scholarly journals EVOLUTIONARY ENVIRONMENT FOR 3D MORPHOLOGICAL DESIGN

2014 ◽  
pp. 56-62
Author(s):  
A. Lamas ◽  
R. J. Duro
Keyword(s):  
Design Process ◽  
Decision Process ◽  
Difficult Problem ◽  
Design System ◽  
Automatic Design ◽  
Engineering Information ◽  
Extract Information

This paper deals with the automation of morphological design. The system proposed here is a part of a complete automatic design system that considers the divergent and convergent stages of the design process through evolutionary procedures. The system provides a way to introduce aesthetics in the decision process. This is a difficult problem within an automatic design system, as aesthetics are subjective, depend on the opinions of humans and humans do not usually agree. The objective here is to be able to obtain the best possible aesthetic solutions for a given set of humans. This is achieved through the introduction of a set of man machine interfaces that allow the system to extract information on their relative opinions without explicitly asking them, and combines them with the engineering information provided by other simulators that participate in the design process.

Development of an Automatic Design and Optimization System for Industrial Silencers

2002 ◽  
Author(s):  
Lee Ming Wong ◽  
G. Gary Wang ◽  
Charles Friesen ◽  
Ken How Foo ◽  
Lucas Pang
Keyword(s):  
Life Cycle ◽  
Optimal Design ◽  
Product Design ◽  
Design Process ◽  
Product Life Cycle ◽  
Design System ◽  
Automatic Design ◽  
Product Life ◽  
Design And Optimization ◽  
Optimization System

Current Computer Aided Design (CAD) technologies offer parametric design functions to allow users to easily change products’ configurations, shape and dimensions without reconstructing the entire product model. A programming tool that often comes with most CAD packages enables a designer to better control the parametric interface. However, these two functions focus on rapid production of computer models, which usually takes place after the product design is completed. The product design process, which has more significant influence on product life-cycle costs, is not fully supported. This paper proposes a systematic method in which a product design can be finalized and optimized through the interactions between 3-D solid modeling and customized cost / performance analysis. The entire optimal design process and generation of design deliverables is fully automated through interactive programming. In addition, an automatic design and optimization system for industrial silencers has been developed, which takes customers’ order from the Internet, sends the order to a CAD system, generates the optimal design, and sends back the design to the customer. The entire process takes only a few minutes. The proposition of integrating customized product life-cycle considerations with the model generation and optimization, as well as the developed silencer design system should be useful for other product designs.

Process Control Method of Complex Product Multidisciplinary Collaborative Design System

2013 ◽  
Vol 712-715 ◽  
pp. 2888-2893
Author(s):  
Hai Qiang Liu ◽  
Ming Lv
Keyword(s):  
Information Sharing ◽  
Product Design ◽  
Design Process ◽  
Collaborative Design ◽  
Control Method ◽  
Integrated System ◽  
Design System ◽  
System Control ◽  
Complex Product ◽  
Product Design Process

In order to realize information sharing and interchange of complex product multidisciplinary collaborative design (MCD) design process and resources. The Process integrated system control of product multidisciplinary collaborative design was analyzed firstly in this paper, then design process of complex product for supporting multidisciplinary collaborative was introduced, a detailed description is given of the organization structure and modeling process of MCD-oriented Integration of Product Design Meta-model ; and concrete implement process of process integrated system control method was introduced to effectively realize information sharing and interchange between product design process and resources.

Using VR as a Tool for the Automated Capture and Formalisation of Engineering Knowledge

2011 ◽  
Author(s):  
James M. Ritchie ◽  
Raymond C. W. Sung ◽  
Theodore Lim
Keyword(s):  
Design System ◽  
Design Knowledge ◽  
Engineering Knowledge ◽  
Cable Harness ◽  
Head Mounted Display ◽  
Design Engineers ◽  
Development Cycle ◽  
Engineering Information ◽  
Automatic Capture ◽  
And Training

The effective capture of legacy knowledge and information during all aspects of the product development cycle is one of the biggest remaining challenges in engineering companies. Life Cycle Engineering requires the capture of engineering information and knowledge created during design sessions to support knowledge reuse, product reengineering and training. In the past, many attempts have been made to determine if this is possible; however, those that are partially successful are very time consuming, expensive to implement and interrupt the engineers’ creativity. This work investigates and demonstrates new and novel paradigms for knowledge and information capture by adapting and applying a well recognised knowledge capture methodology to suit the non-intrusive automated real time logging, capture and post processing of engineering knowledge using a head-mounted display virtual reality (VR) design system. This logging is accomplished during individual cable harness design tasks carried out by 12 cable harness design engineers from five industrial partners to demonstrate the effective, unobtrusive and automatic capture and representation of various forms of engineering design knowledge and information. The formats were subsequently evaluated by the engineers to determining those they consider best at conveying design knowledge and information for other engineers.

scholarly journals An Interactive System to Integrate the Design, Analysis, and Manufacture of Centrifugal Compressor Impellers

1990 ◽  
Author(s):  
James E. Crouse ◽  
James M. Sorokes
Keyword(s):  
Design Process ◽  
Centrifugal Compressor ◽  
Design Analysis ◽  
Design System ◽  
Interactive System ◽  
Cylindrical Coordinates ◽  
Manufacturing Software

This paper presents the impeller design system developed at Dresser-Rand using Bezier polynomials in cylindrical coordinates. A discussion of the basic techniques utilized in the code is presented as are sample graphic outputs generated to aid the user in the design process. The paper also describes some of the output options and how results may be interfaced with other analytical, drafting, and manufacturing software. Comments are included regarding the increased productivity, accuracy, and quality which resulted directly from use of this code and its support routines.

scholarly journals Automatic Design System with Generative Adversarial Network and Convolutional Neural Network for Optimization Design of Interior Permanent Magnet Synchronous Motor

2021 ◽  
Author(s):  
Yuki Shimizu ◽  
Shigeo Morimoto ◽  
Masayuki Sanada ◽  
Yukinori Inoue
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Convolutional Neural Network ◽  
Permanent Magnet ◽  
Optimization Design ◽  
Design System ◽  
Automatic Design ◽  
Wide Range ◽  
Interior Permanent Magnet ◽  
Long Time

The optimal design of interior permanent magnet synchronous motors requires a long time because finite element analysis (FEA) is performed repeatedly. To solve this problem, many researchers have used artificial intelligence to construct a prediction model that can replace FEA. However, because the training data are generated by FEA, it takes a very long time to obtain a sufficient amount of data, making it impossible to train a large-scale prediction model. Here, we propose a method for generating a large amount of data from a small number of FEA results using machine learning. An automatic design system with a deep generative model and a convolutional neural network is then constructed. With its sufficient data, the proposed system can handle three topologies and three motor parameters in a wide range of current vector regions. The proposed system was applied to multi-objective optimization design, with the optimization completed in 13-15 seconds.

scholarly journals Automatic Design System with Generative Adversarial Network and Convolutional Neural Network for Optimization Design of Interior Permanent Magnet Synchronous Motor

2021 ◽  
Author(s):  
Yuki Shimizu ◽  
Shigeo Morimoto ◽  
Masayuki Sanada ◽  
Yukinori Inoue
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Convolutional Neural Network ◽  
Permanent Magnet ◽  
Optimization Design ◽  
Design System ◽  
Automatic Design ◽  
Wide Range ◽  
Interior Permanent Magnet ◽  
Long Time

The optimal design of interior permanent magnet synchronous motors requires a long time because finite element analysis (FEA) is performed repeatedly. To solve this problem, many researchers have used artificial intelligence to construct a prediction model that can replace FEA. However, because the training data are generated by FEA, it takes a very long time to obtain a sufficient amount of data, making it impossible to train a large-scale prediction model. Here, we propose a method for generating a large amount of data from a small number of FEA results using machine learning. An automatic design system with a deep generative model and a convolutional neural network is then constructed. With its sufficient data, the proposed system can handle three topologies and three motor parameters in a wide range of current vector regions. The proposed system was applied to multi-objective optimization design, with the optimization completed in 13-15 seconds.

Star tracker lens mechanical automatic design system on parametric modeling

2021 ◽  
Vol 0 (0) ◽  
pp. 1-11
Author(s):  
ZHU Jun-qing ◽  
◽  
◽  
SHA Wei ◽  
FANG Chao ◽  
...  
Keyword(s):  
Parametric Modeling ◽  
Design System ◽  
Star Tracker ◽  
Automatic Design
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