Engineering Design Synthesis: A Domain Independent Representation

1989 ◽  
pp. 156-156
Author(s):  
Mary Lou Maher
Author(s):  
Mary Lou Maher

The knowledge used in the design of engineering systems includes: understanding systems and their components, and the understanding implications of design decisions on other decisions and further problem decomposition This paper presents design as a process and then characterizes the knowledge used in synthesizing design alternatives. A knowledge based approach to design synthesis is proposed, followed by a description of the implementation of a domain independent synthesis framework. The implementation is further illustrated by an example application to structural design.


Author(s):  
Ang Liu ◽  
Wei Wei ◽  
Stephen C.-Y. Lu

Synthesis is a common activity in engineering design. It is widely recognized to be important to the whole engineering design process in general, and to the early design stages in particular. In the past, however, there remains lack of a set of rigorous metrics to evaluate the effectiveness of performing design synthesis in conceptual design. Based on relevant studies of abductive reasoning in logic, this paper introduces a set of domain-independent design synthesis metric: clarity, feasibility, testability, simplicity, and analogy. For each metrics, the rationale of including it is explained, and a systemic evaluation procedure is prescribed. Individually, each metrics addresses a particular aspect of design synthesis in conceptual design. Collectively, the combined consideration of all metrics as a single vector helps the designer to identify the most promising synthesis outcome, the best design concept, which both satisfies upstream objectives and meets downstream constraints.


Author(s):  
Julian R. Eichhoff ◽  
Felix Baumann ◽  
Dieter Roller

In this paper we demonstrate and compare two complementary approaches to the automatic generation of production rules from a set of given graphs representing sample designs. The first approach generates a complete rule set from scratch by means of frequent subgraph discovery. Whereas the second approach is intended to learn additional rules that fit an existing, yet incomplete, rule set using genetic programming. Both approaches have been developed and tested in the context of an application for automated conceptual engineering design, more specifically functional decomposition. They can be considered feasible, complementary approaches to the automatic inference of graph rewriting rules for conceptual design applications.


Author(s):  
Guo Q. Huang ◽  
John A. Brandon

A main theme of concurrent engineering is the effective communication between relevant disciplines. Any computer tools for concurrent engineering must provide sufficient constructs and strategies for this purpose. This paper describes the AGENTS system, a domain-independent general-purpose Object-Oriented Prolog language for cooperating expert systems in concurrent engineering design. Emphasis is placed on demonstrating the use of the AGENTS constructs for distributed knowledge representation and the cooperation strategies for communication, collaboration, conflict resolution, and control. A simple case study is presented to illustrate the balance between simplicity and flexibility.


Author(s):  
Stephen C.-Y. Lu ◽  
Satish T. S. Bukkapatnam ◽  
Ping Ge ◽  
Nanxin Wang

Abstract Design efficiency and robustness at early stage of parametric engineering design play a critical role in reducing cycle time and improving product quality in the overall product development process. Usually, the “forward mapping” approach, is used to find designs, where the desirable performances are satisfied through large iterations of analysis and evaluation from design space to performance space. However, these approaches are time-consuming and involve blind search if the engineering system simulation models and/or initial conditions are not appropriately selected. On the other hand, common “reverse engineering” methods use domain-specific assumptions and are not effective in generic scenarios where the presumed conditions are violated. In this paper, a Backward Mapping Methodology for Design Synthesis (BMDS) is presented that can help conduct design synthesis rapidly and robustly at early stage of parametric engineering design. BMDS is a surrogate model-based approach that combines the strengths of metamodeling and statistics. It can help designers explicitly identify the robust design solutions that satisfy the designer-specified performance requirements through a “backward mapping” from the performance space directly to the design space. Preliminary case studies show its effectiveness and potential to be used as a generic early stage parametric design synthesis methodology in the future.


2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Murtuza Shergadwala ◽  
Ilias Bilionis ◽  
Karthik N. Kannan ◽  
Jitesh H. Panchal

Many decisions within engineering systems design are typically made by humans. These decisions significantly affect the design outcomes and the resources used within design processes. While decision theory is increasingly being used from a normative standpoint to develop computational methods for engineering design, there is still a significant gap in our understanding of how humans make decisions within the design process. Particularly, there is lack of knowledge about how an individual's domain knowledge and framing of the design problem affect information acquisition decisions. To address this gap, the objective of this paper is to quantify the impact of a designer's domain knowledge and problem framing on their information acquisition decisions and the corresponding design outcomes. The objective is achieved by (i) developing a descriptive model of information acquisition decisions, based on an optimal one-step look ahead sequential strategy, utilizing expected improvement maximization, and (ii) using the model in conjunction with a controlled behavioral experiment. The domain knowledge of an individual is measured in the experiment using a concept inventory, whereas the problem framing is controlled as a treatment variable in the experiment. A design optimization problem is framed in two different ways: a domain-specific track design problem and a domain-independent function optimization problem (FOP). The results indicate that when the problem is framed as a domain-specific design task, the design solutions are better and individuals have a better state of knowledge about the problem, as compared to the domain-independent task. The design solutions are found to be better when individuals have a higher knowledge of the domain and they follow the modeled strategy closely.


Author(s):  
Andrew R. Schnell ◽  
Farrokh Mistree ◽  
Hongseok Moses Noh ◽  
Peter J. Hesketh

The concurrent consideration of design and manufacturing requirements at the early stages of design is one of the cited challenges in microsystem design. In this paper, we take the first steps, through an example, towards addressing these issues through the use of the compromise Decision Support Problem (cDSP). The cDSP is a domain-independent hybrid multiobjective decision support formulation utilized in engineering design. The design of a parylene microchannel for a microscale gas chromatography system is refined using the cDSP. The objective is to adjust the geometry of the microchannel to create a satisficing design for one fabrication goal and two performance goals. The cDSP is utilized for five scenarios, one in which all three goals are given equal priority, one for each of three goals when they are given first priority, and one in which the performance goals are given equal priority. We are more interested in demonstrating the method than the results per se. Our goal is to show how microsystem designers can use the cDSP to gain some insight into how these goals interact and how design decisions can be made with this insight.


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