The Digital Twin as a Knowledge-Based Engineering Enabler for Product Development

Author(s):  
Miguel Azevedo ◽  
Sérgio Tavares ◽  
António Lucas Soares
Author(s):  
Christopher Sauer ◽  
Bjoern Heling ◽  
Simon Schmutzler ◽  
Benjamin Schleich

Abstract Designers often lack important information about achievable manufacturing tolerances. Moreover tolerances are not considered from the beginning of product development. This often leads to inaccurately specified parts. Furthermore the full potential of the manufacturing departements is not used. This contribution tackles those areas by presenting a knowledge-based engineering workbench for automated tolerance specification, which has also been implemented using a commercial CAD system. This tool allows the designer to assign part tolerances that take into account the achievable accuracies for a specific manufacturing process, while at the same time allowing for specific part properties. The novelty of the presented approach can be found in the knowledge-based support of the product developers in tolerance specification by employing an engineering workbench. Moreover preprocessing for variation simulation and analysis is supported. It is possible to automate parts of the tolerance specification process, using the presented approach.


Author(s):  
Francesco Furini ◽  
Marco Rossoni ◽  
Giorgio Colombo

The study illustrated in this paper aims at analyzing the knowledge management issue related to product development. Especially, the focus is on the domains in which Knowledge-based Systems (KBE) and Design Automation (DA) tools could be adopted. In the past various studies, a lot of KBE and DA systems have been developed in multiple fields such as automotive, aerospace, energy, materials and manufacturing: the information treated in these studies are about data relatives to specific design, for example, of automotive engine components, aircraft structures, energy plants, advanced material and manufacturing or assembly lines. In all of these domain the organization and formalization of the knowledge is a critical issue. The adoption of a good strategy to manage data and information relative to products and processes involves benefits in the product development process. Different methodologies are described in literature. The two of the most used are the Object-Oriented (OO) and Ontology Engineering (OE) approaches. The former is one of the most common and adopted in the industrial domain, including a lot of implementations in the recent past years. The latter is more commonly used in other fields, like bio-engineering, used with the scope of management of experimental data; few implementation in industrial engineering have been considered. The article considers a brief description of the state of the art about Knowledge Based Engineering and Ontology Engineering. A case studies will be described and the benefits and disadvantages due to the use of the different methodologies will be discussed.


2002 ◽  
Vol 2002.12 (0) ◽  
pp. 283-284
Author(s):  
Hiromitsu TOKISUE ◽  
Ichiro NISHIGAKI ◽  
Shunsuke MINAMI ◽  
Mitsuru Sakai

2009 ◽  
Vol 20 (8) ◽  
pp. 1070-1083 ◽  
Author(s):  
Angelo Corallo ◽  
Robert Laubacher ◽  
Alessandro Margherita ◽  
Giuseppe Turrisi

2020 ◽  
Vol 1 ◽  
pp. 345-354
Author(s):  
L. P. Poot ◽  
C. Wehlin ◽  
M. Tarkian ◽  
J. Ölvander

AbstractWith industries striving towards increased customisation of complex products through engineer-to-order, methods are continuously sought to rationalise the product development process. To this end, a framework is proposed using CAD configurators, utilising design automation and knowledge-based engineering to integrate sales and design processes in product development. The application of this framework to the design of spiral staircases is described and analysed, with results showing decreased lead-times and a decreased risk for design errors.


2013 ◽  
Vol 1 (1) ◽  
pp. 158-178
Author(s):  
Urcun John Tanik

Cyberphysical system design automation utilizing knowledge based engineering techniques with globally networked knowledge bases can tremendously improve the design process for emerging systems. Our goal is to develop a comprehensive architectural framework to improve the design process for cyberphysical systems (CPS) and implement a case study with Axiomatic Design Solutions Inc. to develop next generation toolsets utilizing knowledge-based engineering (KBE) systems adapted to multiple domains in the field of CPS design automation. The Cyberphysical System Design Automation Framework (CPSDAF) will be based on advances in CPS design theory based on current research and knowledge collected from global sources automatically via Semantic Web Services. A case study utilizing STEM students is discussed.


Author(s):  
Elina Mäkelä ◽  
Petra Auvinen ◽  
Tero Juuti

AbstractThe paper concerns the Finnish product development teacherś perceptions on their pedagogical content knowledge in higher education settings. The aim is to describe and analyse what kind of pedagogical content knowledge the teachers have and, therefore, to provide a better understanding of the type of knowledge unique to product development teaching. The model of pedagogical content knowledge used here includes the components of product development content knowledge, pedagogical knowledge and pedagogical content knowledge. Based on seven teacher interviews, the main content knowledge concerns the process of product development, its different phases and methods as well as the usage of different software programs. The teachers use diverse teaching methods and their attitude towards educational technology is mostly positive. Course learning outcomes and working life are acknowledged when planning teaching, but only a few teachers take curriculum into account and participate in curriculum design. Even though the teachers use different evaluation methods in teaching, new ways of evaluation are needed. This may be something that innovative educational technology tools can make possible.


Author(s):  
Jerzy Pokojski ◽  
Karol Szustakiewicz ◽  
Łukasz Woźnicki ◽  
Konrad Oleksiński ◽  
Jarosław Pruszyński

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