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Special Issue "Industry 4.0 Technologies for Sustainable Asset Life Cycle Management"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (15 November 2022) | Viewed by 4358

Special Issue Editors

Dr. Malgorzata Jasiulewicz-Kaczmarek
E-Mail Website1 Website2
Guest Editor
Faculty of Engineering Management, Poznan University of Technology, 61-704 Poznan, Poland
Interests: manufacturing engineering; maintenance technologies; maintenance management; multi-criteria decision-making methods; sustainability performance
Special Issues, Collections and Topics in MDPI journals
Dr. Katarzyna Antosz
E-Mail Website
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 inteligence; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Chao Zhang
E-Mail Website
Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Interests: reliability testing; accelerated life testing; reliability estimation; maintenance strategy
Prof. Dr. Vitalii Ivanov
E-Mail Website
Guest Editor
Department of Manufacturing Engineering, Machines and Tools, Sumy State University, 40007 Sumy, Ukraine
Interests: Industry 4.0; intelligent manufacturing; manufacturing technology; CAx technologies; decision support systems

Special Issue Information

Dear Colleagues,

Asset life cycle management is not a new concept for industries. Life cycle thinking means that people have a life cycle model in mind that affects the scope of their activities. A life cycle perspective for manufacturing assets is often mentioned in the literature regarding sustainability. This approach aims to understand and analyze individual stages of the asset life cycle, identify potential economic, social, and environmental risk factors and opportunities at each stage, and create possibilities to take advantage of these opportunities and reduce potential risks. In the Industry 4.0 era, manufacturers can monitor assets and make smart decisions in each phase of their life cycle through real-time communication and cooperation with humans, machines, sensors, etc. These technologies can support all stages of ALC through various emergent communication, information, and intelligence technologies. Technologies such as Digital Twin (DT), Internet of Things (IoT), Cyber-Physical Systems (CPS) and their respective specialization to industry, Industrial Internet of Things (IIoT), and Cyber-Physical Production System (CPPS), are considered in this Special Issue to increase the effectiveness of asset life cycle management (ALCM).

Topics and themes of this Special Issue can include but are not limited to:

  • Drivers and barriers for the implementation of Industry 4.0 technologies for sustainability in ALCM;
  • Intelligent decision support systems for sustainability in ALCM;
  • Digitalization and Industry 4.0 for supporting the ALCM;
  • Mapping of technologies and capabilities for adoption and implementation of Industry I4.0 for ALCM;
  • Role of competences for successful adoption and implementation of Industry 4.0 technologies for ALCM;
  • Digital product–service system for sustainability in ALCM;
  • The impact of digitalization on ALCM;
  • Modeling and simulation in ALCM;
  • Big data analytics implementation for sustainable ALCM;
  • Digital-twin-driven intelligent ALCM for sustainability;
  • IoT solutions in ALCM for sustainability;
  • Data-driven maintenance and ALCM systems;
  • Risk-based approaches in ALCM;
  • Causes and effects of implementing Industry 4.0 technologies for sustainable ALCM.

Dr. Malgorzata Jasiulewicz-Kaczmarek
Prof. Dr. Katarzyna Antosz
Dr. Chao Zhang
Prof. Dr. Vitalii Ivanov
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. Sustainability 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 2200 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

  • asset life cycle management
  • Industry 4.0 technologies (e.g., IoT, big data, AI, additive manufacturing, robotics)
  • life cycle data for sustainability
  • product-service system
  • servitization
  • operation and maintenance
  • reliability and availability
  • smart maintenance
  • data-driven design
  • digital twin

Published Papers (4 papers)

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Research

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Article
State Estimation and Remaining Useful Life Prediction of PMSTM Based on a Combination of SIR and HSMM
Sustainability 2022, 14(24), 16810; https://doi.org/10.3390/su142416810 - 14 Dec 2022
Viewed by 408
Abstract
The permanent magnet synchronous traction motor (PMSTM) is the core equipment of urban rail transit. If a PMSTM fails, it will cause serious economic losses and casualties. It is essential to estimate the current health state and predict remaining useful life (RUL) for [...] Read more.
The permanent magnet synchronous traction motor (PMSTM) is the core equipment of urban rail transit. If a PMSTM fails, it will cause serious economic losses and casualties. It is essential to estimate the current health state and predict remaining useful life (RUL) for PMSTMs. Directly obtaining the internal representation of a PMSTM is known to be difficult, and PMSTMs have long service lives. In order to address these drawbacks, a combination of SIR and HSMM based state estimation and RUL prediction method is introduced with the multi-parameter fusion health index (MFHI) as the performance indicator. The proposed method’s advantages over the conventional HSMM method were verified through simulation research and examples. The results show that the proposed state estimation method has small error distribution results, and the RUL prediction method can obtain accurate results. The findings of this study demonstrate that the proposed method may serve as a new and effective technique to estimate a PMSTM’s health state and RUL. Full article
(This article belongs to the Special Issue Industry 4.0 Technologies for Sustainable Asset Life Cycle Management)
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Article
Implementing Sustainable Development Concept: A Typology of Family Firms in Poland
Sustainability 2022, 14(7), 4302; https://doi.org/10.3390/su14074302 - 05 Apr 2022
Cited by 1 | Viewed by 1026
Abstract
For companies, sustainable development generally represents a long-term business orientation towards social, economic and environmental well-being. The concept has gained momentum among researchers partly due to the necessity of finding a modern approach to business development that does not deprive the next generation [...] Read more.
For companies, sustainable development generally represents a long-term business orientation towards social, economic and environmental well-being. The concept has gained momentum among researchers partly due to the necessity of finding a modern approach to business development that does not deprive the next generation of the opportunity to meet its own needs. Based on a sample of 333 Polish family firms, three groups of businesses were isolated (via k-means clustering) on the basis of low, medium and high deployment of pro-sustainability initiatives. This paper aims to investigate whether family firms demonstrating divergent levels of sustainable development express between-group differences. Measuring diversity using ANOVA with post hoc testing produced results associating business growth and higher levels of family involvement (e.g., via increased participation of family members from different generations in firm management) with the increased absorption of sustainable solutions and actions. These findings support notions from social identity theory suggesting that groups significantly shape the individual identities of their members. This means that family members inclined to implement sustainable development initiatives are likely to stimulate each other to introduce particular solutions and actions in praxis. Full article
(This article belongs to the Special Issue Industry 4.0 Technologies for Sustainable Asset Life Cycle Management)
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Article
The Influence of Cork and Manufacturing Parameters on the Properties of Cork–Rubber Composites for Vibration Isolation Applications
Sustainability 2021, 13(20), 11240; https://doi.org/10.3390/su132011240 - 12 Oct 2021
Cited by 2 | Viewed by 836
Abstract
The addition of cork to a natural rubber compound and the vulcanization parameters were studied in terms of their influence on the properties of cork–rubber materials. The characterization of different compounds was carried out and included in the determination of mechanical properties related [...] Read more.
The addition of cork to a natural rubber compound and the vulcanization parameters were studied in terms of their influence on the properties of cork–rubber materials. The characterization of different compounds was carried out and included in the determination of mechanical properties related to the application of cork–rubber composites as vibration isolation pads, such as static and dynamic behavior under compressive loading. Statistical methods, such as ANOVA and regression analysis, were used in this study. The results showed that the introduction of cork as an additional filler in the studied rubber compound increased its hardness and static stiffness, while maintaining a similar dynamic behavior to the base rubber compound when subjected to compressive loading. In addition, it was found that increasing the amount and granulometry of cork and lower vulcanization temperatures resulted in stiffer vulcanizates. Materials with higher cork granule contents were found to be affected in their final properties by molding pressure. A study involving the use of linear regression models as a tool to predict or optimize properties related to vibration isolation applications was also developed. Full article
(This article belongs to the Special Issue Industry 4.0 Technologies for Sustainable Asset Life Cycle Management)
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Review

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Review
Trends in Adopting Industry 4.0 for Asset Life Cycle Management for Sustainability: A Keyword Co-Occurrence Network Review and Analysis
Sustainability 2022, 14(19), 12233; https://doi.org/10.3390/su141912233 - 27 Sep 2022
Viewed by 614
Abstract
With the potential of Industry 4.0 technologies to enable sustainable manufacturing, asset life cycle management (ALCM) has been gaining increasing attention in recent years. This study explores the evolution of Industry 4.0 technology applications to sustainable ALCM from 2002 to 2021. This study [...] Read more.
With the potential of Industry 4.0 technologies to enable sustainable manufacturing, asset life cycle management (ALCM) has been gaining increasing attention in recent years. This study explores the evolution of Industry 4.0 technology applications to sustainable ALCM from 2002 to 2021. This study is based on keywords collected from 3896 ALCM-related scientific articles published in the Web of Science, IEEE Xplore and Engineering Village between 2002 and 2021. We conducted a review analysis of these keywords using a network science-based methodology, which unlike the tedious traditional literature review methods, gives the capability to analyze a huge number of scientific articles efficiently. We built keyword co-occurrence networks (KCNs) from the keywords and explored the network characteristics to uncover meaningful knowledge patterns, knowledge components, knowledge structure, and research trends in the body of literature at the intersection of ALCM and Industry 4.0. The network modeling and data analysis results identify the emerging Industry 4.0-related keywords in ALCM literature and indicate the recent explosion of connectivity among keywords. We found IoT, predictive maintenance and big data to be the top three most popular Industry 4.0-related keywords in ALCM literature. Furthermore, this study maps relevant ALCM keywords in contemporary literature to the nine pillars of Industry 4.0 to help the responsible manufacturing community identify research trends and emerging technologies for sustainability. Full article
(This article belongs to the Special Issue Industry 4.0 Technologies for Sustainable Asset Life Cycle Management)
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