuboslav Dulina, Beáta Furmannová, Štefan Mozol, Dariusz Plinta, Natália Burganová, Wojciech Danilczuk and Radovan Svitek
Processes 2021, 9(7), 1197; https://doi.org/10.3390/pr9071197 - 10 Jul 2021
Cited by 26 | Viewed by 5005
Abstract
In the last decade, simulation software as a tool for managing and controlling business processes has received a lot of attention. Many of the new software features allow businesses to achieve better quality results using optimisation, such as genetic algorithms. This article describes [...] Read more.
In the last decade, simulation software as a tool for managing and controlling business processes has received a lot of attention. Many of the new software features allow businesses to achieve better quality results using optimisation, such as genetic algorithms. This article describes the use of modelling and simulation in shipment and sorting processes that are optimised by a genetic algorithm’s involvement. The designed algorithm and simulation model focuses on optimising the duration of shipment processing times and numbers of workers. The commercially available software Tecnomatix Plant Simulation, paired with a genetic algorithm, was used for optimisation, decreasing time durations, and thus selecting the most suitable solution for defined inputs. This method has produced better results in comparison to the classical heuristic methods and, furthermore, is not as time consuming. This article, at its core, describes the algorithm used to determine the optimal number of workers in sorting warehouses with the results of its application. The final part of this article contains an evaluation of this proposal compared to the original methods, and highlights what benefits result from such changes. The major purpose of this research is to determine the number of workers needed to speed up the departure of shipments and optimise the workload of workers. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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16 pages, 12578 KiB  
Article
Implementation of an Automated Manufacturing Process for Smart Clothing: The Case Study of a Smart Sports Bra
by Suhyun Lee, Soo Hyeon Rho, Sojung Lee, Jiwoong Lee, Sang Won Lee, Daeyoung Lim and Wonyoung Jeong
Processes 2021, 9(2), 289; https://doi.org/10.3390/pr9020289 - 2 Feb 2021
Cited by 29 | Viewed by 8879
Abstract
The garment manufacturing industry is a labor-intensive industry, with one of the slowest transitions to automation. Hence, it is essential to build a smart factory based on automated systems to improve productivity and allow responsive production in the market. In this study, the [...] Read more.
The garment manufacturing industry is a labor-intensive industry, with one of the slowest transitions to automation. Hence, it is essential to build a smart factory based on automated systems to improve productivity and allow responsive production in the market. In this study, the manufacturing processes for a smart sports bra were established and optimized using various automated machines. For this system, computer-based 3D virtual design software, a technical embroidery machine, an automatic cutting machine, an industrial robot arm with gripper, and an industrial pattern sewing machine were used. The design and materials of the sports bra were selected considering embroidery, cutting, robot gripping, and sewing processes. In addition, conductive thread and light-emitting diode (LED) sequences were used to implement smart functions to the sports bra. Transport of intermediate materials, work orders, and process conditions were optimized to improve the flexible connection of each process and the quality of the final product. This study suggests the concept of the automated manufacturing system that minimizes human intervention by connecting the processes needed to produce a smart sports bra using various automation equipment and programs already used in the industry. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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18 pages, 572 KiB  
Article
Qualitative Analysis of the Perception of Company Managers in Knowledge Management in the Maintenance Activity in the Era of Industry 4.0
by Javier Cárcel-Carrasco and Consuelo Gómez-Gómez
Processes 2021, 9(1), 121; https://doi.org/10.3390/pr9010121 - 8 Jan 2021
Cited by 26 | Viewed by 4095
Abstract
In industrial maintenance activity, very sophisticated technical and human factors are needed to achieve the great process or service that the company provides, with a large dose of knowledge based on the personal experience of maintenance technicians. However, the management and application of [...] Read more.
In industrial maintenance activity, very sophisticated technical and human factors are needed to achieve the great process or service that the company provides, with a large dose of knowledge based on the personal experience of maintenance technicians. However, the management and application of knowledge in this activity is often relegated to a third level (or simply forgotten). The aim of this study is to identify, classify and prioritize the different barriers and facilitators that can be found in maintenance organizations of the company in reference to knowledge management in strategic maintenance activities, and what competitive advantages could be used for their appropriate introduction in the company. For this, qualitative techniques have been used through a field study and observation, as well as semi-structured interviews between company directors and maintenance managers of first-level companies in various sectors (industrial or services), to draw conclusions on the application of knowledge management techniques which help to determine the principles of a company that wants to face a knowledge management project within the area of maintenance engineering. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)

Review

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12 pages, 1011 KiB  
Review
Digital Twin Applications: A Survey of Recent Advances and Challenges
by Rafael da Silva Mendonça, Sidney de Oliveira Lins, Iury Valente de Bessa, Florindo Antônio de Carvalho Ayres, Jr., Renan Landau Paiva de Medeiros and Vicente Ferreira de Lucena, Jr.
Processes 2022, 10(4), 744; https://doi.org/10.3390/pr10040744 - 12 Apr 2022
Cited by 43 | Viewed by 7498
Abstract
Industry 4.0 integrates a series of emerging technologies, such as the Internet of Things (IoT), cyber-physical systems (CPS), cloud computing, and big data, and aims to improve operational efficiency and accelerate productivity inside the industrial environment. This article provides a series of information [...] Read more.
Industry 4.0 integrates a series of emerging technologies, such as the Internet of Things (IoT), cyber-physical systems (CPS), cloud computing, and big data, and aims to improve operational efficiency and accelerate productivity inside the industrial environment. This article provides a series of information about the required structure to adopt Industry 4.0 approaches and a brief review of related concepts to finally identify challenges and research opportunities to envision the adoption of so-called digital twins. We want to pay attention to upgrading older systems aiming to provide the well-known advantages of Industry 4.0 to such legacy systems as reducing production costs, increasing efficiency, acquiring better robustness of equipment, and reaching advanced process connectivity. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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29 pages, 1888 KiB  
Review
Modelling for Digital Twins—Potential Role of Surrogate Models
by Ágnes Bárkányi, Tibor Chován, Sándor Németh and János Abonyi
Processes 2021, 9(3), 476; https://doi.org/10.3390/pr9030476 - 7 Mar 2021
Cited by 67 | Viewed by 10794
Abstract
The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin applications and to explore the fields where [...] Read more.
The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin applications and to explore the fields where surrogate models can be utilised advantageously. In this sense, the paper discusses what types of surrogate models are suitable for different practical problems as well as introduces the appropriate techniques for building and using these models. A number of examples of digital twin applications from both continuous processes and discrete manufacturing are presented to underline the potentials of utilising surrogate models. The surrogate models and model-building methods are categorised according to the area of applications. The importance of keeping these models up to date through their whole model life cycle is also highlighted. An industrial case study is also presented to demonstrate the applicability of the concept. Full article
(This article belongs to the Special Issue Digitalized Industrial Production Systems and Industry 4.0)
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