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Monetti, Fabio Marco, MScORCID iD iconorcid.org/0000-0003-2993-511X
Publications (10 of 17) Show all publications
Monetti, F. M., Bertoni, M. & Maffei, A. (2024). A Systematic Literature Review:Key Performance Indicatorson Feeding-as-a-Service. In: Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024). Paper presented at Swedish Production Symposium 2024, Trollhättan, Sweden, April 23-26, 2024 (pp. 256-267). IOS Press, 52
Open this publication in new window or tab >>A Systematic Literature Review:Key Performance Indicatorson Feeding-as-a-Service
2024 (English)In: Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024), IOS Press , 2024, Vol. 52, p. 256-267Conference paper, Published paper (Refereed)
Abstract [en]

In the evolving landscape of modern manufacturing, a novel concept known as Feeding-as-a-Service (FaaS) is emerging, part of the larger Automationas-a-Service (AaaS) framework. FaaS aims to optimize feeding systems in cloud manufacturing environments to meet the demands of mass customization and allow for quick responses to production changes. Therefore, it fits into the Manufacturing as-a-Service (MaaS) system as well. As the manufacturing industry undergoes significant transformations through automation and service-oriented models, understanding how FaaS fits into the other frameworks is essential.This study presents a systematic literature review with two primary objectives: first, to contextualize FaaS within AaaS and MaaS, highlighting similarities, differences,and distinctive characteristics; second, to identify and clarify the essential Key Performance Indicators (KPIs) crucial for its strategic implementation.KPIs are pivotal metrics guiding organizations toward manufacturing excellence.In this context, common KPIs focus on efficiency and quality, such as resource utilization, and error rates. Other KPIs are also crucial, such as the ones related tocost reduction and customer satisfaction. For FaaS, the most relevant include also data security, data management, and network speed.This research provides a valuable KPI framework for FaaS developers, aidingin strategic decision making and deployment in industrial settings. It also contributes to a broader understanding of KPIs in manufacturing, which benefits both researchers and industrial practitioners.The results of the review, though, fail to address other crucial indicators for ‘asa-Service’ business, such as Churn Rate and Total Contract Value. Future research will address these limitations through methods ranging from questionnaires to practitioner interviews, with the aim of gathering the knowledge needed for real-world implementations.

Place, publisher, year, edition, pages
IOS Press, 2024
Series
Advances in Transdisciplinary Engineering ; 52
Keywords
Key performance indicators, feeding-as-a-service, automation-as-aservice, manufacturing-as-a-service, cloud manufacturing
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-345682 (URN)10.3233/ATDE240170 (DOI)2-s2.0-85191338996 (Scopus ID)
Conference
Swedish Production Symposium 2024, Trollhättan, Sweden, April 23-26, 2024
Note

QC 20240429

Available from: 2024-04-18 Created: 2024-04-18 Last updated: 2024-05-14Bibliographically approved
Monetti, F. M., Martínez, P. Z. & Maffei, A. (2024). Assessing sustainable recyclability of battery systems: a tool to aid design for disassembly. In: Proceedings of the Design Society, Design 2024: . Paper presented at 2024 International Design Society Conference, Design 2024, Cavtat, Dubrovnik, Croatia, May 20 2024 - May 23 2024 (pp. 1389-1398). Cambridge University Press (CUP), 4
Open this publication in new window or tab >>Assessing sustainable recyclability of battery systems: a tool to aid design for disassembly
2024 (English)In: Proceedings of the Design Society, Design 2024, Cambridge University Press (CUP) , 2024, Vol. 4, p. 1389-1398Conference paper, Published paper (Refereed)
Abstract [en]

This study, conducted with Northvolt, examines battery system recyclability and disassembly dynamics. It introduces indices for material and product recyclability, along with disassembly time assessment. The goal is to create a design tool to streamline the evaluation of battery disassembly, aiding in designing recyclable and serviceable components. These methodologies serve as a blueprint for enhancing battery systems' overall sustainability and circularity design, presenting a base for future product development in alignment with environmental and economic objectives.

Place, publisher, year, edition, pages
Cambridge University Press (CUP), 2024
Keywords
batteries, circular economy, design for x (DfX), energy storage systems, sustainability
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-347333 (URN)10.1017/pds.2024.141 (DOI)2-s2.0-85194038526 (Scopus ID)
Conference
2024 International Design Society Conference, Design 2024, Cavtat, Dubrovnik, Croatia, May 20 2024 - May 23 2024
Note

QC 20240613

Available from: 2024-06-10 Created: 2024-06-10 Last updated: 2024-06-13Bibliographically approved
Antonelli, D., Aliev, K., Soriano, M., Samir, K., Monetti, F. M. & Maffei, A. (2024). Exploring the limitations and potential of digital twins for mobile manipulators in industry. In: 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023): . Paper presented at 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023, Lisbon, 22-24 November 2023 (pp. 1121-1130). Elsevier BV, 232
Open this publication in new window or tab >>Exploring the limitations and potential of digital twins for mobile manipulators in industry
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2024 (English)In: 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023), Elsevier BV , 2024, Vol. 232, p. 1121-1130Conference paper, Published paper (Refereed)
Abstract [en]

This paper explores the qualification of a digital twin (DT) for a mobile manipulator (MOMA) in industrial applications. We discuss the development of different DT models based on various industrial needs and highlight the dependence of model accuracy on online sensor precision. Limitations of DTs for MOMA are examined, including challenges in respecting qualifiers due to the inability to incorporate unstructured aspects of the factory environment. Through a case study and some examples, we show the latent potential and limitations of DTs for MOMA in industrial contexts. The challenges of fidelity, real-time operation, and environment modeling are discussed. It is emphasized that creating a true digital twin of a mobile manipulator is hindered by the inability to include the complete surrounding environment. Recommendations for future research focus on addressing these limitations to enhance the effectiveness of DTs for MOMA in Industry 4.0 and smart manufacturing.

Place, publisher, year, edition, pages
Elsevier BV, 2024
Series
Procedia Computer Science, ISSN 1877-0509 ; 232
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-345683 (URN)10.1016/j.procs.2024.01.110 (DOI)2-s2.0-85189767607 (Scopus ID)
Conference
5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023, Lisbon, 22-24 November 2023
Note

QC 20240418

Available from: 2024-04-18 Created: 2024-04-18 Last updated: 2024-06-10Bibliographically approved
Monetti, F. M. & Maffei, A. (2024). Towards the definition of assembly-oriented modular product architectures: a systematic review. Research in Engineering Design, 35(2), 137-169
Open this publication in new window or tab >>Towards the definition of assembly-oriented modular product architectures: a systematic review
2024 (English)In: Research in Engineering Design, ISSN 0934-9839, E-ISSN 1435-6066, Vol. 35, no 2, p. 137-169Article in journal (Refereed) Published
Abstract [en]

The success of a product in the market is largely defined by the quality of design decisions made during the early stages of development. The product design requires designers to balance multiple objectives such as functionality, cost, and user satisfaction, while addressing the challenges posed by increasing product variants and customization demands. To tackle these challenges, one approach is to structure a comprehensive model that incorporates design for assembly (DFA) guidelines during the formulation of product architecture in the conceptual phase of development. While numerous strategies have been proposed in the literature, information is often scattered, making it difficult for readers to gain a comprehensive understanding of the topic. This paper systematically reviews the role and impact of DFA in product development, consolidating and presenting the information coherently. The review provides an overview of the methods developed, along with their potential benefits and limitations. A common framework is identified that defines the structure of the models, helping designers integrate assembly consideration into their design processes, thus reducing assembly time, cost, and complexity. The framework describes the operational setting, including the domain and context in which models operate, and offers a classification of possible methods and desired outputs. Additionally, the review identifies the industry in which case studies have been most frequently presented, and the software used to facilitate the process. By connecting with such a framework, future models can be created following a structured approach, and existing models can be classified and upgraded accordingly.

Place, publisher, year, edition, pages
Springer Nature, 2024
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-345681 (URN)10.1007/s00163-023-00427-1 (DOI)2-s2.0-85176773561 (Scopus ID)
Funder
KTH Royal Institute of Technology
Note

QC 20240418

Available from: 2024-04-18 Created: 2024-04-18 Last updated: 2024-04-18Bibliographically approved
Mo, F., Rehman, H. U., Monetti, F. M., Chaplin, J. C., Sanderson, D., Popov, A., . . . Ratchev, S. (2023). A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence. Robotics and Computer-Integrated Manufacturing, 82, 102524, Article ID 102524.
Open this publication in new window or tab >>A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence
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2023 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 82, p. 102524-, article id 102524Article in journal (Refereed) Published
Abstract [en]

Digital twins and artificial intelligence have shown promise for improving the robustness, responsiveness, and productivity of industrial systems. However, traditional digital twin approaches are often only employed to augment single, static systems to optimise a particular process. This article presents a paradigm for combining digital twins and modular artificial intelligence algorithms to dynamically reconfigure manufacturing systems, including the layout, process parameters, and operation times of numerous assets to allow system decision -making in response to changing customer or market needs. A knowledge graph has been used as the enabler for this system-level decision-making. A simulation environment has been constructed to replicate the manufacturing process, with the example here of an industrial robotic manufacturing cell. The simulation environment is connected to a data pipeline and an application programming interface to assist the integration of multiple artificial intelligence methods. These methods are used to improve system decision-making and optimise the configuration of a manufacturing system to maximise user-selectable key performance indicators. In contrast to previous research, this framework incorporates artificial intelligence for decision -making and production line optimisation to provide a framework that can be used for a wide variety of manufacturing applications. The framework has been applied and validated in a real use case, with the automatic reconfiguration resulting in a process time improvement of approximately 10%.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Reconfigurable manufacturing system, Modular artificial intelligence, Digital twin, Process simulation, Knowledge graphs
National Category
Robotics
Identifiers
urn:nbn:se:kth:diva-324472 (URN)10.1016/j.rcim.2022.102524 (DOI)000925914800001 ()2-s2.0-85146635569 (Scopus ID)
Note

QC 20230403

Available from: 2023-04-03 Created: 2023-04-03 Last updated: 2023-04-03Bibliographically approved
Mo, F., Monetti, F. M., Torayev, A., Rehman, H. U., Mulet Alberola, J. A., Rea Minango, N., . . . Chaplin, J. C. (2023). A maturity model for the autonomy of manufacturing systems. The International Journal of Advanced Manufacturing Technology, 126(1-2), 405-428
Open this publication in new window or tab >>A maturity model for the autonomy of manufacturing systems
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2023 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 126, no 1-2, p. 405-428Article in journal (Refereed) Published
Abstract [en]

Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require system robustness, flexibility, and resilience. To adapt to these new requirements, manufacturers should consider investigating, investing in, and implementing system autonomy. Autonomy is being adopted in multiple industrial contexts, but divergences arise when formalizing the concept of autonomous systems. To develop an implementation of autonomous manufacturing systems, it is essential to specify what autonomy means, how autonomous manufacturing systems are different from other autonomous systems, and how autonomous manufacturing systems are identified and achieved through the main features and enabling technologies. With a comprehensive literature review, this paper provides a definition of autonomy in the manufacturing context, infers the features of autonomy from different engineering domains, and presents a five-level model of autonomy — associated with maturity levels for the features — to ensure the complete identification and evaluation of autonomous manufacturing systems. The paper also presents the evaluation of a real autonomous system that serves as a use-case and a validation of the model.

Place, publisher, year, edition, pages
Springer Nature, 2023
Keywords
Decision-making; Self-learning; Manufacturing; Digital twin; Industry 4.0; Machine learning
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-327407 (URN)10.1007/s00170-023-10910-7 (DOI)000940340200006 ()2-s2.0-85148953526 (Scopus ID)
Projects
DiManD Innovative Training Network (ITN)
Note

QC 20230529

Available from: 2023-05-26 Created: 2023-05-26 Last updated: 2023-05-29Bibliographically approved
de Giorgio, A., Monetti, F. M., Maffei, A., Romero, M. & Wang, L. (2023). Adopting extended reality?: A systematic review of manufacturing training and teaching applications. Journal of manufacturing systems, 71, 645-663
Open this publication in new window or tab >>Adopting extended reality?: A systematic review of manufacturing training and teaching applications
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2023 (English)In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 71, p. 645-663Article in journal (Refereed) Published
Abstract [en]

The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Extended reality, Augmented reality, Virtual reality, Manufacturing, Education, Technology readiness level (TRL)
National Category
Production Engineering, Human Work Science and Ergonomics Human Computer Interaction
Identifiers
urn:nbn:se:kth:diva-340328 (URN)10.1016/j.jmsy.2023.10.016 (DOI)001107069600001 ()2-s2.0-85175525171 (Scopus ID)
Funder
KTH Royal Institute of Technology
Note

QC 20231215

Available from: 2023-12-02 Created: 2023-12-02 Last updated: 2023-12-15Bibliographically approved
Maffei, A., Mura, M. D., Monetti, F. M. & Boffa, E. (2023). Dynamic Mixed Reality Assembly Guidance Using Optical Recognition Methods. Applied Sciences, 13(3), Article ID 1760.
Open this publication in new window or tab >>Dynamic Mixed Reality Assembly Guidance Using Optical Recognition Methods
2023 (English)In: Applied Sciences, E-ISSN 2076-3417, Vol. 13, no 3, article id 1760Article in journal (Refereed) Published
Abstract [en]

Augmented (AR) and Mixed Reality (MR) technologies are enablers of the Industry 4.0 paradigm and are spreading at high speed in production. Main applications include design, training, and assembly guidance. The latter is a pressing concern, because assembly is the process that accounts for the biggest portion of total cost within production. Teaching and guiding operators to assemble with minimal effort and error rates is pivotal. This work presents the development of a comprehensive MR application for guiding novice operators in following simple assembly instructions. The app follows innovative programming logic and component tracking in a dynamic environment, providing an immersive experience that includes different guidance aids. The application was tested by experienced and novice users, data were drawn from the performed experiments, and a questionnaire was submitted to collect the users' perception. Results indicate that the MR application was easy to follow and even gave confidence to inexperienced subjects. The guidance support was perceived as useful by the users, though at times invasive in the field of view. Further development effort is required to draw from this work a complete and usable architecture for MR application in assembly, but this research forms the basis to achieve better, more consistent instructions for assembly guidance based on component tracking.

Place, publisher, year, edition, pages
MDPI AG, 2023
Keywords
assembly, assembly instructions, assembly guidance, augmented reality, mixed reality, unity, Vuforia
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-324699 (URN)10.3390/app13031760 (DOI)000929438300001 ()2-s2.0-85148001562 (Scopus ID)
Note

QC 20230320

Available from: 2023-03-20 Created: 2023-03-20 Last updated: 2023-03-20Bibliographically approved
Monetti, F. M. & Maffei, A. (2023). Feeding-as-a-Service in a cloud manufacturing environment. In: 56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023: . Paper presented at 56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023, Oct 24 2023 - Oct 26 2023, Cape Town, South Africa (pp. 1387-1392). Elsevier BV
Open this publication in new window or tab >>Feeding-as-a-Service in a cloud manufacturing environment
2023 (English)In: 56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023, Elsevier BV , 2023, p. 1387-1392Conference paper, Published paper (Refereed)
Abstract [en]

The shift towards a mass customization paradigm in production requires the development of new concepts for manufacturing systems. Manufacturing system producers need to address the investment gap between large companies and SMEs to open new market shares and generate new revenue streams. Cloud technologies offer new service models and business opportunities: combined with Product Service Systems ideas, they can have a significant impact on both customers and suppliers. The paper proposes a new concept called Feeding-as-a-Service, which aims to connect servitization and cloud technology to explore how a feeding system can be deployed within an efficient and sustainable Configure-to-Order paradigm in a cloud manufacturing environment. The article outlines the potential system architecture, necessary technologies, and business model for the proposed Feeding-as-a-Service concept and highlights the advantages that the system offers through the enhancement of autonomous robotics capabilities for a cloud-deployed feeding service.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
business model, Cloud manufacturing, feeding-as-a-service, product service system, robot-as-a-service
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-343753 (URN)10.1016/j.procir.2023.09.181 (DOI)2-s2.0-85184610665 (Scopus ID)
Conference
56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023, Oct 24 2023 - Oct 26 2023, Cape Town, South Africa
Note

QC 20240228

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-02-28Bibliographically approved
Mo, F., Chaplin, J. C., Sanderson, D., Rehman, H. U., Monetti, F. M., Maffei, A. & Ratchev, S. (2022). A Framework for Manufacturing System Reconfiguration Based on Artificial Intelligence and Digital Twin. In: Kyoung-Yun Kim, Leslie Monplaisir, Jeremy Rickli (Ed.), Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus: Proceedings of FAIM 2022, June 19–23, 2022, Detroit, Michigan, USA. Paper presented at 31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, Detroit, 19-23 June 2022. Detroit, MI: Springer Nature
Open this publication in new window or tab >>A Framework for Manufacturing System Reconfiguration Based on Artificial Intelligence and Digital Twin
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2022 (English)In: Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus: Proceedings of FAIM 2022, June 19–23, 2022, Detroit, Michigan, USA / [ed] Kyoung-Yun Kim, Leslie Monplaisir, Jeremy Rickli, Detroit, MI: Springer Nature , 2022Conference paper, Published paper (Refereed)
Abstract [en]

The application of digital twins and artificial intelligence to manufacturing has shown potential in improving system resilience, responsiveness, and productivity. Traditional digital twin approaches are generally applied to single, static systems to enhance a specific process. This paper proposes a framework that applies digital twins and artificial intelligence to manufacturing system reconfiguration, i.e., the layout, process parameters, and operation time of multiple assets, to enable system decision making based on varying demands from the customer or market. A digital twin environment has been developed to simulate the manufacturing process with multiple industrial robots performing various tasks. A data pipeline is built in the digital twin with an API (application programming interface) to enable the integration of artificial intelligence. Artificial intelligence methods are used to optimise the digital twin environment and improve system decision-making. Finally, a multi-agent program approach shows the communication and negotiation status between different agents to determine the optimal configuration for a manufacturing system to solve varying problems. Compared with previous research, this framework combines distributed intelligence, artificial intelligence for decision making, and production line optimisation that can be widely applied in modern reactive manufacturing applications.

Place, publisher, year, edition, pages
Detroit, MI: Springer Nature, 2022
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364 ; 1
Keywords
Artificial intelligence; Multi-agent programming; Digital twin; Process simulation
National Category
Production Engineering, Human Work Science and Ergonomics Computer Sciences Computer and Information Sciences
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-321493 (URN)10.1007/978-3-031-18326-3_35 (DOI)2-s2.0-85141841476 (Scopus ID)
Conference
31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, Detroit, 19-23 June 2022
Note

QC 20221123

Part of proceedings: ISBN 978-3-031-18325-6

Available from: 2022-11-16 Created: 2022-11-16 Last updated: 2022-11-23Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-2993-511X

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