scholarly journals Process-oriented Knowledge Representation of the Requirement Management Phase of TOGAF-ADM: an Empirical Evaluation

2021 ◽  
Vol 192 ◽  
pp. 2239-2248
Author(s):  
Elena Kornyshova ◽  
Judith Barrios
Author(s):  
Benjamin Gernhardt ◽  
Tobias Vogel ◽  
Mohammad Givehchi ◽  
Lihui Wang ◽  
Matthias Hemmje

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 modern 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.


Author(s):  
Benjamin Gernhardt ◽  
Franz Miltner ◽  
Tobias Vogel ◽  
Holger Brocks ◽  
Matthias Hemmje ◽  
...  

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.


Author(s):  
Benjamin Gernhardt ◽  
Tobias Vogel ◽  
Lihui Wang ◽  
Matthias Hemmje

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.


2013 ◽  
Vol 336-338 ◽  
pp. 2175-2181
Author(s):  
Jian Zhang ◽  
Fei Feng ◽  
Yu Liu ◽  
Nan Wang

Recent research on knowledge representation demonstrated that the more clearly domain concepts, the higher accuracy of the information extraction. Accounting that the ontology with an advantage in the aspects of the concept representation, it can be introduced to the Salt Lake domain to construct the domain ontology, and will convenience for the future of information extraction and retrieval. The main contribution of this paper is to propose a process-oriented domain ontology construction method which through comparative analysis of the domestic and international typical domain ontology construction method, and combined with the characteristics of the Salt Lake field, not only more comprehensive representation of the characteristics of the domain, but also has better logic and relevance.


2020 ◽  
Vol 14 (4) ◽  
pp. 277-284
Author(s):  
Naadira C. Upshaw ◽  
Douglas E. Lewis ◽  
Amber L. Nelson

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