scholarly journals Knowledge-based engineering in the context of railway design by integrating BIM, BPMN, DMN and the methodology for knowledge-based engineering applications (MOKA)

2021 ◽  
Vol 26 ◽  
pp. 193-226
Author(s):  
Marco Häußler ◽  
André Borrmann
Keyword(s):  
Process Model ◽  
Best Practice ◽  
Engineering Applications ◽  
Engineering Knowledge ◽  
Domain Specific ◽  
Knowledge Based ◽  
Routine Design ◽  
Knowledge Based Engineering ◽  
Knowledge Intensive ◽  
Use Of Knowledge

Designing railway infrastructure is a knowledge-intensive task. Although there are a number of mature design authoring systems available, their support for dynamically incorporating domain-specific engineering knowledge is very limited. At the same time, a standardized digital representation of railway engineering knowledge (such as building codes and best practice) does not exists. To overcome this deficiency, this paper proposes the use of Knowledge Based Engineering (KBE) to automate routine design tasks by considering multiple knowledge sources. In this scenario, KBE is used to support a Railway design authoring system. To ensure maximum transparency in the design of the developed KBE application, graphical ‘Business Process Model and Notation’ (BPMN) has been used in combination with ‘Decision Model and Notation’ (DMN) to formalize the underlying engineering knowledge. The KBE application has been developed according to the Methodology for Knowledge-Based Engineering Applications (MOKA). An evaluation of the BPMN/DMN approach shows that it meets up to 58% of the acceptance criteria found in the literature. In addition, BPMN and DMN can already be used in the early capture phase of MOKA and its workflows can be developed into an executable KBE application in the subsequent phases. The results of the test example discussed here show that time savings of up to 97.5% can be achieved in the execution of the KBE application.

scholarly journals Use of Knowledge-Based Engineering in Compressor Rotor Design

1995 ◽  
Author(s):  
John Marra
Keyword(s):  
Design Process ◽  
Concurrent Engineering ◽  
Synergistic Effects ◽  
General Description ◽  
Knowledge Based ◽  
Compressor Rotor ◽  
Product And Process Knowledge ◽  
Knowledge Based Engineering ◽  
Product And Process ◽  
Use Of Knowledge

Competitive pressures are forcing manufacturers of turbine engines to reduce product development times, minimize design iterations, and react rapidly to changing markets and customers. Concurrent Engineering replaces the traditional sequential design process with parallel efforts in multiple disciplines, increasing product quality while reducing leadtime. Knowledge-Based Engineering captures product and process knowledge contained in the “corporate memory” to enhance and accelerate the design process. Linking the two together provides a wide variety of synergistic effects not separately available. In this paper a general description of the process used to create a Knowledge Based Engineering (KBE) System capable of Concurrent Engineering (CE) will be presented, along with selected results. The summary discusses use of the system created to pursue real world design problems.

scholarly journals Knowledge Intensive Software Engineering Applications

2021 ◽  
Vol 27 (2) ◽  
pp. 87-90
Author(s):  
Jezreel Mejía ◽  
Rafael Valencia-García ◽  
Giner Alor-Hernández ◽  
José A. Calvo-Manzano
Keyword(s):  
Software Engineering ◽  
Information And Communication Technologies ◽  
Knowledge Engineering ◽  
Workflow Management ◽  
Subsequent Development ◽  
Engineering Applications ◽  
Technological Basis ◽  
Software Applications ◽  
Knowledge Based ◽  
Knowledge Intensive

The use of Information and Communication Technologies (ICTs)  has become a competitive strategy that allows organizations to position themselves within their market of action. In addition, the evolution, advancement and use of ICTs within any type of organization have created new domains of interest. In this context, Knowledge-intensive software engineering applications are becoming crucial in organizations to support their performance. Knowledge-based technologies provide a consistent and reliable basis to face the challenges for organization, manipulation and visualization of the data and knowledge, playing a crucial role as the technological basis of the development of a large number of information systems. In software engineering, it involves the integration of various knowledge sources that are in constant change. Knowledge-intensive software applications are becoming more significant because the domains of many software applications are inherently knowledge-intensive and this knowledge is often not explicitly dealt with in software development. This impedes maintenance and reuse. Moreover, it is generally known that developing software requires expertise and experience, which are currently also implicit and could be made more tangible and reusable using knowledge-based or related techniques. Furthermore, organizations have recognized that the software engineering applications are an optimal way for providing solutions, because it is a file that is constantly evolving due to the new challenges. Examples of approaches that are directly related to this tendency are data analysis, software architectures, knowledge engineering, ontologies, conceptual modelling, domain analysis and domain engineering, business rules, workflow management, human and cultural factors, to mention but a few. Therefore, tools and techniques are necessary to capture and process knowledge in order to facilitate subsequent development efforts, especially in the domain of software engineering.  

scholarly journals Augmented Intensional Reasoning in Knowledge-Based Accounting Systems

2000 ◽  
Vol 14 (2) ◽  
pp. 127-150 ◽  
Author(s):  
Guido L. Geerts ◽  
William E. McCarthy
Keyword(s):  
Knowledge Sharing ◽  
Accounting Systems ◽  
Conceptual Schema ◽  
Domain Specific ◽  
Design And Implementation ◽  
Knowledge Based ◽  
Conceptual Structures ◽  
Intensive Use ◽  
Different Dimensions ◽  
Knowledge Intensive

A limitation of existing accounting systems is their lack of knowledge sharing and knowledge reuse, which makes the design and implementation of new accounting systems time-consuming and expensive. An important requirement for knowledge sharing and reuse is the existence of a common semantic infrastructure. In this article we use McCarthy's (1982) Resource-Event-Agent (REA) model as a common semantic infrastructure in an accounting context. The objective is to make knowledge-intensive use of REA to share accounting concepts across functional boundaries and to reuse these concepts in different applications and different systems, an approach we call augmented intensional reasoning. Intensional reasoning is the active use of conceptual structures in information systems operations such as design and information retrieval. For augmented intensional reasoning, the conceptual structures are extended with domain-specific REA knowledge. Sections II and III describe different dimensions of augmented intensional reasoning: the REA primitives, the technological features needed to support augmented intensional reasoning, the need for epistemologically adequate representations to make augmented intensional reasoning feasible, and the practical necessity of implementation compromises. Sections IV and V explore two uses of augmented intensional reasoning: design and operation of knowledge-based accounting systems. The example in Section V explains how augmented intensional reasoning works: (1) define the conceptual schema, (2) structure the conceptual schema in terms of REA (knowledge augmentation), (3) define a shareable and reusable accounting concept (claim), and (4) use the concept (claim) to derive information in different accounting cycles (revenue and acquisition).

A framework for management of Knowledge-Based Engineering applications as software services: Enabling personalization and codification

2012 ◽  
Vol 26 (2) ◽  
pp. 219-230 ◽  
Author(s):  
Pablo Bermell-Garcia ◽  
Wim J.C. Verhagen ◽  
Simon Astwood ◽  
Kiran Krishnamurthy ◽  
Jean Luc Johnson ◽  
...  
Keyword(s):  
Engineering Applications ◽  
Knowledge Based ◽  
Knowledge Based Engineering ◽  
Software Services

Review of Knowledge Based Engineering with PLM

2007 ◽  
Vol 10-12 ◽  
pp. 127-131 ◽  
Author(s):  
Q.C. Ma ◽  
X.W. Liu
Keyword(s):  
Knowledge Representation ◽  
General Structure ◽  
Digital Tools ◽  
Current Development ◽  
Knowledge Based System ◽  
Domain Specific ◽  
Knowledge Based ◽  
History Of ◽  
Knowledge Based Engineering ◽  
Internal Knowledge

This paper starts with an analysis of the need for knowledge based engineering (KBE) system based on typical domain-specific engineering products. It looks back the history of KBE and exams the general structure of KBE systems. It then reviews the current development, particularly the knowledge representation in a KBE system, followed by a discussion of the shortcomings regarding to the maintenance and excessive cost of integrations with other digital tools. Finally it recommends the characteristics of a genuine KBE system and the standardization of KBE applications, particularly the internal knowledge representation standards and knowledge-based system interface standards with CAx systems and PLM solutions.

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