Special Issue "Development, Reliability, Maintenance and Control of Cyber-Physical Systems"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 1462

Special Issue Editors

Prof. Dr. Katarzyna Antosz
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Guest Editor
Department of Manufacturing Processes and Production Engineering, Rzeszow University of Technology, Aleja Powstańców Warszawy 12, 35-959 Rzeszów, Poland
Interests: Industry 4.0; maintenance; production engineering; systems reliability; lean maintenance; decision support systems; artificial intelligence; machine learning
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Prof. Dr. Jose Machado
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Guest Editor
Prof. Dr. Yi Ren
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Guest Editor
School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
Interests: reliability modelling and design for complex systems; model-based reliability system engineering; reliability physics; autonomous system reliability
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Prof. Dr. Erika Ottaviano
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Guest Editor
Dept. of Civil and Mechanical Engineering (DICeM), University of Cassino and Southern Lazio, 03043 Cassino, Italy
Interests: robotics; mechanical design; automatic inspection
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Prof. Dr. Pierluigi Rea
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Guest Editor
Department of Mechanical, Chemical and Material Engineering (DIMCM), University of Cagliari (CA), 09123 Cagliari, Italy
Interests: robotics; mechatronics; mechanical design; automatic inspection
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Prof. Dr. Alejandro Pereira
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Guest Editor
Manufacturing Engineering Group (GEF) EEI Campus Lagoas, University of Vigo, 36310 Vigo, Spain
Interests: surface engineering; tribology; additive manufacturing; dimensional metrology, machining, robotics
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Special Issue Information

Dear Colleagues,

Industry 4.0 integrates massively implemented intelligent computing and network technologies for the purpose of automation, reliability and control of systems. Technologies such as the Internet of Things (IoT), cloud computing (CC), big data analytics (BDA), and artificial intelligence (AI) are driving the development of such systems significantly. An important element of intelligent systems are cyberphysical systems (CPS). These systems are networked systems of cyber (computing and communication) and physical (sensors and actuators) components that interact in a feedback loop with possible aid for human intervention, interaction, and use. Morover, CPS, due to the possibility of collecting and recording data, are used in many areas, e.g., smart manufacturing, autonomous vehicle systems, and intelligent energy networks and in numerous large-scale technologies. In this context, many research activities are related to the development, reliability, maintenance, and control of cyberphysical systems.

The scope of this Special Issue is closely associated with that of the ICIE’2022 conference. This conference and journal Special Issue is to present current innovations and engineering achievements of scientists and industrial practitioners in the thematic areas described above.

Topics of interest include but are not limited to the following:

  • Smart manufacturing and maintenance;
  • Industrial Internet of Things (IIoT);
  • Robotics and mechatronic systems;
  • Digital twins;
  • Multiagent systems (MAS);
  • Autonomous systems;
  • Human–machine interaction and machine to machine communication (M2M);
  • Learning control and cognition;
  • Artificial intelligence and data mining;
  • Predictive maintenance;
  • Reliability and risk assessment.

Prof. Dr. Katarzyna Antosz
Dr. José Machado
Prof. Dr. Yi Ren
Dr. Erika Ottaviano
Prof. Dr. Pierluigi Rea
Prof. Dr. Alejandro Pereira
Guest Editors

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2300 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.

Published Papers (2 papers)

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Research

Article
Joint Optimization of Production Lot Sizing and Preventive Maintenance Threshold Based on Nonlinear Degradation
Appl. Sci. 2022, 12(17), 8638; https://doi.org/10.3390/app12178638 - 29 Aug 2022
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Abstract
In a manufacturing system, lot sizing and maintenance are interdependent and interact with each other. Few studies jointly investigated production lot sizing and maintenance management considering system degradation. However, during the production process, the system and critical component performance will undergo inevitable degradation [...] Read more.
In a manufacturing system, lot sizing and maintenance are interdependent and interact with each other. Few studies jointly investigated production lot sizing and maintenance management considering system degradation. However, during the production process, the system and critical component performance will undergo inevitable degradation over time. For example, equipment wears out due to both its own internal causes and the external environment. To monitor the degradation process, interval inspection is usually performed to obtain information about the system degradation and nonlinear degradation is more general. Thus, based on the nonlinear degradation of the production system, this study developed a joint optimization model of production lot sizing and preventive maintenance (PM) thresholds with the goal of maximizing profit per unit of time. The maintenance decision follows the control limit principle, i.e., the choice between preventive maintenance (PM), corrective maintenance (CM), or neither (do nothing) is based on the magnitude of degradation. A simulation algorithm is proposed to obtain the optimal lot-sizing allocation and PM thresholds. The effectiveness of this joint optimization model algorithm is illustrated by numerical examples and the results show that the maximum profit per unit time can be obtained by reasonably formulating PM thresholds and production lot sizing. Full article
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Article
Identification of the Critical Enablers for Perishable Food Supply Chain Using Deterministic Assessment Models
Appl. Sci. 2022, 12(9), 4503; https://doi.org/10.3390/app12094503 - 29 Apr 2022
Viewed by 484
Abstract
Today’s perishable food supply chains must be resilient to handle volatile demands, environmental restrictions, and disruptions in order to meet customers’ requirements. The enablers of the perishable food supply chain have not yet been explored. In this paper, a bibliometric systematic literature review [...] Read more.
Today’s perishable food supply chains must be resilient to handle volatile demands, environmental restrictions, and disruptions in order to meet customers’ requirements. The enablers of the perishable food supply chain have not yet been explored. In this paper, a bibliometric systematic literature review has been conducted to identify the articles related to the perishable food supply chain. Next, with these identified articles, a map is created with bibliographic data using Vosviewer network visualization software, and then the enablers were identified by conducting keyword co-occurrence analysis. Later, a total interpretive structural modeling (TISM) is employed to analyze the interrelationships among enablers and then determine each enabler’s hierarchies, further representing them in a diagraph. Finally, the identified enablers are classified using cross-impact matrix multiplication applied to classification (MICMAC) analysis, and the graph is plotted. The results obtained from the deterministic assessment model provide the critical enablers for the perishable food supply chain. The obtained critical enablers and their hierarchies provide valuable insights for researchers in the context of perishable food supply chain for further study. Full article
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