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Applied Sciences
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Lifecycle and Supply Chain Optimization in Industry 4.0
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Lifecycle and Supply Chain Optimization in Industry 4.0

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 25951

Special Issue Editors

Dr. Pal Varga

E-Mail Website
Guest Editor
Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, 2 Magyar Tudósok krt., H-1117 Budapest, Hungary
Interests: IoT; CPS; Industry 4.0; interoperability; wireless communication; monitoring; performance evaluation; QoS; 5G; artificial intelligence; deep learning
Special Issues, Collections and Topics in MDPI journals
Dr. Daniel Kozma

E-Mail Website
Guest Editor
Department of Telecommunications and Media Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, 2, Magyar Tudosok krt., 1117 Budapest, Hungary
Interests: Industry 4.0; automated production; workflow management; supply chain management; lifecycle management; information security; IoT
Prof. Dr. Felix Larrinaga

E-Mail Website
Guest Editor
Software and System Engineering, Electronics and Computer Science Department, Faculty of Engineering, Mondragon University, Loramendi 4, 20500 Arrasate-Mondragon, Spain
Interests: IoT; Industry 4.0; interoperability; automated production; workflow management; lifecycle management

Special Issue Information

Dear Colleagues,

Industry 4.0 has fundamentally reformed manufacturing processes, resulting in much more efficient production and supply chain management than ever before. However, in addition to automatized industrial processes, digitalization has brought about great changes in many other related areas. One of these major fields is lifecycle management. It can be observed that the previous models have transformed or evolved, with some new management models also appearing, according to the specific needs of a given area. In addition to traditional product lifecycle management, service lifecycle management also plays an important role because of service-oriented Industry 4.0. The lifecycle management of software, applications, information, and systems is also continuously changing.

With adequate lifecycle management within various parts of the supply chain, it is evident that more transparent and efficient production can be achieved. Monitoring all of the elements of a smart factory can allow for proactive maintenance and production optimization; furthermore, advanced product lifecycle management can raise the user experience and can lead to greater customer satisfaction. This Special Issue aims to gather work related to supply chain and lifecycle management in general, especially in the aspect of Industry 4.0. Original and survey papers analyzing state-of-the-art in the area are also welcome. Reports on applications of existing models are interesting, as well as scientific achievements on the changes in current lifecycle management models, whether it is a change within a given model or possibly a description of how several lifecycle models can work together to achieve better lifecycle management. Furthermore, of course, it is particularly interesting to introduce research that presents new lifecycle models that did not exist before and were created to meet the changing needs brought about by Industry 4.0.

Prof. Dr. Pal Varga
Dr. Daniel Kozma
Prof. Dr. Felix Larrinaga
Guest Editors

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

  • Industry 4.0
  • lifecycle models
  • lifecycle management
  • supply chain management
  • asset tracking
  • blockchains
  • configuration management
  • workflow management
  • process management
  • engineering toolchains
  • industrial IoT applications
  • practical application results on lifecycle models

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Published Papers (6 papers)

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Research

22 pages, 7103 KiB  
Article
A SOA-Based Engineering Process Model for the Life Cycle Management of System-of-Systems in Industry 4.0
by Gianvito Urgese, Paolo Azzoni, Jan van Deventer, Jerker Delsing, Alberto Macii and Enrico Macii
Appl. Sci. 2022, 12(15), 7730; https://doi.org/10.3390/app12157730 - 1 Aug 2022
Cited by 2 | Viewed by 2603
Abstract
The evolution of industrial digitalisation has accelerated in recent years with the availability of hyperconnectivity, low-cost miniaturised electronic components, edge computing, and Internet of Things (IoT) technologies. More generally, with these key enablers, the concept of a system of systems (SoS) is becoming [...] Read more.
The evolution of industrial digitalisation has accelerated in recent years with the availability of hyperconnectivity, low-cost miniaturised electronic components, edge computing, and Internet of Things (IoT) technologies. More generally, with these key enablers, the concept of a system of systems (SoS) is becoming a reality in the industry domain. However, due to its complexity, the engineering process model adopted to design, develop, and manage IoT and SoS-based solutions for industry digitalisation is inadequate, inefficient, and frequently unable to manage the digitalisation solution’s entire life cycle. To address these limitations, we propose the Arrowhead Engineering Process (Arrowhead-EP) model and the Value Chain Engineering Process Map (VCEP-map), which explicitly reveal the interactions and dynamics of the engineering processes adopted by multistakeholder use cases in the industry domain. We decomposed and remodeled the engineering process to cover the complete life cycle of an industrial SoS, and we introduced a service-oriented solution intended to efficiently, flexibly, and effectively manage the three assets addressed by RAMI 4.0. The Arrowhead-EP model complemented by the VCEP-map fills the gaps identified in our literature-based analysis and satisfies the requirements of the life cycle management of a typical use case in the Industry 4.0 domain. In this regard, a specific example is used to illustrate the advantages of adopting the proposed engineering solution in a real multistakeholder use case. Full article
(This article belongs to the Special Issue Lifecycle and Supply Chain Optimization in Industry 4.0)
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44 pages, 3020 KiB  
Article
Converging Telco-Grade Solutions 5G and beyond to Support Production in Industry 4.0
by Pal Varga, Sándor Bácsi, Ravi Sharma, Abdulhalim Fayad, Ali Raheem Mandeel, Gabor Soos, Attila Franko, Tibor Fegyo and Dániel Ficzere
Appl. Sci. 2022, 12(15), 7600; https://doi.org/10.3390/app12157600 - 28 Jul 2022
Cited by 10 | Viewed by 4991
Abstract
The Industry 4.0 initiative has been showing the way for industrial production to optimize operations based on collecting, processing, and sharing data. There are new requirements on the production floor: flexible but ultra-reliable, low latency wireless communications through interoperable systems can share data. [...] Read more.
The Industry 4.0 initiative has been showing the way for industrial production to optimize operations based on collecting, processing, and sharing data. There are new requirements on the production floor: flexible but ultra-reliable, low latency wireless communications through interoperable systems can share data. Further challenges of data sharing and storage arise when diverse systems come into play at the Manufacturing Operations Management and Business Planning & Logistics levels. The emerging complex cyber-physical systems of systems need to be engineered with care. Regarding industrial requirements, the telecommunication industry has many similarities to production—including ultra-reliability, high complexity, and having humans “in-the-loop”. The current paper aims to provide an overview of converging telco-grade solutions that can be successfully applied in the wide sense of industrial production. These toolsets range from model-driven engineering through system interoperability frameworks, 5G- and 6G-supported manufacturing, and the telco-cloud to speech recognition in noisy environments. Full article
(This article belongs to the Special Issue Lifecycle and Supply Chain Optimization in Industry 4.0)
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23 pages, 556 KiB  
Article
JSON Schemas with Semantic Annotations Supporting Data Translation
by Gonçalo Amaro, Filipe Moutinho, Rogério Campos-Rebelo, Julius Köpke and Pedro Maló
Appl. Sci. 2021, 11(24), 11978; https://doi.org/10.3390/app112411978 - 16 Dec 2021
Cited by 3 | Viewed by 4551
Abstract
As service-oriented architectures are a solution for large distributed systems, interoperability between these systems, which are often heterogeneous, can be a challenge due to the different syntax and semantics of the exchanged messages or even different data interchange formats. This paper addresses the [...] Read more.
As service-oriented architectures are a solution for large distributed systems, interoperability between these systems, which are often heterogeneous, can be a challenge due to the different syntax and semantics of the exchanged messages or even different data interchange formats. This paper addresses the data interchange format and data interoperability issues between XML-based and JSON-based systems. It proposes novel annotation mechanisms to add semantic annotations and complement date values to JSON Schemas, enabling an interoperability approach for JSON-based systems that, until now, was only possible for XML-based systems. A set of algorithms supporting the translation from JSON Schema to XML Schema, JSON to XML, and XML to JSON is also proposed. These algorithms were implemented in an existing prototype tool, which now supports these systems’ interoperability through semantic compatibility verification and the automatic generation of translators. Full article
(This article belongs to the Special Issue Lifecycle and Supply Chain Optimization in Industry 4.0)
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16 pages, 603 KiB  
Article
Matheuristics for the Design of a Multi-Step, Multi-Product Supply Chain with Multimodal Transport
by David A. Ruvalcaba-Sandoval, Elias Olivares-Benitez, Omar Rojas and Guillermo Sosa-Gómez
Appl. Sci. 2021, 11(21), 10251; https://doi.org/10.3390/app112110251 - 1 Nov 2021
Cited by 4 | Viewed by 2555
Abstract
Supply-chain network design is a complex task because there are many decisions involved, and presently, global networks involve many actors and variables, for example, in the automotive, pharmaceutical, and electronics industries. This research addresses a supply-chain network design problem with four levels: suppliers, [...] Read more.
Supply-chain network design is a complex task because there are many decisions involved, and presently, global networks involve many actors and variables, for example, in the automotive, pharmaceutical, and electronics industries. This research addresses a supply-chain network design problem with four levels: suppliers, factories, warehouses, and customers. The problem considered decides on the number, locations, and capacities of factories and warehouses and the transportation between levels in the supply chain. The problem is modeled as a mixed-integer linear program. The main contribution of this work is the proposal of two matheuristic algorithms to solve the problem. Matheuristics are algorithms that combine exact methods and heuristics, attracting interest in the literature because of their fast execution and high-quality solutions. The matheuristics proposed to select the warehouses and their capacities following heuristic rules. Once the warehouses and their capacities are fixed, the algorithms solve reduced models using commercial optimization software. Medium and large instances were generated based on a procedure described in the literature. A comparison is made between the algorithms and the results obtained, solving the model with a time limit. The algorithms proposed are successful in obtaining better results for the largest instances in shorter execution times. Full article
(This article belongs to the Special Issue Lifecycle and Supply Chain Optimization in Industry 4.0)
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20 pages, 739 KiB  
Article
An Integrated Model for the Harvest, Storage, and Distribution of Perishable Crops
by Giovanni Giallombardo, Giovanni Mirabelli and Vittorio Solina
Appl. Sci. 2021, 11(15), 6855; https://doi.org/10.3390/app11156855 - 26 Jul 2021
Cited by 12 | Viewed by 2898
Abstract
Coordination of the production and distribution activities represents a significant opportunity to cut costs and limit waste in the food supply chains. In this paper, we propose two mathematical models. The first one aims to integrate the harvesting, storage, and distribution activities of [...] Read more.
Coordination of the production and distribution activities represents a significant opportunity to cut costs and limit waste in the food supply chains. In this paper, we propose two mathematical models. The first one aims to integrate the harvesting, storage, and distribution activities of an agricultural company dealing with perishable products. The second one promotes horizontal collaboration between heterogeneous agri-companies for the distribution phase, in order to achieve cost savings. Computational experiments, conducted on a set of real-life instances, confirm the effectiveness and efficiency of the proposed models, which provide multi-level support. At the tactical level, managerial insights suggest the most profitable parameter setting, in terms of harvesting frequency and quality of service. At the operational level, the use of a heuristic framework can support the decision-making of the companies, suggesting when collaboration is profitable. Full article
(This article belongs to the Special Issue Lifecycle and Supply Chain Optimization in Industry 4.0)
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29 pages, 1142 KiB  
Article
System of Systems Lifecycle Management—A New Concept Based on Process Engineering Methodologies
by Dániel Kozma, Pál Varga and Felix Larrinaga
Appl. Sci. 2021, 11(8), 3386; https://doi.org/10.3390/app11083386 - 9 Apr 2021
Cited by 13 | Viewed by 7090
Abstract
In order to tackle interoperability issues of large-scale automation systems, SOA (Service-Oriented Architecture) principles, where information exchange is manifested by systems providing and consuming services, have already been introduced. However, the deployment, operation, and maintenance of an extensive SoS (System of Systems) mean [...] Read more.
In order to tackle interoperability issues of large-scale automation systems, SOA (Service-Oriented Architecture) principles, where information exchange is manifested by systems providing and consuming services, have already been introduced. However, the deployment, operation, and maintenance of an extensive SoS (System of Systems) mean enormous challenges for system integrators as well as network and service operators. The existing lifecycle management approaches do not cover all aspects of SoS management; therefore, an integrated solution is required. The purpose of this paper is to introduce a new lifecycle approach, namely the SoSLM (System of Systems Lifecycle Management). This paper first provides an in-depth description and comparison of the most relevant process engineering methodologies and ITSM (Information Technology Service Management) frameworks, and how they affect various lifecycle management strategies. The paper’s novelty strives to introduce an Industry 4.0-compatible PLM (Product Lifecycle Management) model and to extend it to cover SoS management-related issues on well-known process engineering methodologies. The presented methodologies are adapted to the PLM model, thus creating the recommended SoSLM model. This is supported by demonstrations of how the IIoT (Industrial Internet of Things) applications and services can be developed and handled. Accordingly, complete implementation and integration are presented based on the proposed SoSLM model, using the Arrowhead framework that is available for IIoT SoS. Full article
(This article belongs to the Special Issue Lifecycle and Supply Chain Optimization in Industry 4.0)
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