TITLE:
Leveraging Robust Artificial Intelligence for Mechatronic Product Development—A Literature Review
AUTHORS:
Alexander Nüßgen, René Degen, Marcus Irmer, Fabian Richter, Cecilia Boström, Margot Ruschitzka
KEYWORDS:
Artificial Intelligence, Mechatronic Product Development, Knowledge Management, Data Analysis, Optimization, Human Experts, Decision-Making Processes, V-Cycle
JOURNAL NAME:
International Journal of Intelligence Science,
Vol.14 No.1,
December
22,
2023
ABSTRACT: Mechatronic product development is a complex and multidisciplinary field
that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software
engineering. The integration of artificial intelligence technologies is
revolutionizing this domain, offering opportunities to enhance design
processes, optimize performance, and leverage vast amounts of knowledge.
However, human expertise remains essential in contextualizing information,
considering trade-offs, and ensuring ethical and societal implications are
taken into account. This paper therefore explores the existing literature
regarding the application of artificial intelligence as a comprehensive
database, decision support system, and modeling tool in mechatronic product
development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert
knowledge, improving prediction quality, and enhancing intelligent
control systems. For this purpose, a consideration of the V-cycle takes place,
a standard in mechatronic product development. Along this, an initial
assessment of the AI potential is shown and
important categories of AI support are formed. This is followed by an
examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in
mechatronic product development opens new possibilities and transforms
the way innovative mechatronic systems are conceived, designed, and deployed.
However, the approaches are only
taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive
artificial intelligence along them is still needed.