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Ferko, E., Bucaioni, A., Pelliccione, P. & Behnam, M. (2023). Analysing Interoperability in Digital Twin Software Architectures for Manufacturing. In: Lect. Notes Comput. Sci.: . Paper presented at Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 170-188). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Analysing Interoperability in Digital Twin Software Architectures for Manufacturing
2023 (English)In: Lect. Notes Comput. Sci., Springer Science and Business Media Deutschland GmbH , 2023, p. 170-188Conference paper, Published paper (Refereed)
Abstract [en]

Digital twins involve the integration of advanced information technologies to create software replicas that control and monitor physical assets. Interoperability is an essential requirement in the engineering of digital twins. This paper is the first study analysing interoperability in digital twin software architectures in the manufacturing industry. We began with an initial set of 2403 peer-reviewed publications and after a screening process, we selected a final set of 21 primary studies. We identified the set of technologies used for data exchange and the level of interoperability achieved during such an exchange. We organised the results according to the ISO 23247 standard and the level of conceptual interoperability model.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2023
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 14212 LNCS
Keywords
Digital twin, Interoperability, ISO 23247, LCIM, Software Architecture, Electronic data interchange, Advanced informations, Conceptual interoperability, Control and monitor, Interoperability modeling, Manufacturing industries, Physical assets, Screening process
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-64434 (URN)10.1007/978-3-031-42592-9_12 (DOI)2-s2.0-85172123330 (Scopus ID)9783031425912 (ISBN)
Conference
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Available from: 2023-10-09 Created: 2023-10-09 Last updated: 2023-10-09Bibliographically approved
Imtiaz, S., Capannini, G., Carlson, J., Behnam, M. & Jägemar, M. (2023). Automatic Clustering of Performance Events. In: : . Paper presented at 28th Annual Conference of the IEEE Industrial Electronics Society (ETFA2023).
Open this publication in new window or tab >>Automatic Clustering of Performance Events
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2023 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Modern hardware and software are becoming increasingly complex due to advancements in digital and smart solutions. This is why industrial systems seek efficient use of resources to confront the challenges caused by the complex resource utilization demand. The demand and utilization of different resources show the particular execution behavior of the applications. One way to get this information is by monitoring performance events and understanding the relationship among them. However, manual analysis of this huge data is tedious and requires experts’ knowledge. This paper focuses on automatically identifying the relationship between different performance events. Therefore, we analyze the data coming from the performance events and identify the points where their behavior changes. Two events are considered related if their values are changing at ”approximately” the same time. We have used the Sigmoid function to compute a real-value similarity between two sets (representing two events). The resultant value of similarity is induced as a similarity or distance metric in a traditional clustering algorithm. The proposed solution is applied to different software applications that are widely used in industrial systems to show how different setups including the selection of cost functions can affect the results.

National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-64276 (URN)10.1109/ETFA54631.2023.10275660 (DOI)2-s2.0-85175433182 (Scopus ID)
Conference
28th Annual Conference of the IEEE Industrial Electronics Society (ETFA2023)
Available from: 2023-09-18 Created: 2023-09-18 Last updated: 2024-01-18Bibliographically approved
Al-Dulaimy, A., Ashjaei, S. M., Behnam, M., Nolte, T. & Papadopoulos, A. (2023). Fault Tolerance in Cloud Manufacturing: An Overview. In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol 495: . Paper presented at 13th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2022, Messina, 17 November 2022 through 18 November 2022 (pp. 89-101). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Fault Tolerance in Cloud Manufacturing: An Overview
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2023 (English)In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol 495, Springer Science and Business Media Deutschland GmbH , 2023, p. 89-101Conference paper, Published paper (Refereed)
Abstract [en]

Utilizing edge and cloud computing to empower the profitability of manufacturing is drastically increasing in modern industries. As a result of that, several challenges have raised over the years that essentially require urgent attention. Among these, coping with different faults in edge and cloud computing and recovering from permanent and temporary faults became prominent issues to be solved. In this paper, we focus on the challenges of applying fault tolerance techniques on edge and cloud computing in the context of manufacturing and we investigate the current state of the proposed approaches by categorizing them into several groups. Moreover, we identify critical gaps in the research domain as open research directions. 

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2023
Keywords
Cloud computing, Cloud manufacturing, CMfg, Edge computing, Fault tolerance, MaaS, Manufacturing as a Service, Reliability
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-63500 (URN)10.1007/978-3-031-31891-7_7 (DOI)2-s2.0-85161360896 (Scopus ID)9783031318900 (ISBN)
Conference
13th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2022, Messina, 17 November 2022 through 18 November 2022
Available from: 2023-06-21 Created: 2023-06-21 Last updated: 2023-06-26Bibliographically approved
Fattouh, A., Chirumalla, K., Ahlskog, M., Behnam, M., Hatvani, L. & Bruch, J. (2023). Remote integration of advanced manufacturing technologies into production systems: integration processes, key challenges and mitigation actions. Journal of Manufacturing Technology Management
Open this publication in new window or tab >>Remote integration of advanced manufacturing technologies into production systems: integration processes, key challenges and mitigation actions
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2023 (English)In: Journal of Manufacturing Technology Management, ISSN 1741-038X, E-ISSN 1758-7786Article in journal (Refereed) Published
Abstract [en]

The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

Design/methodology/approach: The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

Findings: By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

Practical implications: The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

Originality/value: The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

Keywords
Technology adoption, Industry 4.0 implementation, Cyber-physical production system, Plug and produce, Smart production, Mobile robot, TOE framework, Production system development, Process innovation, Technology integration
National Category
Engineering and Technology Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:mdh:diva-61541 (URN)10.1108/jmtm-02-2022-0087 (DOI)000916547200001 ()2-s2.0-85146389784 (Scopus ID)
Available from: 2023-01-19 Created: 2023-01-19 Last updated: 2024-01-09Bibliographically approved
Struhar, V., Ashjaei, S. M., Behnam, M., Papadopoulos, A. & Craciunas, S. S. (2023). Resource Adaptation for Real-Time Containers Considering Quality of Control. In: IEEE Int. Conf. Emerging Technol. Factory Autom., ETFA: . Paper presented at IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Resource Adaptation for Real-Time Containers Considering Quality of Control
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2023 (English)In: IEEE Int. Conf. Emerging Technol. Factory Autom., ETFA, Institute of Electrical and Electronics Engineers Inc. , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Container-based virtualization has become a promising deployment model for industrial applications mainly due to its benefits, such as providing support for co-located applications in heterogeneous environments. However, such facilitation brings challenges, including full temporal isolation among real-time applications and support for time-critical applications. In this paper, we tackle such challenges, in particular when the applications are time-sensitive Control Applications. The literature suggests that flexible timing constraints for Control Applications are beneficial in responding to disturbances and minimizing response deviation. Therefore, we propose a mechanism to support such a runtime adaptation in container-based virtualization. To show the performance of the proposed mechanism, we implement our approach on a Linux-based hierarchical scheduling platform, and we evaluate it for a Control application.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Computer operating systems, Quality control, Virtual reality, Virtualization, Co-located, Control applications, Deployment models, Heterogeneous environments, Quality of controls, Real- time, Real-time application, Temporal isolation, Time-critical applications, Virtualizations, Containers
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-64702 (URN)10.1109/ETFA54631.2023.10275357 (DOI)2-s2.0-85175421179 (Scopus ID)9798350339918 (ISBN)
Conference
IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Available from: 2023-11-09 Created: 2023-11-09 Last updated: 2024-01-18Bibliographically approved
Ferko, E., Bucaioni, A., Pelliccione, P. & Behnam, M. (2023). Standardisation in Digital Twin Architectures in Manufacturing. In: 2023 IEEE 20th International Conference on Software Architecture (ICSA): . Paper presented at 2023 IEEE 20th International Conference on Software Architecture (ICSA), 13-17 March 2023,L'Aquila, Italy (pp. 70-81).
Open this publication in new window or tab >>Standardisation in Digital Twin Architectures in Manufacturing
2023 (English)In: 2023 IEEE 20th International Conference on Software Architecture (ICSA), 2023, p. 70-81Conference paper, Published paper (Refereed)
Abstract [en]

Engineering digital twins following standardised reference architectures is an upcoming requirement for ensuring their adoption and facilitating their creation, processing, and integration. The ISO 23247 standard proposes a reference architecture for digital twins in manufacturing, including an entity-based reference model and a functional view specified in terms of functional entities. During our experience with projects in the field, we noticed that standards, and in particular the ISO 23247 standard, are not completely followed. In this paper, we analyse to what extent digital twin architectures documented in the literature are aligned with the reference architecture presented in the ISO 23247 standard. We achieved this through a mixedmethods research methodology that includes the analysis of 29 digital twin architectures in the manufacturing domain resulting from a systematic literature review of 140 peer-reviewed studies, a survey with 33 respondents, and four semi-structured, in-depth expert interviews. On the basis of our findings, practitioners and researchers can reflect, discuss, and plan actions for future research and development activities.

Keywords
Software Architecture, Digital Twin, ISO 23247, Reference Architecture
National Category
Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-62410 (URN)10.1109/ICSA56044.2023.00015 (DOI)000990536000007 ()2-s2.0-85159222904 (Scopus ID)979-8-3503-9749-9 (ISBN)
Conference
2023 IEEE 20th International Conference on Software Architecture (ICSA), 13-17 March 2023,L'Aquila, Italy
Available from: 2023-05-08 Created: 2023-05-08 Last updated: 2023-09-15Bibliographically approved
Ferko, E., Bucaioni, A. & Behnam, M. (2023). Supporting Technical Adaptation and Implementation of Digital Twins in Manufacturing. In: 20th International Conference on Information Technology-New Generations. ITNG 2023.: . Paper presented at International Conference on Information Technology-New Generations. ITNG 2023. (pp. 181-189). , 1445, Article ID 21.
Open this publication in new window or tab >>Supporting Technical Adaptation and Implementation of Digital Twins in Manufacturing
2023 (English)In: 20th International Conference on Information Technology-New Generations. ITNG 2023., 2023, Vol. 1445, p. 181-189, article id 21Conference paper, Published paper (Refereed)
Abstract [en]

In manufacturing, digital twins are emerging technologies that integrate several advances, such as the industrial internet of things, and cyber-physical systems, for creating software replicas that monitor and control manufacturing units or processes. Despite their great potential and innovation, digital twins are challenging to implement and there is a lack of practical guidelines for their technical adaptation and implementation. This discourages enterprises from planning and adopting full-fledged digital twin-based solutions due to the low return on investment.

In this paper, we fill such a lack of guidelines for the technical adaptation and implementation of digital twins by providing a catalogue of technologies used for realising digital twin-based systems in manufacturing. We align the catalogue to the International Organization for Standardization 23247 standard for digital twins in manufacturing. We elicit the catalogue by systematically reviewing 14 state-of-the-art DT implementations resulting from a pool of 140 peer-reviewed studies.

To the best of our knowledge, this is the first work that identifies a catalogue of technologies supporting the realisation of digital twin-based systems mapping it into the 23247 standard.

Series
Advances in Intelligent Systems and Computing
Keywords
Digital twin, Manufacturing, ISO 23247, Standardisation, Architecture, Functional entities, Development, Implementation, Tools, Technologies
National Category
Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-62416 (URN)10.1007/978-3-031-28332-1_21 (DOI)978-3-031-28331-4 (ISBN)
Conference
International Conference on Information Technology-New Generations. ITNG 2023.
Available from: 2023-05-08 Created: 2023-05-08 Last updated: 2023-09-15Bibliographically approved
Ferko, E., Bucaioni, A. & Behnam, M. (2022). Architecting Digital Twins. IEEE Access, 10, 50335-50350
Open this publication in new window or tab >>Architecting Digital Twins
2022 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 10, p. 50335-50350Article in journal (Refereed) Published
Abstract [en]

In 2002, Grieves defined the concept of the digital twin as a virtual instance of physical assets capable of continuously mirroring them. Ever since then, driven by remarkable industrial attention, digital twins flourished and ripened in several sectors. The notable industrial adoption has been sided by a growing interest from the software engineering community in general and the software architecture community in particular as demonstrated by the growing number of published peer-reviewed publications and proposed software architectural solutions for digital twins. In this paper, we report on the planning, execution, and results of a systematic mapping study on architecting digital twins. The study captures crucial aspects of software architectures for digital twins as types of architectural solutions, quality attributes, and architectural patterns. It supports practitioners in creating digital twins tailored to their specific needs and researchers in identifying trends and open challenges. Starting from an initial set of potentially relevant 1630 peer-reviewed publications, we selected 140 primary studies. We analysed the set of primary studies using thorough data extraction, analysis, and synthesis process. To compensate for single method limitations and reduce possible threats to conclusion validity, we discussed the results of our study with experts in the software architecture community. Based on our results, the field of software architecture for digital twins is lively and an increasing number of architectural solutions are being proposed. Although there is a lack of widely accepted reference architectural solutions for digital twins, most of them are built using a combination of the layered and service-oriented patterns and address maintainability, performance efficiency, and compatibility quality attributes.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022
Keywords
Digital twin, Systematics, Software architecture, Computer architecture, Standards, Market research, Planning, Architectural patterns, software architectures, quality attributes
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-58351 (URN)10.1109/ACCESS.2022.3172964 (DOI)000797418000001 ()2-s2.0-85130855388 (Scopus ID)
Available from: 2022-06-01 Created: 2022-06-01 Last updated: 2023-09-15Bibliographically approved
Imtiaz, S., Behnam, M., Capannini, G., Carlson, J. & Marcus, J. (2022). Automatic Segmentation of Resource Utilization Data. In: 1st IEEE Industrial Electronics Society Annual On-Line Conference (ONCON) 2022: . Paper presented at 2022 IEEE 1st Industrial Electronics Society Annual On-Line Conference (ONCON), 09-11 December 2022, Kharagpur, India.
Open this publication in new window or tab >>Automatic Segmentation of Resource Utilization Data
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2022 (English)In: 1st IEEE Industrial Electronics Society Annual On-Line Conference (ONCON) 2022, 2022Conference paper, Published paper (Other academic)
Abstract [en]

Advancement of industrial systems seek improvements to achieve required level of quality of service and efficient performance management. It is essential though to have better understanding of resource utilization behaviour of applications in execution. Even the expert engineers desire to envision dependencies and impact of one computer resource on the other. For such situations it is significant to know statistical relationship between data sets such as a resource with higher cache demand should not be scheduled together with other cache hungry process at the same time and same core. Performance monitoring data coming from hardware and software is huge and grouping of this time series data based on similar behaviour can display distinguishable execution phases. For benefits like these we opt to choose change point analysis method. By using this method study determined the optimal threshold which can identify more or less same segments for other executions of same application and same event. These segments are then validated with the help of test data. Finally the study provided segment-wise, local, compact statistical model with decent accuracy.

National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-61461 (URN)10.1109/ONCON56984.2022.10126744 (DOI)2-s2.0-85161320276 (Scopus ID)979-8-3503-9806-9 (ISBN)
Conference
2022 IEEE 1st Industrial Electronics Society Annual On-Line Conference (ONCON), 09-11 December 2022, Kharagpur, India
Available from: 2023-01-11 Created: 2023-01-11 Last updated: 2023-09-19Bibliographically approved
Struhar, V., Craciunas, S., Behnam, M. & Papadopoulos, A. (2022). RT-Scaler: Adaptive Resource Allocation Framework for Real-Time Containers. In: Proceedings of RAGE 2022: . Paper presented at 1st Real-time And intelliGent Edge computing workshop, July 10th, 2022, San Francisco, CA, USA.
Open this publication in new window or tab >>RT-Scaler: Adaptive Resource Allocation Framework for Real-Time Containers
2022 (English)In: Proceedings of RAGE 2022, 2022Conference paper, Published paper (Refereed)
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-61291 (URN)
Conference
1st Real-time And intelliGent Edge computing workshop, July 10th, 2022, San Francisco, CA, USA
Available from: 2022-12-15 Created: 2022-12-15 Last updated: 2022-12-15Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1687-930X

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