The Four-Box Method: Problem Formulation and Analogy Evaluation in Biologically Inspired Design

2014 ◽  
Vol 136 (11) ◽  
Author(s):  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Design Problem ◽  
Problem Formulation ◽  
Biologically Inspired ◽  
Design Problems ◽  
In Situ Observations ◽  
Box Method ◽  
Biologically Inspired Design ◽  
Search Design

Searching for biological analogies appropriate for design problems is a core process of biologically inspired design (BID). Through in situ observations of student BIDs, we discovered that student designers struggle with two issues that bookend the problem of search: design problem formulation, which generates the set of conditions to be used for search; and evaluation of the appropriateness of the retrieved analogies, which depends both on problem formulation and the retrieved analogy. We describe a method for problem formulation and analogy evaluation in BID that we call the Four-Box method. We show that the Four-Box method can be rapidly and accurately used by designers for both problem formulation and analogy evaluation, and that designers find the method valuable for the intended tasks.

The Four-Box Method of Problem Specification and Analogy Evaluation in Biologically Inspired Design

2014 ◽  
Author(s):  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Design Problem ◽  
Idea Generation ◽  
Performance Criteria ◽  
Biologically Inspired ◽  
Classroom Implementation ◽  
Interdisciplinary Design ◽  
Final Design ◽  
Box Method ◽  
Biologically Inspired Design ◽  
And Performance

The process of biologically inspired design is fundamentally analogical; given a design problem, the process retrieves potentially multiple biological analogues as potential sources of inspiration. The selection of a specific analogue for idea generation naturally has a strong influence on the final design. But what makes one biological analogue better than another for a given design problem? In the context of a classroom on biologically inspired design, we found that interdisciplinary design teams often struggle with this question. In this paper, we describe a Four-Box method that identifies function, operating environment, constraints, and performance criteria as dimensions for matching biological analogues with the design problem. We also present some initial results from a classroom implementation of the Four-Box method of analogy evaluation: The results suggest that the student designers found the Four-Box method both useful and usable.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

On: “RECENT TECHNIQUES FOR DETERMINATION OF IN SITU ELASTIC PROPERTIES AND MEASUREMENT OF MOTION AMPLIFICATION IN LAYERED MEDIA,” BY R.J. SWAIN (GEOPHYSICS, APRIL, 1962, PP. 237–241).

Geophysics ◽  
1963 ◽  
Vol 28 (1) ◽  
pp. 112-112 ◽  
Author(s):  
Harry R. Nicholls
Keyword(s):  
Elastic Properties ◽  
Elastic Constants ◽  
Design Problem ◽  
Critical Angle ◽  
Specific Design ◽  
Design Problems ◽  
Relative Value ◽  
Angle Method

Although I am in general agreement with Mr. Swain’s paper, there are several pitfalls inherent in the use of dynamic elastic constants which should not be ignored. The strength of materials and the elastic properties both undoubtedly depend on the rate of loading and/or the stress levels involved. It does not seem appropriate, therefore, to use dynamic in situ elastic properties for static design problems. The specific design problem at hand should determine the relative value placed on the use of static or dynamic elastic constants. The dynamic in situ values are generally more reliable than those obtained in the laboratory as indicated by Mr. Swain, although continued development of the laboratory pulse and critical‐angle method shows promise of improving the reliability of laboratory values.

Robust MDSDO for Co-Design of Stochastic Dynamic Systems

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Saeed Azad ◽  
Michael J. Alexander-Ramos
Keyword(s):  
Dynamic System ◽  
Design Optimization ◽  
System Design ◽  
Design Problem ◽  
Integrated Design ◽  
Problem Formulation ◽  
Robust Design Optimization ◽  
Design Problems ◽  
Embodiment Design ◽  
And Control

Abstract Optimization of dynamic engineering systems generally requires problem formulations that account for the coupling between embodiment design and control system design simultaneously. Such formulations are commonly known as combined optimal design and control (co-design) problems, and their application to deterministic systems is well established in the literature through a variety of methods. However, an issue that has not been addressed in the co-design literature is the impact of the inherent uncertainties within a dynamic system on its integrated design solution. Accounting for these uncertainties transforms the standard, deterministic co-design problem into a stochastic one, thus requiring appropriate stochastic optimization approaches for its solution. This paper serves as the starting point for research on stochastic co-design problems by proposing and solving a novel problem formulation based on robust design optimization (RDO) principles. Specifically, a co-design method known as multidisciplinary dynamic system design optimization (MDSDO) is used as the basis for an RDO problem formulation and implementation. The robust objective and inequality constraints are computed per usual as functions of their first-order-approximated means and variances, whereas analysis-based equality constraints are evaluated deterministically at the means of the random decision variables. The proposed stochastic co-design problem formulation is then implemented for two case studies, with the results indicating the importance of the robust approach on the integrated design solutions and performance measures.

Problem Discovery With Many-Objective Visual Analytics

2016 ◽  
Author(s):  
Matthew Woodruff ◽  
Timothy W. Simpson
Keyword(s):  
Visual Analytics ◽  
Design Problem ◽  
Problem Formulation ◽  
Design Problems ◽  
Design Decisions ◽  
Detailed Design ◽  
Default State ◽  
State Of Affairs

Problem discovery is messy. It involves many mistakes, which may be regarded as a failure to address a design problem correctly. Mistakes, however, are inevitable, and misunderstanding the problems we are working on is the natural, default state of affairs. Only through engaging in a series of mistakes can we learn important things about our design problems. This study provides a case study in Many-Objective Visual Analytics (MOVA), as applied to the problem of problem discovery. It demonstrates the process of continually correcting and improving a problem formulation while visualizing its optimization results. This process produces a new, clearer understanding of the problem and puts the designer in a position to proceed with more-detailed design decisions.

Enhancing Design Problem Formulation Skills for Engineering Design Students

2014 ◽  
Author(s):  
Mahmoud Dinar ◽  
Jami J. Shah
Keyword(s):  
Graduate Students ◽  
Engineering Design ◽  
Design Problem ◽  
Mechanical Engineering ◽  
Problem Formulation ◽  
Assessment Methods ◽  
Web Tool ◽  
Design Problems ◽  
Course Work ◽  
Design Students

Problem formulation is an essential design skill for which assessment methods have been less commonly developed. In order to evaluate the progress of a group of graduate students in mechanical engineering design in regard with the problem formulation skill, they were asked to work on three design problems using the Problem Formulator web tool during their course work. Changes in a set of measures elicited from this data were examined in addition to sketches, simulations, and working prototypes. Inventories of requirements and issues, as well as concepts derived from morphological charts were created to assess designers’ skills and outcomes.

ROM Based Problem Formulation in Conceptual Design: Algorithm and Case Study

2014 ◽  
Author(s):  
Ronaldo Gutierrez ◽  
Yong Zeng ◽  
Xuan Sun ◽  
Suo Tan ◽  
Xiaoguang Deng ◽  
...  
Keyword(s):  
Natural Language ◽  
Conceptual Design ◽  
Design Problem ◽  
Quality Management System ◽  
Problem Formulation ◽  
Total Quality ◽  
Design Problems ◽  
Design Algorithm ◽  
Problem Formulations

Problem formulations in natural language imply imprecision, ambiguity, incompleteness, conflict and inconsistency between requirements in a design problem. Recursive Object Model (ROM) based problem formulation in conceptual design extracts complete product requirement from design problems structured initially in natural language. Since ROM carries certain semantic and syntactic information implied in natural language, it is used to formulate a design problem through a question asking approach. The scope of this paper is to present an updated algorithm, question templates, rules and detailed procedures to ask generic questions based on ROM representations. Generic questions are needed for the clarification and extension of the meaning of a design problem in order to overcome the imprecisions, ambiguities, conflicts and inconsistencies of problem descriptions in natural language. The updated algorithm, question templates, rules and detailed procedures for asking generic questions are used in a case study to formulate the development of a Total Quality Management system (TQMS).

Robust MDSDO for Co-Design of Stochastic Dynamic Systems

2018 ◽  
Author(s):  
Saeed Azad ◽  
Michael J. Alexander-Ramos
Keyword(s):  
Dynamic System ◽  
Design Optimization ◽  
System Design ◽  
Design Problem ◽  
Integrated Design ◽  
Problem Formulation ◽  
Robust Design Optimization ◽  
Design Problems ◽  
Embodiment Design ◽  
And Control

Optimization of dynamic engineering systems generally requires problem formulations that account for the coupling between embodiment design and control system design simultaneously. Such formulations are commonly known as combined optimal design and control (co-design) problems, and their application to deterministic systems is well-established in the literature through a variety of methods. However, an issue that has not been addressed in the co-design literature is the impact of the inherent uncertainties within a dynamic system on its integrated design solution. Accounting for these uncertainties transforms the standard, deterministic co-design problem into a stochastic one, thus requiring appropriate stochastic optimization approaches for its solution. This paper serves as the starting point for research on stochastic co-design problems by proposing and solving a novel problem formulation based on robust design optimization (RDO) principles. Specifically, a co-design method known as multidisciplinary dynamic system design optimization (MDSDO) is used as the basis for a RDO problem formulation and implementation. The robust objective and inequality constraints are computed per usual as functions of their first-order-approximated means and variances, whereas analysis-based equality constraints are evaluated deterministically at the means of the random decision variables. The proposed stochastic co-design problem formulation is then implemented for two case studies, with the results indicating a significant impact of the robust approach on the integrated design solutions and performance measures.

scholarly journals THE RELATIONSHIP BETWEEN FUNCTIONS AND OUTCOMES OF BIOLOGICALLY-INSPIRED DESIGN

2021 ◽  
Vol 1 ◽  
pp. 3091-3100
Author(s):  
Nicklas Werge Svendsen ◽  
Torben Anker Lenau ◽  
Claus Thorp Hansen
Keyword(s):  
Design Problem ◽  
Historical Data ◽  
Solution Space ◽  
Biologically Inspired ◽  
Problem Types ◽  
Student Teams ◽  
Data Source ◽  
Biologically Inspired Design ◽  
And Function ◽  
The Relationship

AbstractResearch in biologically-inspired design (BID) practice often focus on team composition or ideation based on an already discovered fascinating biological solution principle. However, how are the outcome of the early design phases affecting BID projects' quality?In this study, historical data from 91 reports from student teams documenting their BID efforts from a 3-week course constitute the data source. Thus, the relationship between design problem types, function types, functions descriptions and BID projects' quality is addressed.The study show that especially design problem types and function descriptions affect the BID projects' quality. For instance, BID projects dealing with open-ended problems yield better results than redesign problems with existing solutions operating in a very domain-limited solution space. Next, BID projects obtain the best results when using functions as drivers for analogy searching rather than properties. Finally, BID projects with certain function types seem to have more complicated conceptualization phases.

In situ observations of electromigration induced void behavior

1995 ◽  
Vol 53 ◽  
pp. 244-245
Author(s):  
T. Marieb ◽  
J. C. Bravman ◽  
P. Flinn ◽  
D. Gardner ◽  
M. Madden
Keyword(s):  
Electron Microscopy ◽  
Void Nucleation ◽  
Plan View ◽  
Transmission Electron ◽  
Nucleation Sites ◽  
Microelectronics Industry ◽  
In Situ Observations ◽  
Backscatter Electron Detector ◽  
Voltage Scanning

Electromigration and stress voiding have been active areas of research in the microelectronics industry for many years. While accelerated testing of these phenomena has been performed for the last 25 years[1-2], only recently has the introduction of high voltage scanning electron microscopy (HVSEM) made possible in situ testing of realistic, passivated, full thickness samples at high resolution.With a combination of in situ HVSEM and post-testing transmission electron microscopy (TEM) , electromigration void nucleation sites in both normal polycrystalline and near-bamboo pure Al were investigated. The effect of the microstructure of the lines on the void motion was also studied.The HVSEM used was a slightly modified JEOL 1200 EX II scanning TEM with a backscatter electron detector placed above the sample[3]. To observe electromigration in situ the sample was heated and the line had current supplied to it to accelerate the voiding process. After testing lines were prepared for TEM by employing the plan-view wedge technique [6].

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