scholarly journals Understanding the Roles of Low-fidelity Prototypes in Engineering Design Activity

2020 ◽  
Author(s):  
Hadi Ali ◽  
Micah Lande
Keyword(s):  
Engineering Design ◽  
Design Activity

The Origins of Engineering Design

1993 ◽  
Author(s):  
Andrew D. Dimarogonas
Keyword(s):  
Engineering Design ◽  
19Th Century ◽  
Scientific Knowledge ◽  
Industrial Revolution ◽  
Design Activity ◽  
Ancient Greek ◽  
Modern Engineering ◽  
Hellenistic World ◽  
Systematic Development ◽  
The 19Th Century

Abstract Engineering is distinguished from craft or invention by systematic development and use of intelligence and scientific knowledge. Elements of engineering design can be found in the great Potamic civilizations but systematic engineering design activity started in the ancient Greek and Hellenistic world and matured under the Romans. The renaissance and the industrial revolution revived Engineering and modern engineering design was eventually defined during the 19th Century.

A Multi Autonomic Objects Flexible Workflow and its Knowledge Acquisition Supporting Engineering Design Process

2010 ◽  
Vol 97-101 ◽  
pp. 3341-3344
Author(s):  
Dong Bo Wang ◽  
Xiu Tian Yan ◽  
Ning Sheng Guo ◽  
Tao Li
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Literature Review ◽  
Knowledge Acquisition ◽  
Engineering Design ◽  
Design Process ◽  
Design Activity ◽  
Learning Method ◽  
Matlab Simulation ◽  
Engineering Design Process

In order to support the dynamic and creative Engineering Design Process (EDP) comprehensively, after a detailed literature review, a multi autonomic objects (AO) flexible workflow is applied into the supporting and management of EDP, its support for decision making, EDP evolution and design activity granularity is explained, finally and most importantly, a genetic algorithm-based AO knowledge learning method is proposed, the algorithm is demonstrated by a MATLAB simulation that it can satisfy the knowledge acquisition in EDP satisfactorily.

Applications and prospects for AI in mechanical engineering design

1990 ◽  
Vol 5 (3) ◽  
pp. 167-179 ◽  
Author(s):  
Ian M. Carter
Keyword(s):  
Engineering Design ◽  
Conceptual Design ◽  
Mechanical Engineering ◽  
Subject Area ◽  
Computer Support ◽  
Design Activity ◽  
Engineering Systems ◽  
Design Systems ◽  
Broad Subject ◽  
Future Topics

AbstractMechanical engineering design is a broad subject area covering many topics and bas influences upon many other engineering disciplines and activities. Computer support for mechanical engineering design activity has been in draughting Systems and analysis packages, but there has been little in conceptual design assistance. This paper presents a number of areas of work in which AI techniques and developments are being used, sometimes in conjunction with traditional methods, to improve the support of design. The approaches to design and design Systems are covered, along with some techniques that are used. Specifie design Systems illustrate progress, and integration issues and simultaneous engineering Systems indicate the way research is moving. Finally, discussion of the trends and future topics indicates where and how effort may be applied in the future.

The Maintenance and Handling of Constraints in Machine Design

2009 ◽  
Author(s):  
Jason Matthews ◽  
Lian Ding ◽  
Jonathan Feldman ◽  
Glen Mullineux
Keyword(s):  
Engineering Design ◽  
Machine Design ◽  
Design Activity ◽  
Industrial Case Study ◽  
Design Constraints ◽  
Engineering Design Process ◽  
Design Variation ◽  
Single Objective ◽  
Machinery Design

The engineering design process can be considered to be constraint oriented. It involves the identification, negotiation and resolution of an evolving set of constraints. The nature of engineering design is that such problems are rarely as simple as satisfying a single objective with all the design variation continuous and unbounded. Previous research has shown that as the design evolves, the designer can miss or overlook some of these constraints. To overcome this, the paper presents a supportive approach which allows the designer to annotate the initial CAD drawn models with the design constraints. These constraints are then maintained with the model as it evolves, this presents the opportunity to refine the constraints when the design activity requires. The approach has been created to support manufacturing machinery design and is demonstrated with an industrial case study.

The Engineering Design Discipline: Is its Confounding Lexicon Hindering its Evolution?

1998 ◽  
Author(s):  
Achille Messac ◽  
Wei Chen
Keyword(s):  
Engineering Design ◽  
Design Research ◽  
Research Community ◽  
Design Activity ◽  
Communication Infrastructure ◽  
Current State ◽  
Diverse Backgrounds ◽  
A Priority ◽  
The Web

Abstract In this paper, we invite the engineering design research community to examine the current state of the engineering design lexicon. We expose the nature and the pervasiveness of practices that often hinder intelligible discourse within the engineering design literature. In particular, we show how such commonly used terms as criterion and metric are used sometimes as synonyms and sometimes not, often leading to material miscommunications. In our view, the engineering design discipline has reached a point in its evolution where clarity and conciseness of its lexicon should be a priority. Today’s design activity takes place in a truly multidisciplinary environment, which often involves engineers of diverse backgrounds. Written and oral design discourse among design researchers does not rely on a generally accepted and documented lexicon. These situations are symptomatic of a communication infrastructure that is not effectively facilitating the vigorous evolution of the engineering design discipline of recent years. In addition to detailing the outlines of the design lexicon deficiency, we also propose some avenues to a constructive and productive community-wide discussion on this subject. We invite readers to contribute their views by participating in the web discussion at http://www.eng.buffalo.edu/Research/DBD/.

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