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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
Lupi, F., Maffei, A. & Lanzetta, M. (2024). CAD-based Autonomous Vision Inspection Systems. 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, Portugal, Nov 22 2023 - Nov 24 2023 (pp. 2127-2136). Elsevier BV
Open this publication in new window or tab >>CAD-based Autonomous Vision Inspection Systems
2024 (English)In: 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023, Elsevier BV , 2024, p. 2127-2136Conference paper, Published paper (Refereed)
Abstract [en]

Automated industrial Visual Inspection Systems (VIS) are typically customized for specific applications, limiting their flexibility. They are characterized by a demanding setup, high capital investments, and significant knowledge barriers. In this paper, we propose an alternative architecture for the visual inspection of 3D printed parts or complex assemblies using a robotic arm equipped with hand-eye sensors and controllable lighting system. The core of the proposed Flexible Vision Inspection System (FVIS) is the self-extraction of 3D text annotations from STandard for the Exchange of Product model (STEP) AP242 files. The system self-selects and parametrizes the most suitable inspection algorithm, including lighting settings. Additionally, it autonomously performs self-localization, self-referencing of physical products, and self-planning of robot inspection path based on CAD information. This framework, characterized by self-X, cost-effective, non-invasive, and plug-and-play architecture has the potential to disrupt the business model of vision inspection, enabling an as-a-service solution aligned with the next generation of flexible manufacturing.

Place, publisher, year, edition, pages
Elsevier BV, 2024
Keywords
Autonomous Systems, Flexible Manufacturing, Industry 4.0, STEP file, Visual Inspection
National Category
Robotics
Identifiers
urn:nbn:se:kth:diva-345722 (URN)10.1016/j.procs.2024.02.033 (DOI)2-s2.0-85189768801 (Scopus ID)
Conference
5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023, Lisbon, Portugal, Nov 22 2023 - Nov 24 2023
Note

QC 20240430

Available from: 2024-04-18 Created: 2024-04-18 Last updated: 2024-04-30Bibliographically 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
Boffa, E. & Maffei, A. (2024). Investigating the impact of digital transformation on manufacturers’ Business model: Insights from Swedish industry. Journal of Open Innovation: Technology, Market, and Complexity, 10(2), Article ID 100312.
Open this publication in new window or tab >>Investigating the impact of digital transformation on manufacturers’ Business model: Insights from Swedish industry
2024 (English)In: Journal of Open Innovation: Technology, Market, and Complexity, E-ISSN 2199-8531, Vol. 10, no 2, article id 100312Article in journal (Refereed) Published
Abstract [en]

Digital transformation (DT) triggers a fundamental technological shift in industry enabling the creation of smart and connected factories. DT is not only a technology-driven innovation approach: it also requires changes of the Business Model (BM). Despite this, there is a lack of comprehensive studies that examine how aspects of manufacturing digitalisation align with the Business Model Innovation (BMI) process. To address this gap, this paper analyses the DT journey of several Swedish medium and large firms through semi-structured interviews with staff involved in such process. The empirical findings reveal that the BM elements addressing value creation and strategy aspects are the most affected by DT. Additionally, this study identifies the links among such elements. The findings are compiled in a holistic framework that can serve as a blueprint for practitioners seeking to adopt digital technologies in their production environments. This holistic approach aims at supporting practitioners to understand the BMI process triggered by DT and consequently aligning their manufacturing strategy with the BM's components.

Place, publisher, year, edition, pages
Elsevier B.V., 2024
Keywords
Business model, Business model innovation, Digital transformation, Digitalization level, Manufacturing, Semi-structured interviews
National Category
Information Systems
Identifiers
urn:nbn:se:kth:diva-347683 (URN)10.1016/j.joitmc.2024.100312 (DOI)2-s2.0-85195078932 (Scopus ID)
Note

QC 20240613

Available from: 2024-06-13 Created: 2024-06-13 Last updated: 2024-06-13Bibliographically 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
Ericsson, K. & Maffei, A. (2023). A Systematic Literature Review on Combinations of Industry 4.0 and Lean Production. In: Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures: IFIP WG 5.7 International Conference, APMS 2023, Proceedings. Paper presented at IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2023, Trondheim, Norway, Sep 21 2023 - Sep 17 2023 (pp. 139-156). Springer Nature
Open this publication in new window or tab >>A Systematic Literature Review on Combinations of Industry 4.0 and Lean Production
2023 (English)In: Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures: IFIP WG 5.7 International Conference, APMS 2023, Proceedings, Springer Nature , 2023, p. 139-156Conference paper, Published paper (Refereed)
Abstract [en]

Prior literature reviews on combining Industry 4.0 (I4.0) and Lean Production (LP) in production has often described the paradigms as “supportive”, where either “I4.0 supports LP” or “LP supports I4.0”. In this systematic review of 50 studies from this growing area of research, we find evidence of cases where combinations have not been “supportive”. We also find evidence of causal interactions that cannot be subordinated “I4.0 supports LP” nor “LP supports I4.0”, and that plainly go beyond those two categories. Additionally, we find that several studies evaluate the merits of I4.0- and LP combinations without looking at their effects on results in production, which substantially reduces the use of these evaluations to production managers. We encourage future studies to use nomenclature that does not unnecessarily limit the overall perception of the properties of I4.0- and LP combinations, to evaluate the merits of such combinations more in line with the requirements of production managers, and to be more cautious when concluding on causal interactions between I4.0 and LP.

Place, publisher, year, edition, pages
Springer Nature, 2023
Keywords
I4.0/LP combinations, Industry 4.0, Lean Manufacturing, Lean Production, operations performance
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-337990 (URN)10.1007/978-3-031-43662-8_11 (DOI)2-s2.0-85172413930 (Scopus ID)
Conference
IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2023, Trondheim, Norway, Sep 21 2023 - Sep 17 2023
Note

Part of ISBN 9783031436611

QC 20231012

Available from: 2023-10-12 Created: 2023-10-12 Last updated: 2023-10-12Bibliographically 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
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0723-1712

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