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Publications (10 of 62) Show all publications
Massouh, B., Danielsson, F., Ramasamy, S., Khabbazi, M. R. & Zhang, X. (2024). Online Hazard Detection in Reconfigurable Plug & Produce Systems. In: Silva, F.J.G., Pereira, A.B., Campilho, R.D.S.G. (Ed.), Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems.: FAIM 2023. Paper presented at International Conference on Flexible Automation and Intelligent Manufacturing FAIM 2023, 18-22 June, Porto, Portugal (pp. 889-897). Springer Nature
Open this publication in new window or tab >>Online Hazard Detection in Reconfigurable Plug & Produce Systems
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2024 (English)In: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems.: FAIM 2023 / [ed] Silva, F.J.G., Pereira, A.B., Campilho, R.D.S.G., Springer Nature, 2024, p. 889-897Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Plug & Produce is a modern automation concept in smart manufacturing for modular, quick, and easy reconfigurable production. The system’s flexibility allows for the configuration of production with abstraction, meaning that the production resources participating in a specific production plan are only known in the online phase. The safety assurance process of such a system is complex and challenging. This work aims to assist the safety assurance when utilizing a highly flexible Plug & Produce concept that accepts instant logical and physical reconfiguration. In this work, we propose a concept for online hazard identification of Plug & Produce systems, the proposed concept, allows for the detection of hazards in the online phase and assists the safety assurance as it provides the hazard list of all possible executable alternatives of the abstract goals automatically. Further, it combines the safety-related information with the control logic allowing for safe planning of operations. The concept was validated with a manufacturing scenario that demonstrates the effectiveness of the proposed concept.

Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Mechanical Engineering
Keywords
Plug & Produce, reconfigurable manufacturing, safety assessment, hazard identification
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; Production Technology
Identifiers
urn:nbn:se:hv:diva-20884 (URN)10.1007/978-3-031-38241-3_97 (DOI)2-s2.0-85171556008 (Scopus ID)9783031382406 (ISBN)9783031382413 (ISBN)
Conference
International Conference on Flexible Automation and Intelligent Manufacturing FAIM 2023, 18-22 June, Porto, Portugal
Available from: 2023-12-28 Created: 2023-12-28 Last updated: 2024-01-30
Mosa, W., Massouh, B., Khabbazi, M. R., Eriksson, M. & Danielsson, F. (2024). Software-supported Hazards Identification for Plug & Produce Systems. In: Silva, F.J.G., Pereira, A.B., Campilho, R.D.S.G. (Ed.), Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems: FAIM 2023. Paper presented at International Conference on Flexible Automation and Intelligent Manufacturing FAIM 2023, 18-22 June, Porto, Portugal (pp. 603-610). Springer Nature
Open this publication in new window or tab >>Software-supported Hazards Identification for Plug & Produce Systems
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2024 (English)In: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems: FAIM 2023 / [ed] Silva, F.J.G., Pereira, A.B., Campilho, R.D.S.G., Springer Nature, 2024, p. 603-610Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

This paper presents a model-based safety software that performs Hazard Identification (HI) for Plug&Produce (P&P) systems automatically. P&P systems, inspired by Plug&Play in computers, aim to integrate devices and tools into the manufacturing system with minimum integration efforts and costs. When plugging a new resource, it will exchange all the required information with the manufacturing system and be ready to operate within minutes rather than days or weeks. One of the challenges that face this concept is performing proper risk assessment after each change in the system. Therefore, the risk assessment needs to be automated as much as possible. This paper is about automating one risk assessment step: Hazard Identification. A new safety model is designed to identify hazards. The presented software analyses this model by implementing a novel algorithm that uses lookup tables to cover various possible hazards when resources work together. This software will support the risk reduction team by drastically reducing the time needed for HI and being ready for the next steps in risk analyses. Automating identifying hazards is an essential step towards automating the entire risk assessment process and achieving safe P&P systems.

Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Mechanical Engineering
Keywords
Plug&Produce, Hazard identification, Safety, Risk assessment, Manufacturing systems
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-20885 (URN)10.1007/978-3-031-38241-3_68 (DOI)2-s2.0-85171582278 (Scopus ID)9783031382406 (ISBN)9783031382413 (ISBN)
Conference
International Conference on Flexible Automation and Intelligent Manufacturing FAIM 2023, 18-22 June, Porto, Portugal
Available from: 2023-12-28 Created: 2023-12-28 Last updated: 2023-12-28
Nilsson, A., Danielsson, F. & Svensson, B. (2023). Customization and flexible manufacturing capacity using a graphical method applied on a configurable multi-agent system. Robotics and Computer-Integrated Manufacturing, 79, Article ID 102450.
Open this publication in new window or tab >>Customization and flexible manufacturing capacity using a graphical method applied on a configurable multi-agent system
2023 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 79, article id 102450Article in journal (Refereed) Published
Abstract [en]

This article proposes a Plug & Produce and goal-oriented configurable multi-agent system that admits adding and removing resources to balance the manufacturing capacity without doing any digital reconfiguration or reprogramming. To handle that a new part-agent strategy is developed and described. Goals are central in designing autonomous multi-agent systems, possibilities to execute goals in parallel are desirable when the process requirements admit concurrent use of resources. Also, a standardized graphical method, the sequence of goals chart, is proposed to define and visualize parallel and sequential goals independently of available resources. Premanufacturing of wooden houses belongs to one of many manufacturing industries that claim flexible automation systems due to the high degree of customized products and a fluctuating market. A physical Plug & Produce robot-based workstation was built up to verify the flexibility in altering capacity and adoption to product modifications of a house wall section. Further, the simplicity of modifying the proposed configurable multi-agent system was compared to more traditionally designed systems and plain multi-agent systems with superior results. The flexibility is built into the proposed system by default as a part of the concept, simple enough to be handled by existing in-house knowledge within manufacturing companies. 

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
Autonomous agents; Flexible manufacturing systems; Graphic methods; Robot programming; Customisation; Flexible manufacturing; Goal-oriented; Graphical methods; Industrial robotics; Manufacturing capacity; Manufacturing industries; Plug & produce; Process requirements; Wooden house; Multi agent systems
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-19159 (URN)10.1016/j.rcim.2022.102450 (DOI)000858622500001 ()2-s2.0-85137028501 (Scopus ID)
Note

CC BY 4.0

This work was supported by the Region Västra Götaland (VGR) Dnr. RUN 2018-00476 and the Swedish Agency for Economic and Regional Growth ID: 20201948 through the project Tillverka i trä.

Available from: 2022-10-31 Created: 2022-10-31 Last updated: 2024-01-04Bibliographically approved
Nilsson, A., Danielsson, F. & Svensson, B. (2023). From CAD to Plug & Produce: A generic structure for the integration of standard industrial robots into agents. The International Journal of Advanced Manufacturing Technology, 128(11-12), 5249-5260
Open this publication in new window or tab >>From CAD to Plug & Produce: A generic structure for the integration of standard industrial robots into agents
2023 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 128, no 11-12, p. 5249-5260Article in journal (Refereed) Published
Abstract [en]

Industries of low-batches or one-of manufacturing aim for automation that is competitive enough to adapt to new or modifed products daily through in-house knowledge that focuses on manufacturing processes and not on machine function programming. To solve this, a complete set of actions that utilize seamless data transfer from product design in CAD to a Plug & Produce automation concept is proposed together with a generic structure for the integration of standard industrial robots into agents. This structure enables agents to handle their local reference coordinate systems and locations relative to a global perspective. Seamless utilization of data from product designs to Plug & Produce will simplify and shorten the time of digital development through concurrently usable text-based and graphical confguration tools of a confgurable multi-agent system. Needed data extracts directly from the product design as requirements of operational goals. Extraction of data from the product design, sequence of goals, and process plans, which are recipes of how to solve goals, can by this concept be confgured by in-house knowledge that has the process knowledge but not necessarily programming competence.

Place, publisher, year, edition, pages
Springer, 2023
Keywords
Robotics, Automation, Manufacturing, Multi-agent systems, Plug & Produce, Process planning
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-20871 (URN)10.1007/s00170-023-12280-6 (DOI)001096180300035 ()2-s2.0-85169880137 (Scopus ID)
Funder
Region Västra Götaland, 2018-00476Swedish Agency for Economic and Regional Growth, 20201948
Note

CC BY 4.0

Available from: 2023-10-29 Created: 2023-10-29 Last updated: 2024-01-08Bibliographically approved
Khabbazi, M. R., Danielsson, F., Bennulf, M., Ramasamy, S. & Nilsson, A. (2023). Model-based Plug & Produce in Assembly Automation. In: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA): 12-15 September 2023. Paper presented at 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, 2023-September
Open this publication in new window or tab >>Model-based Plug & Produce in Assembly Automation
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2023 (English)In: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA): 12-15 September 2023, IEEE, 2023, Vol. 2023-SeptemberConference paper, Published paper (Refereed)
Abstract [en]

Manual assembly systems are featured with high flexibility but with the risk of lower quality, higher cycle time, inefficient resource employment, and affecting sustainability goals in comparison to fully automated ones. Conventional automated assembly is challenged by the desired level of flexibility when compared to what automation through Plug & Produce system represents. Plug and Produce, during the last few decades aimed at addressing highly flexible automation systems handling rapid changes and adaptations as one dominant solution. Multi-agent System (MAS) as a tool to handle different areas of manufacturing control systems can be used in Plug & Produce representing every physical control entity (e.g., parts, resources) as agents. This article aims to describe a model-based configurable multi-agent design in Plug and Produce system together with a prototype implementation of the actual automated assembly use case of a kitting operation highlighting flexibility and reconfigurability and the model functionality. A model-based approach with a few models using UML standards describes the structure and behavior of the system. Model instantiation is introduced and followed by real prototype use case implementation. The use case study of advanced automated kitting operation in the assembly automation domain has been selected. Agent-based operation control systems have been applied during the assembly process. The evaluation was accomplished by testing several scenarios on Plug & Produce for kitting operation. To conclude, several desirable functionality features of the framework during the demonstration such as rapid instantiation and adaptation, and in particular, the flexibility features have been examined and evaluated with several failure-handling testing scenarios. © 2023 IEEE.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
Assembly; Automation; Control systems; Assembly automation; Assembly systems; Automated assembly; High flexibility; Kitting; Kitting operation; Manual assembly; Model-based design; Model-based OPC; Plug & produce; Multi agent systems
National Category
Robotics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-21197 (URN)10.1109/ETFA54631.2023.10275691 (DOI)2-s2.0-85175465641 (Scopus ID)979-8-3503-3991-8 (ISBN)979-8-3503-3990-1 (ISBN)979-8-3503-3992-5 (ISBN)
Conference
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
Available from: 2024-01-19 Created: 2024-01-19 Last updated: 2024-01-19Bibliographically approved
Ramasamy, S., Bennulf, M., Zhang, X., Hammar, S. & Danielsson, F. (2023). Online Path Planning in a Multi-agent-Controlled Manufacturing System. Paper presented at 31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, Detroit, 19 June 2022, through 23 June 2022 Code 285199. Lecture Notes in Mechanical Engineering, 124-134
Open this publication in new window or tab >>Online Path Planning in a Multi-agent-Controlled Manufacturing System
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2023 (English)In: Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364, p. 124-134Article in journal (Refereed) Published
Abstract [en]

In recent years the manufacturing sectors are migrating from mass production to mass customization. To be able to achieve mass customization, manufacturing systems are expected to be more flexible to accommodate the different customizations. The industries which are using the traditional and dedicated manufacturing systems are expensive to realize this transition. One promising approach to achieve flexibility in their production is called Plug & Produce concept which can be realized using multi-agent-based controllers. In multi-agent systems, parts and resources are usually distributed logically, and they communicate with each other and act as autonomous agents to achieve the manufacturing goals. During the manufacturing process, an agent representing a robot can request a path for transportation from one location to another location. To address this transportation facility, this paper presents the result of a futuristic approach for an online path planning algorithm directly implemented as an agent in a multi-agent system. Here, the agent systems can generate collision-free paths automatically and autonomously. The parts and resources can be configured with a multi-agent system in the manufacturing process with minimal human intervention and production downtime, thereby achieving the customization and flexibility in the production process needed. 

Place, publisher, year, edition, pages
Springer, 2023
Keywords
Autonomous agents; Computer aided manufacturing; Motion planning; Online systems; Customisation; Manufacturing process; Manufacturing sector; Mass customization; Mass production; Multi agent; On-line path planning; Path planner service; Path planners; Plug & produce; Multi agent systems
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-19432 (URN)10.1007/978-3-031-18326-3_13 (DOI)2-s2.0-85141873498 (Scopus ID)
Conference
31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, Detroit, 19 June 2022, through 23 June 2022 Code 285199
Funder
Knowledge Foundation, 20200036
Note

CC-BY 4.0

The work was funded by PoPCoRN project by KK-stiftelsen, Sweden.

31st International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022; Conference date: 19 June 2022 through 23 June 2022; Conference code: 285199

Available from: 2023-09-12 Created: 2023-09-12 Last updated: 2024-01-18Bibliographically approved
Massouh, B., Ramasamy, S., Svensson, B. & Danielsson, F. (2022). A Framework for Hazard Identification of a Collaborative Plug&Produce System. Paper presented at 4th International Conference on Intelligent Technologies and Applications, INTAP 2021; Conference date: 11 October 2021 through 13 October 2021; Conference code: 281209. Communications in Computer and Information Science, 1616 CCIS, 144-155
Open this publication in new window or tab >>A Framework for Hazard Identification of a Collaborative Plug&Produce System
2022 (English)In: Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937, Vol. 1616 CCIS, p. 144-155Article in journal (Refereed) Published
Abstract [en]

Plug&Produce systems accept reconfiguration and have the attribute of physical and logical flexibility. To implement the Plug&Produce system in a manufacturing plant, there is a need to assure that the system is safe. The process of risk assessment provides information that is used to implement the proper safety measures to ensure human and machine safety. An important step in the risk assessment process is hazard identification. Hazard identification of Plug&Produce system is unique as the hazard identification method provided in the safety standards do not consider system flexibility. In this paper, a framework for hazard identification of a collaborative Plug&Produce system is presented. A study case that includes a collaborative Plug&Produce system is presented and the framework is applied to identify the system’s hazards. Also, the generalisation of the framework application is discussed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2022
Keywords
Collaborative robots; Hazards; Assessment process; Collaborative robots; Hazard identification; Human safety; Identification method; Machine safety; Manufacturing plant; Plug&produce; Risks assessments; Safety measures; Risk assessment
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-19172 (URN)10.1007/978-3-031-10525-8_12 (DOI)2-s2.0-85135037497 (Scopus ID)
Conference
4th International Conference on Intelligent Technologies and Applications, INTAP 2021; Conference date: 11 October 2021 through 13 October 2021; Conference code: 281209
Available from: 2022-11-08 Created: 2022-11-08 Last updated: 2024-01-30Bibliographically approved
Bennulf, M., Danielsson, F. & Svensson, B. (2022). A Method for Configuring Agents in Plug & Produce Systems. In: Amos H.C. Ng, Anna Syberfeldt, Dan Högberg, Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium, SPS 2022; Conference date: 26 April 2022 through 29 April 2022; Conference code: 179964 (pp. 135-146). IOS Press, 21
Open this publication in new window or tab >>A Method for Configuring Agents in Plug & Produce Systems
2022 (English)In: SPS2022: Proceedings of the 10th Swedish Production Symposium / [ed] Amos H.C. Ng, Anna Syberfeldt, Dan Högberg, Magnus Holm, IOS Press, 2022, Vol. 21, p. 135-146Conference paper, Published paper (Refereed)
Abstract [en]

Multi-agent technology, used for implementing Plug & Produce systems have many proposed benefits for fast adaption of manufacturing systems. However, still today multi-agent technology is not ready for the industry, due to the lack of mature supporting tools and guidelines. The result is that today, multi-agent systems are more complicated and time-consuming to use than traditional approaches. This hides their true benefits. In this paper, a new method for configuring agents is presented that includes automated deployment to manufacturing systems and by its flexible design opens the possibility to connect many other supporting tools when needed. A configuration tool is also designed that works with the proposed method by connecting to an agent configuration database. The overall aim of the method is to simplify the steps taken for adapting a manufacturing system for new parts and resources.  

Place, publisher, year, edition, pages
IOS Press, 2022
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528
Keywords
Industry 4.0; Configuration; Configuration database; Deployment; Flexible designs; Multi-agent technologies; Plug & produce; Supporting tool; Traditional approaches; Multi agent systems
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-19198 (URN)10.3233/ATDE220133 (DOI)2-s2.0-85132824747 (Scopus ID)978-1-64368-268-6 (ISBN)978-1-64368-269-3 (ISBN)
Conference
10th Swedish Production Symposium, SPS 2022; Conference date: 26 April 2022 through 29 April 2022; Conference code: 179964
Funder
Knowledge Foundation, 20201192
Note

This paper was written as part of the PoPCoRN project, funded by the K-K foundation and the Miljö för Flexibel och Innovativ Automation, Project reference: 20201192, Funded under: Europeiska regionala utvecklingsfonden/VGR.

Distributed under the termsof the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0

Available from: 2022-12-05 Created: 2022-12-05 Last updated: 2023-01-05
Eriksson, K. M., Ramasamy, S., Zhang, X., Wang, Z. & Danielsson, F. (2022). Conceptual framework of scheduling applying discrete event simulation as an environment for deep reinforcement learning. Paper presented at 55th CIRP Conference on Manufacturing Systems. Procedia CIRP, 107, 955-960
Open this publication in new window or tab >>Conceptual framework of scheduling applying discrete event simulation as an environment for deep reinforcement learning
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2022 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 107, p. 955-960Article in journal (Refereed) Published
Abstract [en]

Increased environmental awareness is driving the manufacturing industry towards novel ways of energy reduction to become sustainable yet stay competitive. Climate and enviromental challenges put high priority on incorporating aspects of sustainability into both strategic and operational levels, such as production scheduling, in the manufacturing industry. Considering energy as a parameter when planning makes an already existing highly complex task of production scheduling even more multifaceted. The focus in this study is on inverse scheduling, defined as the problem of finding the number of jobs and duration times to meet a fixed input capacity. The purpose of this study was to investigate how scheduling can be formulated, within the environment of discrete event simulation coupled with reinforcement learning, to meet production demands while simultaneously minimize makespan and reduce energy. The study applied the method of modeling a production robot cell with its uncertainties, using discrete event simulation combined with deep reinforcement learning and trained agents. The researched scheduling approach derived solutions that take into consideration the performance measures of energy use. The method was applied and tested in a simulation environment with data from a real robot production cell. The study revealed opportunities for novel approaches of studying and reducing energy in the manufacturing industry. Results demonstrated a move towards a more holistic approach for production scheduling, which includes energy usage, that can aid decision-making and facilitate increased sustainability in production. We propose a conceptual framework for scheduling for minimizing energy use applying discrete event simulation as an environment for deep reinforcement learning.

Keywords
Reinforcement learning; Discrete event simulation; Energy optimal scheduling; Inverse scheduling; Industty 4.0
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Work Integrated Learning; Production Technology
Identifiers
urn:nbn:se:hv:diva-18474 (URN)10.1016/j.procir.2022.05.091 (DOI)
Conference
55th CIRP Conference on Manufacturing Systems
Note

The work was carried out at the Production Technology Centre at University West, Sweden supported by the Swedish Governmental Agency for Innovation Systems (Vinnova) under the project SmoothIT and by the KK Foundation under the project Artificial and Human Intelligence through Learning (AHIL). Their support is gratefully acknowledged. Assistance provided by Master's students Maria Vincenta Vivo and Mohammadali Zakeriharandi was greatly appreciated. 

Available from: 2022-06-13 Created: 2022-06-13 Last updated: 2022-06-13
Nilsson, A., Danielsson, F., Bennulf, M. & Svensson, B. (2021). A Classification of Different Levels of Flexibility in an Automated Manufacturing System and Needed Competence. In: Ann-Louise Andersen, Rasmus Andersen, Thomas Ditlev Brunoe, Maria Stoettrup Schioenning Larsen, Kjeld Nielsen, Alessia Napoleone, Stefan Kjeldgaard (Ed.), Ann-Louise Andersen, Rasmus Andersen, Thomas Ditlev Brunoe, Maria Stoettrup Schioenning Larsen, Kjeld Nielsen, Alessia Napoleone, Stefan Kjeldgaard (Ed.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2021) and the 10th World Mass Customization & Personalization Conference (MCPC2021), Aalborg, Denmark, October/November 2021. Paper presented at 8th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2021) and the 10th World Mass Customization & Personalization Conference (MCPC2021), Aalborg, Denmark, October/November 2021 (pp. 27-34). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>A Classification of Different Levels of Flexibility in an Automated Manufacturing System and Needed Competence
2021 (English)In: Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2021) and the 10th World Mass Customization & Personalization Conference (MCPC2021), Aalborg, Denmark, October/November 2021 / [ed] Ann-Louise Andersen, Rasmus Andersen, Thomas Ditlev Brunoe, Maria Stoettrup Schioenning Larsen, Kjeld Nielsen, Alessia Napoleone, Stefan Kjeldgaard, Springer Science and Business Media Deutschland GmbH , 2021, p. 27-34Conference paper, Published paper (Refereed)
Abstract [en]

Mass customization has become more attractive but requires a transformation towards more flexible solutions in contrast to dedicated manufacturing systems. Flexibility includes complex tasks such as the introduction of new products or new manufacturing processes as well as to efficiently handle daily balancing. The main challenge when it comes to flexibility in manufacturing is to be able to handle the technical aspects and still be competitive. In this article we consider the cost for flexibility to include two main things; (1) setup time, e.g., time for planning, design, programming and configuration, installation, ramp-up, scrapping of old equipment, preparation of facility, hardware installation, and (2) need of competence, inhouse knowledge, external competence, or external expert competence. This article presents an overview of available solutions and the level of flexibility and the level of competence that is needed for a reconfiguration one can expect out of a specific solution. Further, most of the existing solutions found do not consider or address the full problem of flexibility. However, we describe a possible future of industrial concept: Plug & Produce, which can address flexibility within manufacturing more completely and sustainably over time. Methods for configuration instead of programming are developed by University West. 

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2021
Keywords
Plug & Produce, Flexibility, Re-configurability, Automation Competence
National Category
Production Engineering, Human Work Science and Ergonomics Control Engineering
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-17889 (URN)10.1007/978-3-030-90700-6_2 (DOI)2-s2.0-85119450410 (Scopus ID)978-3-030-90700-6 (ISBN)
Conference
8th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2021) and the 10th World Mass Customization & Personalization Conference (MCPC2021), Aalborg, Denmark, October/November 2021
Available from: 2021-12-22 Created: 2021-12-22 Last updated: 2023-10-30Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-6604-6904

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