Knowledge-intensive Collaborative Decision Support for Design Process

Zha, Xuan F.; Sriram, Ram D.

doi:10.1007/1-84628-231-4_16

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…Other applications support the concept phase by providing suggestions for later manufacturing strategies [30], manufacturing capabilities [31,32], and assembly [33]. Additionally, product configurations [34,35] and product family management [36] have been explored as use-cases as well as concept analyses [37][38][39][40]. There are also attempts to influence product reliability during system design using test and field data [41].…”

Section: System Designmentioning

confidence: 99%

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Gerschütz

Sauer

Kormann

et al. 2023

Designs

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This work aims to evaluate the current state of research on the use of artificial intelligence, deep learning, digitalization, and Data Mining in product development, mainly in the mechanical and mechatronic domain. These methods, collectively referred to as “digital engineering”, have the potential to disrupt the way products are developed and improve the efficiency of the product development process. However, their integration into current product development processes is not yet widespread. This work presents a novel consolidated view of the current state of research on digital engineering in product development by a literature review. This includes discussing the methods of digital engineering, introducing a product development process, and presenting results classified by their individual area of application. The work concludes with an evaluation of the literature analysis results and a discussion of future research potentials.

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Section: System Designmentioning

confidence: 99%

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Gerschütz

Sauer

Kormann

et al. 2023

Designs

View full text Add to dashboard Cite

show abstract

“…Like conventional and computer-aided design, smart design also includes creative and reflective design actions. There is a difference between smart design and knowledge-intensive computer-aided design, the latter being supported by (i) lifecycle information management (Yang et al, 2007), (ii) multi-disciplinary collaboration of teams (Zha et al, 2003), and (iii) using knowledge warehouses and design ontologies (Sun et al, 2010). In a smart design process, the role of humans is changed.…”

mentioning

confidence: 99%

Connectors of smart design and smart systems

Horváth

2021

AIEDAM

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Though they can be traced back to different roots, both smart design and smart systems have to do with the recent developments of artificial intelligence. There are two major questions related to them: (i) What way are smart design and smart systems enabled by artificial narrow, general, or super intelligence? and (ii) How can smart design be used in the realization of smart systems? and How can smart systems contribute to smart designing? A difficulty is that there are no exact definitions for these novel concepts in the literature. The endeavor to analyze the current situation and to answer the above questions stimulated an exploratory research whose first findings are summarized in this paper. Its first part elaborates on a plausible interpretation of the concept of smartness and provides an overview of the characteristics of smart design as a creative problem solving methodology supported by artificial intelligence. The second part exposes the paradigmatic features and system engineering issues of smart systems, which are equipped with application-specific synthetic system knowledge and reasoning mechanisms. The third part presents and elaborates on a conceptual model of AI-based couplings of smart design and smart systems. The couplings may manifest in various concrete forms in real life that are referred to as “connectors” in this paper. The principal types of connectors are exemplified and discussed. It has been found that smart design tends to manifest as a methodology of blue-printing smart systems and that smart systems will be intellectualized the enablers of implementation of smart design. Understanding the affordances of and creating proper connectors between smart design and smart systems need further explorative research.

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Knowledge-intensive Collaborative Decision Support for Design Process

Cited by 2 publications

References 11 publications

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Connectors of smart design and smart systems

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