Share
Title
Industrial Design of Electric Machines Supported with Knowledge-Based Engineering SystemsPublished Date
2021Publisher
MDPIKeywords
knowledge-based engineeringelectric motor
electric machine design
Industry 4.0
Abstract
The demand for electric machines has increased in the last decade, mainly due to applications that try to make a full transition from fuel to electricity. These applications encounter the need for tai ... [+]
The demand for electric machines has increased in the last decade, mainly due to applications that try to make a full transition from fuel to electricity. These applications encounter the need for tailor-made electric machines that must meet demanding requirements. Therefore, it is necessary for small-medium companies to adopt new technologies offering customized products fulfilling the customers’ requirements according to their investment capacity, simplify their development process, and reduce computational time to achieve a feasible design in shorter periods. Furthermore, they must find ways to retain know-how that is typically kept within each designer to retrieve it or transfer it to new designers. This paper presents a framework with an implementation example of a knowledge-based engineering (KBE) system to design industrial electric machines to support this issue. The devised KBE system groups the main functionalities that provide the best outcome for an electric machine designer as development-process traceability, knowledge accessibility, automation of tasks, and intelligent support. The results show that if the company effectively applies these functionalities, they can leverage the attributes of KBE systems to shorten time-to-market. They can also ensure not losing all knowledge, information, and data through the whole development process. [-]
Publisher’s version
https://doi.org/10.3390/app11010294ISSN
2076-3417Published at
Applied Sciences Vol. 11. N. 1. N. artículo 294, 2021Document type
Article
Version
Published
Rights
© 2021 by the authors. Licensee MDPIAccess
Open AccessCollections
- Articles - Engineering [478]
The following license files are associated with this item: