| 21. |
- Adamson, Göran, 1958-
(författare)
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A Novel Method for Adaptive Control of Manufacturing Equipment in Cloud Environments
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The ability to adaptively control manufacturing equipment, both in local and distributed environments, is becoming increasingly more important for many manufacturing companies.One important reason for this is that manufacturing companies are facing increasing levels of changes, variations and uncertainty, caused by both internal and external factors, which can negatively impact their performance. Frequently changing consumer requirements and market demands usually lead to variations in manufacturing quantities, product design and shorter product life-cycles. Variations in manufacturing capability and functionality, such as equipment breakdowns, missing/worn/broken tools and delays, also contribute to a high level of uncertainty. The result is unpredictable manufacturing system performance, with an increased number of unforeseen events occurring in these systems. Events which are difficult for traditional planning and control systems to satisfactorily manage.For manufacturing scenarios such as these, the use of real-time manufacturing information and intelligence is necessary to enable manufacturing activities to be performed according to actual manufacturing conditions and requirements, and not according to a pre-determined process plan. Therefore, there is a need for an event-driven control approach to facilitate adaptive decision-making and dynamic control capabilities.Another reason driving the move for adaptive control of manufacturing equipment is the trend of increasing globalization, which forces manufacturing industry to focus on more cost-effective manufacturing systems and collaboration within global supply chains and manufacturing networks. Cloud Manufacturing is evolving as a new manufacturing paradigm to match this trend, enabling the mutually advantageous sharing of resources, knowledge and information between distributed companies and manufacturing units. One of the crucial objectives for Cloud Manufacturing is the coordinated planning, control and execution of discrete manufacturing operations in collaborative and networked environments. Therefore, there is also a need that such an event-driven control approach supports the control of distributed manufacturing equipment.The aim of this research study is to define and verify a novel and comprehensive method for adaptive control of manufacturing equipment in cloud environments.The presented research follows the Design Science Research methodology. From a review of research literature, problems regarding adaptive manufacturing equipment control have been identified. A control approach, building on a structure of event-driven Manufacturing Feature Function Blocks, supported by an Information Framework, has been formulated. The Function Block structure is constructed to generate real-time control instructions, triggered by events from the manufacturing environment. The Information Framework uses the concept of Ontologies and The Semantic Web to enable description and matching of manufacturing resource capabilities and manufacturing task requests in distributed environments, e.g. within Cloud Manufacturing. The suggested control approach has been designed and instantiated, implemented as prototype systems for both local and distributed manufacturing scenarios, in both real and virtual applications. In these systems, event-driven Assembly Feature Function Blocks for adaptive control of robotic assembly tasks have been used to demonstrate the applicability of the control approach. The utility and performance of these prototype systems have been tested, verified and evaluated for different assembly scenarios.The proposed control approach has many promising characteristics for use within both local and distributed environments, such as cloud environments. The biggest advantage compared to traditional control is that the required control is created at run-time according to actual manufacturing conditions.The biggest obstacle for being applicable to its full extent is manufacturing equipment controlled by proprietary control systems, with native control languages. To take the full advantage of the IEC Function Block control approach, controllers which can interface, interpret and execute these Function Blocks directly, are necessary.
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| 22. |
- Adamson, Göran, 1958-, et al.
(författare)
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Adaptive Robot Control as a Service in Cloud Manufacturing
- 2015
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Ingår i: ASME 2015 International Manufacturing Science and Engineering Conference. - : ASME Press. - 9780791856833 ; , s. Paper No. MSEC2015-9479-
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Konferensbidrag (refereegranskat)abstract
- The interest for implementing the concept of Manufacturing-as-a-Service is increasing as concepts for letting the manufacturing shop-floor domain take advantage of the cloud appears. Combining technologies such as Internet of Things, Cloud Computing, Semantic Web, virtualisation and service-oriented technologies with advanced manufacturing models, information and communication technologies, Cloud Manufacturing (CM) is emerging as a new manufacturing paradigm. The ideas of on-demand, scalable and pay-for-usage resource-sharing in this concept will move manufacturing towards distributed and collaborative missions in volatile partnerships. This will require a control approach for distributed planning and execution of cooperating manufacturing activities. Without control based on both global and local environmental conditions, the advantages of CM will not be fulfilled.By utilising smart and distributable decision modules such as event-driven FBs, run-time manufacturing operations in a distributed environment may be adjusted to prevailing manufacturing conditions. Packaged in a cloud service for manufacturing equipment control, it will satisfy the control needs in CM. By combining different resource types, such as hard, soft and capability resources, the cloud service Robot Control-as-a-Service can be realised.This paper describes the functional perspective and enabling technologies for a control approach for robotic assembly tasks in CM, and describes a scenario for its implementation.
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| 23. |
- Adamson, Göran, 1958-, et al.
(författare)
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Cloud Manufacturing : A Critical Review of Recent Development and Future Trends
- 2017
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Ingår i: International journal of computer integrated manufacturing (Print). - : Taylor & Francis Group. - 0951-192X .- 1362-3052. ; 30:4-5, s. 347-380
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Tidskriftsartikel (refereegranskat)abstract
- There is an on-going paradigm shift in manufacturing, in which modern manufacturing industry is changing towards global manufacturing networks and supply chains. This will lead to the flexible usage of different globally distributed, scalable and sustainable, service-oriented manufacturing systems and resources. Combining recently emerged technologies, such as Internet of Things, Cloud Computing, Semantic Web, service-oriented technologies, virtualisation and advanced high-performance computing technologies, with advanced manufacturing models and information technologies, Cloud Manufacturing is a new manufacturing paradigm built on resource sharing, supporting and driving this change.It is envisioned that companies in all sectors of manufacturing will be able to package their resources and know-hows in the Cloud, making them conveniently available for others through pay-as-you-go, which is also timely and economically attractive. Resources, e.g. manufacturing software tools, applications, knowledge and fabrication capabilities and equipment, will then be made accessible to presumptive consumers on a worldwide basis.Cloud Manufacturing has been in focus for a great deal of research interest and suggested applications during recent years, by both industrial and academic communities. After surveying a vast array of available publications, this paper presents an up-to-date literature review together with identified outstanding research issues, and future trends and directions within Cloud Manufacturing.
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| 24. |
- Adamson, Göran, et al.
(författare)
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Feature-Based Adaptive Manufacturing Equipment Control for Cloud Environments
- 2016
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Ingår i: Proceedings of the ASME 11th International Manufacturing Science and Engineering Conference, 2016, vol 2. - : American Society of Mechanical Engineers (ASME). - 9780791849903
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Konferensbidrag (refereegranskat)abstract
- The ideas of on-demand, scalable and pay-for-usage resource-sharing in Cloud Manufacturing are steadily attracting more interest. For implementing the concept of Manufacturing as-a-Service in a cloud environment, description models and implementation language for resources and their capabilities are required. A standardized approach for systemived virtualization, servisilisation, retrieval, selection and composition into higher levels of functionality is necessary. For the collaborative sharing and use of networked manufacturing resources there is also a need for a control approach for distributed manufacturing equipment. In this paper, the technological perspective for an adaptive cloud service-based control approach is described, and a supporting information model for its implementation. The control is realized through the use of a network of intelligent and distributable Function Block decision modules, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system's integration to the cloud service management functionality is described, as well as a feature-level capability model and the use of ontologies and the Semantic Web.
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| 25. |
- Adamson, Göran, 1958-, et al.
(författare)
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Feature-based control and information framework for adaptive and distributed manufacturing in cyber physical systems
- 2017
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Ingår i: Journal of manufacturing systems. - : Elsevier. - 0278-6125 .- 1878-6642. ; 43, s. 305-315
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Tidskriftsartikel (refereegranskat)abstract
- Modern distributed manufacturing within Industry 4.0, supported by Cyber Physical Systems (CPSs), offers many promising capabilities regarding effective and flexible manufacturing, but there remain many challenges which may hinder its exploitation fully. One major issue is how to automatically control manufacturing equipment, e.g. industrial robots and CNC-machines, in an adaptive and effective manner. For collaborative sharing and use of distributed and networked manufacturing resources, a coherent, standardised approach for systemised planning and control at different manufacturing system levels and locations is a paramount prerequisite.In this paper, the concept of feature-based manufacturing for adaptive equipment control and resource-task matching in distributed and collaborative CPS manufacturing environments is presented. The concept has a product perspective and builds on the combination of product manufacturing features and event-driven Function Blocks (FB) of the IEC 61499 standard. Distributed control is realised through the use of networked and smart FB decision modules, enabling the performance of collaborative run-time manufacturing activities according to actual manufacturing conditions. A feature-based information framework supporting the matching of manufacturing resources and tasks, as well as the feature-FB control concept, and a demonstration with a cyber-physical robot application, are presented.
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| 26. |
- Adamson, Göran, 1958-, et al.
(författare)
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Feature-based Function Block Control Framework for Manufacturing Equipment in Cloud Environments
- 2018
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Ingår i: International Journal of Production Research. - : Taylor & Francis. - 0020-7543 .- 1366-588X. ; 57:12, s. 3954-3974
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Tidskriftsartikel (refereegranskat)abstract
- The ability to adaptively control manufacturing equipment in cloud environments is becoming increasingly more important. Industry 4.0, supported by Cyber Physical Systems and the concept of on-demand, scalable and pay-for-usage resource-sharing in cloud environments offers many promises regarding effective and flexible manufacturing. For implementing the concept of manufacturing services in a cloud environment, a cloud control approach for the sharing and control of networked manufacturing resources is required. This paper presents a cloud service-based control approach which has a product perspective and builds on the combination of event-driven IEC 61499 Function Blocks and product manufacturing features. Distributed control is realised through the use of a networked control structure of such Function Blocks as decision modules, enabling an adaptive run-time behaviour. The control approach has been developed and implemented as prototype systems for both local and distributed manufacturing scenarios, in both real and virtual applications. An application scenario is presented to demonstrate the applicability of the control approach. In this scenario, Assembly Feature-Function Blocks for adaptive control of robotic assembly tasks have been used.
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| 27. |
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Advanced Information Systems Engineering Workshops : CAiSE 2015 International Workshops, Stockholm, Sweden, June 8-9, 2015, Proceedings
- 2015
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Proceedings (redaktörskap) (refereegranskat)abstract
- This book constitutes the thoroughly refereed proceedings of seven international workshops held in Stockholm, Sweden, in conjunction with the 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015, in June 2015.The 38 full and nine short papers were carefully selected from 107 submissions.The workshops were the Second International Workshop on Advances in Services Design based on the Notion of Capability (ASDENCA), the Third International Workshop on Cognitive Aspects of Information Systems Engineering (COGNISE), the First International Workshop on Digital Business Innovation and the Future Enterprise Information Systems Engineering (DiFenSE), the First International Workshop on Enterprise Modeling (EM), the First Workshop on the Role of Real-World Objects in Business Process Management Systems (RW-BPMS), the 10th International Workshop on Trends in Enterprise Architecture Research (TEAR), and the 5th International Workshop on Information Systems Security Engineering (WISSE).
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| 28. |
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Advances in Conceptual Modeling : ER 2015 Workshops, AHA, CMS, EMoV, MoBiD, MORE-BI, MReBA, QMMQ, and SCME Stockholm, Sweden, October 19–22, 2015, Proceedings
- 2015
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Proceedings (redaktörskap) (refereegranskat)abstract
- PrefaceWelcome to the proceedings of the workshops held during the 34th InternationalConference on Conceptual Modeling (ER conference 2015) in Stockholm, Sweden.Workshops offer an incremental exploration of cutting-edge research issues thatbecome prominent in the future. The ER conference has a long tradition of thought-provoking and state-of-the-art workshops. This year we had a rich combination ofseven workshops and a special symposium on conceptual modeling education.We attracted 52 paper submissions for all the workshops, of which 26 wereaccepted. These workshops also have invited papers along with papers from thesymposium on conceptual modeling education.This volume comprises contributions from the following workshops:AHA 2015–Conceptual Modeling for Ambient Assistance and Healthy AgeingCMS 2015–Conceptual Modeling of ServicesEMoV 2015–Event Modeling and Processing in Business Process ManagementMoBiD 2015–Modeling and Management of Big DataMORE-BI 2015–Modeling and Reasoning for Business IntelligenceMReBA 2015–Conceptual Modeling in Requirements Engineering and Business AnalysisQMMQ 2015–Quality of Modeling and Modeling of QualitySCME 2015–Symposium on Conceptual Modeling Education
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| 29. |
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| 30. |
- Aggestam, Lena
(författare)
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Knowledge Leakage when SMEs Participate in Supply Chains : What Is It About and How Can It Occur?
- 2016
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Ingår i: International Journal of Knowledge and Systems Science (IJKSS). - : IGI Global. - 1947-8208. ; 7:3, s. 30-45
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Tidskriftsartikel (refereegranskat)abstract
- The advantages of sharing knowledge when participating in a Supply Chain (SC) are well established in the literature, but the challenge of knowledge leakage, and how to manage it, is still in its infancy. In order to increase the understanding of knowledge leakage, when SMEs participate in SCs, this study describes types of knowledge that may leak away, how they are valued, and how knowledge leakage can occur. The result includes two frameworks that also have shown to be potentially useful for examining the maturity of a specific SME with regard to knowledge leakages when participating in the SC.
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