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| 2. |
- Gernhardt, Benjamin, et al.
(författare)
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A SEMANTIC REPRESENTATION FOR PROCESS-ORIENTED KNOWLEDGE MANAGEMENT BASED ON FUNCTIONBLOCK DOMAIN MODELS SUPPORTING DISTRIBUTED AND COLLABORATIVE PRODUCTION PLANNING
- 2015
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Ingår i: PROCEEDINGS OF THE ASME 10TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2015, VOL 2. - : AMER SOC MECHANICAL ENGINEERS.
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Konferensbidrag (refereegranskat)abstract
- Semantic knowledge representation, management, sharing, access, and re-use approaches can support collaborative production planning in a flexible and efficient as well as an effective way. Therefore, semantic-technology based representations of Collaborative Production Process Planning (CAPP) knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based semantic-enabled knowledge repositories supporting CAPP scenarios as required in the CAPP4SMES project [1]. Beyond that, Small and Medium Enterprises (SMEs) as represented in CAPP4SMES request for a standardized CAPP-oriented product-knowledge- and production-feature representation that can be achieved by applying function-block based knowledge representation models. Semantic Web- and at the same time Cloud-based technologies, tool suites and application solutions which are based on process-oriented semantic knowledge representation methodologies such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozesess-orientiertes Innovationsmanagement, WPIM) [2] can satisfy these needs, supporting the semantic integration, management, access and re-use in a machine readable and integrated representation of distributed CAPP knowledge that is shared within a cloud-based centralized semantic-enabled knowledge repository. Furthermore semantic knowledge representation and querying add value to knowledge-based and computer-aided re-use of such knowledge within CAPP activities and, finally, pave the way towards further automating planning, simulation and optimization support in a semantic web for CAPP.
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| 3. |
- Gernhardt, Benjamin, et al.
(författare)
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A Semantic Representation for Process-Oriented Knowledge Management to Support Production Planning based on Function Block Domain Models and a Three-level Mediator Architecture
- 2015
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Konferensbidrag (refereegranskat)abstract
- Semantic knowledge representation, management, sharing, access, and re-use approaches can support collaborative production planning in a flexible and efficient as well as an effective way. Therefore, semantic-technology based representations of Collaborative Production Process Planning (CAPP) knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based semantic-enabled knowledge repositories supporting CAPP scenarios as required in the CAPP4SMES project [1]. Beyond that, Small and Medium Enterprises (SMEs) as represented in CAPP4SMES request for a standardized CAPP-oriented product-knowledge- and production-feature representation that can be achieved by applying function-block based knowledge representation models. Semantic Web- and at the same time Cloud-based technologies, tool suites and application solutions which are based on process-oriented semantic knowledge representation methodologies such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozesess-orientiertes Innovationsmanagement, WPIM) [2] can satisfy these needs, supporting the semantic integration, management, access and re-use in a machine readable and integrated representation of distributed CAPP knowledge that is shared within a cloud-based centralized semantic-enabled knowledge repository. Furthermore semantic knowledge representation and querying add value to knowledge-based and computer-aided re-use of such knowledge within CAPP activities and, finally, pave the way towards further automating planning, simulation and optimization support in a semantic web for CAPP.
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| 4. |
- Gernhardt, Benjamin, et al.
(författare)
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IMPLEMENTATION OF A KNOWLEDGE-BASED PRODUCTION PLANNING INCLUDING A DIRECT MANIPULATIVE PROCESS EDITOR AND A MEDIATOR ARCHITECTURE
- 2017
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Ingår i: PROCEEDINGS OF THE ASME 12TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE - 2017, VOL 3. - : AMER SOC MECHANICAL ENGINEERS.
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Konferensbidrag (refereegranskat)abstract
- Today, in the era of modern Intelligent Production Environments (IPE) and Industry 4.0, the manufacturing of a product takes place in various partial steps and these mostly in different locations, potentially distributed all over the world. The producing companies must assert in the global market and always find new ways to cut costs by saving tax, changing to the best providers, and by using the most efficient and fastest production processes. Furthermore, they must be inevitably based on a cloud-based repository and distributed architectures to make data and information accessible everywhere as well as development processes and knowledge available for a worldwide cooperation. A so called Collaborative Adaptive (Production) Process Planning (CAPP) can be supported by semantic approaches for knowledge representation and management as well as knowledge sharing, access, and re-use in a flexible and efficient way. In this way, to support CAPP scenarios, semantic representations of such knowledge integrated into a machine-readable process formalization is a key enabling factor for sharing in cloud-based knowledge repositories. This is especially required for, e.g., Small and Medium Enterprises (SMEs). When SMEs work together on a production planning for a joint product, they exchange component production and manufacturing change information between different planning subsystems. These exchanges are mostly based on the already well-established Standard for the Exchange of Product model data (STEP), not least to obtain a computer-interpretable representation. Moreover, so-called Function Block (FB) Domain Models could support these planning process. FBs serve as a high-level planning-process knowledge-resource template and to the representation of knowledge. Furthermore, methodologies are required, which based on process-oriented semantic knowledge-representation, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM). WPIM is already a web and cloud-based tool suites and can represent such planning processes and their knowledge resources and can therefore be used to support the integration and the management of distributed CAPP knowledge in Manufacturing Change Management (MCM), as well as its access and re-use. That is also valid for Assembly-, Logistics- and Layout Planning (ALLP). On the one hand, a collaborative planning in a machine-readable and integrated representation will be possible as well as an optimization for mass production. On the other hand, within a cloud-based semantic knowledge repository, that knowledge can be shared with all partners and contributors. To combine all these functionalities, in 2016 we have already introduced a method, called Knowledge-based Production Planning (KPP). We outlined the theoretical advantages of integrating CAPP with Collaborative Manufacturing Change Management (CMCM) in the last year at MSEC16. In this Paper, we will demonstrate our first implementations of the KPP application with an integrated visual direct manipulative process editor as well as a first prototype of our mediator architecture with a semantic integration including a query library based on the KPP ontology.
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| 5. |
- Gernhardt, Benjamin, et al.
(författare)
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Knowledge-Based Production Planning Within the Reference Planning Process Supporting Manufacturing Change Management
- 2016
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Ingår i: Proceedings of the ASME 11TH International Manufacturing Science and Engineering Conference, 2016, VOL 2. - : AMER SOC MECHANICAL ENGINEERS.
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Konferensbidrag (refereegranskat)abstract
- The manufacturing of a product takes place in several partial steps and these mostly in different locations to save tax or to use the best providers. Therefore, in the era of Internet of Things (IoT) and modem Intelligent Production Environments (IPE) are going to be inevitably based on a cloud-based repository and distributed architecture to make data and information accessible everywhere as well as development processes and knowledge available for worldwide cooperation. Semantic approaches for knowledge representation and management as well as knowledge sharing, access, and re-use can support Collaborative Adaptive Production Process Planning (CAPP) in a flexible, efficient, and effective way. Thus, semantic representations of such CAPP knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based knowledge repositories supporting CAPP scenarios as required for e.g., Small and Medium Enterprises (SMEs). When such contributors work together on a product component production planning, they exchange component production and manufacturing change information between different planning subsystems which require, e.g., a standardized product-feature and production-machine feature representation. These data exchanges are mostly based on applying the already established Standard for the Exchange of Product model data (STEP) for the computer-interpretable representation and exchange of product manufacturing information. Furthermore, the planning process can be supported by so-called Function Block (FB) based knowledge representation models, serving as a high-level planning-process knowledge-resource template. Web-based and at the same time Cloud-based tool suites, which are based on process-oriented semantic knowledge-representation methodologies, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM) can satisfy the needs of representing such planning processes and their knowledge resources. In this way, WPIM can be used to support the integration and management of distributed CAPP knowledge, as well as its access and re-use in Manufacturing Change Management (MCM) including Assembly-, Logistics and Layout Planning (ALLP). Therefore, also a collaborative planning and optimization for mass production in a machine readable and integrated representation is possible. On the other hand, that knowledge can be shared within a cloud-based semantic knowledge repository. To integrate all these functionalities, this paper introduces a new method, called Knowledge-based Production Planning (KPP) and outlines the advantages of integrating CAPP with Collaborative Manufacturing Change Management (CMCM). In this way, an enabling basis for achieving ALLP interoperability in Distributed Collaborative Manufacturing and Logistics will be demonstrated.
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| 6. |
- Gernhardt, Benjamin, et al.
(författare)
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Supporting production planning through semantic mediation of processing functionality
- 2016
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Konferensbidrag (refereegranskat)abstract
- Semantic approaches for knowledge representation and management as well as knowledge sharing, access and re-use can support Collaborative Adaptive Production Process Planning (CAPP) in a flexible, efficient and effective way. Therefore, semantic representations of such CAPP knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based knowledge repositories supporting CAPP scenarios as required in the CAPP-4-SMEs project. Beyond that, Small and Medium Enterprises (SMEs) as represented in CAPP-4-SMEs request for a standardized production-feature representation. That can be achieved by applying so-called Function Block (FB) based knowledge representation models. Web-based and at the same time Cloud-based tool suites which are based on process-oriented semantic knowledge-representation methodologies, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM) can satisfy these needs. In this way, WPIM can be applied to support the integration and management of distributed CAPP knowledge, as well as its access and re-use in a machine readable and integrated representation. On the other hand, that knowledge can be shared within a cloud-based semantic knowledge repository. Furthermore, semantic knowledge representation and querying will add value to the knowledge-based and computer-aided re-use of such machine-readable knowledge resources within CAPP activities. Finally, it will pave the way towards further automating planning, simulation and optimization in a semantic-web for CAPP.
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| 7. |
- Schafmayer, Clemens, et al.
(författare)
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Genome-wide association analysis of diverticular disease points towards neuromuscular, connective tissue and epithelial pathomechanisms
- 2019
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Ingår i: Gut. - : BMJ. - 0017-5749 .- 1468-3288. ; 68:5, s. 854-865
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Tidskriftsartikel (refereegranskat)abstract
- Objective Diverticular disease is a common complex disorder characterised by mucosal outpouchings of the colonic wall that manifests through complications such as diverticulitis, perforation and bleeding. We report the to date largest genome-wide association study (GWAS) to identify genetic risk factors for diverticular disease. Design Discovery GWAS analysis was performed on UK Biobank imputed genotypes using 31 964 cases and 419 135 controls of European descent. Associations were replicated in a European sample of 3893 cases and 2829 diverticula-free controls and evaluated for risk contribution to diverticulitis and uncomplicated diverticulosis. Transcripts at top 20 replicating loci were analysed by real-time quatitative PCR in preparations of the mucosal, submucosal and muscular layer of colon. The localisation of expressed protein at selected loci was investigated by immunohistochemistry. Results We discovered 48 risk loci, of which 12 are novel, with genome-wide significance and consistent OR in the replication sample. Nominal replication (p< 0.05) was observed for 27 loci, and additional 8 in meta-analysis with a population-based cohort. The most significant novel risk variant rs9960286 is located near CTAGE1 with a p value of 2.3x10-10 and 0.002 (OR allelic = 1.14 (95% CI 1.05 to 1.24)) in the replication analysis. Four loci showed stronger effects for diverticulitis, PHGR1 (OR 1.32, 95% CI 1.12 to 1.56), FAM155A-2 (OR 1.21, 95% CI 1.04 to 1.42), CALCB (OR 1.17, 95% CI 1.03 to 1.33) and S100A10 (OR 1.17, 95% CI 1.03 to 1.33). Conclusion I n silico analyses point to diverticulosis primarily as a disorder of intestinal neuromuscular function and of impaired connective fibre support, while an additional diverticulitis risk might be conferred by epithelial dysfunction.
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| 8. |
- Vogel-Heuser, B., et al.
(författare)
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Selected challenges of software evolution for automated production systems
- 2015
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Ingår i: 13th International Conference on Industrial Informatics, INDIN 2015, Robinson College, Cambridge, United Kingdom, 22 - 24 July 2015. - : IEEE. - 9781479966493
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Konferensbidrag (refereegranskat)abstract
- Automated machines and plants are operated for some decades and undergo an everlasting evolution during this time. In this paper, we present three related open evolution challenges focusing on software evolution in the domain of automated production systems, i.e. evolution and co-evolution of (interdisciplinary) engineering models and code, quality assurance as well as variant and version management during evolution.
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| 9. |
- Vogel-Heuser, B., et al.
(författare)
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Technical debt in Automated Production Systems
- 2015
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Ingår i: 7th International Workshop on Managing Technical Debt, MTD 2015, Bremen, Germany. - 9781467373784 ; , s. 49-52
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Konferensbidrag (refereegranskat)abstract
- The term technical debt borrowed from financial debt describes the long-term negative effects of sub-optimal solutions to achieve short-term benefits. It has been widely studied so far in pure software systems. However, there is a lack of studies on technical debt in technical systems, which contain mechanical, electrical and software parts. Automated Production Systems are such technical systems. In this position paper, we introduce technical debt for Automated Production Systems and give examples from the different disciplines. Based on that description, we outline future research directions on technical debt in this field.
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