Identification of Subproblems in Complex Design Problems: A Study of Facility Design

2016 ◽  
Author(s):  
Azrah Azhar ◽  
Erica L. Gralla ◽  
Connor Tobias ◽  
Jeffrey W. Herrmann
Keyword(s):  
Standard Method ◽  
Association Rule ◽  
Rule Learning ◽  
Problem Decomposition ◽  
Design Teams ◽  
Design Problems ◽  
Manufacturing Facility ◽  
Qualitative And Quantitative ◽  
Complex Design ◽  
Design Activities

Many design problems are too difficult to solve all at once; therefore, design teams often decompose these problems into more manageable subproblems. While there has been much interest in engineering design teams, no standard method has been developed to understand how teams solve design problems. This paper describes a method for analyzing a team’s design activities and identifying the subproblems that they considered. This method uses both qualitative and quantitative techniques; in particular, it uses association rule learning to group variables into subproblems. We used the method on data from ten teams who redesigned a manufacturing facility. This approach provides researchers with a clear structure for using observational data to identify the problem decomposition patterns of human designers.

scholarly journals Evaluating Clustering Algorithms for Identifying Design Subproblems

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Jeffrey W. Herrmann ◽  
Michael Morency ◽  
Azrah Anparasan ◽  
Erica L. Gralla
Keyword(s):  
Association Rule ◽  
Euclidean Distance ◽  
Clustering Algorithms ◽  
Design Teams ◽  
Clustering Methods ◽  
Design Problems ◽  
Design Variables ◽  
Complex Design ◽  
Synthetic Datasets ◽  
Better Than

Understanding how humans decompose design problems will yield insights that can be applied to develop better support for human designers. However, there are few established methods for identifying the decompositions that human designers use. This paper discusses a method for identifying subproblems by analyzing when design variables were discussed concurrently by human designers. Four clustering techniques for grouping design variables were tested on a range of synthetic datasets designed to resemble data collected from design teams, and the accuracy of the clusters created by each algorithm was evaluated. A spectral clustering method was accurate for most problems and generally performed better than hierarchical (with Euclidean distance metric), Markov, or association rule clustering methods. The method's success should enable researchers to gain new insights into how human designers decompose complex design problems.

scholarly journals EVALUATING STUDENT DESIGN ACTIVITY IN ENGINEERING DESIGN PROJECTS

2011 ◽  
Author(s):  
D. S. Petkau ◽  
D. D. Mann
Keyword(s):  
Engineering Design ◽  
Evaluation Process ◽  
Design Activity ◽  
Design Teams ◽  
Short Term ◽  
Design Problems ◽  
Design Activities ◽  
University Of Manitoba ◽  
Design Projects ◽  
The University

Student design projects in engineering courses are usually short term conceptual design problems. Upon completion of the projects it is difficult to assess which design activities had the greatest contribution to the success of the design. In the fall of 2006, students in 2nd, 3rd, and 4th year Design Trilogy courses at the University of Manitoba were asked to keep extensive design journals. Design teams consisted of multiyear students completing various industry projects. Student design activities recorded in the journals were coded. Data were compared between design teams and between students in the different years of study. This paper describes the evaluation process and reports on the preliminary findings.

Analysis of Decomposability and Complexity for Design Problems in the Context of Decomposition

2004 ◽  
Author(s):  
Li Chen ◽  
Simon Li
Keyword(s):  
Current Practice ◽  
Complexity Analysis ◽  
A Priori ◽  
Optimal Number ◽  
Problem Decomposition ◽  
Phase Decomposition ◽  
Trial And Error ◽  
Two Phase ◽  
Design Problems ◽  
Complex Design

The current practice in problem decomposition assumes that (1) design problems can be rationally decomposed a priori and (2) decomposition can usefully result in complexity reduction a priori. However, this assumption is not always true in reality. In response to this concern, this paper introduces the notions of decomposability and complexity to problem decomposition. In particular, a full scale of decomposability analysis and complexity analysis in the context of decomposition are presented along with approaches and algorithms. These new analyses not only address the viability and validity of decomposition, but also help achieve an optimal number of sub-problems during decomposition, which is usually determined by trial and error or a priori. Further, a procedure that is able to combine these new analyses into our two-phase decomposition framework is described. This effort leads to an enhanced decomposition method that is able to find the most appropriate decomposition solution to a complex design problem.

Understanding Designers Behavior in Parameter Design Activities

2017 ◽  
Author(s):  
Turki Alelyani ◽  
Ye Yang ◽  
Paul T. Grogan
Keyword(s):  
Parameter Design ◽  
Future Research ◽  
Design Experiment ◽  
Problem Complexity ◽  
Design Problems ◽  
Complex Design ◽  
Design Activities ◽  
Successful Design ◽  
And Performance ◽  
The Individual

Successful design processes and tools are vital for the success of any design project, particularly when developing aerospace, automotive and other complex systems that can entail imposing design constraints to meet desired objectives. These constraints, coupled with a lack of uniform strategies to define, acquire and process the interaction between designers and tools, add new challenges to the design process. So appropriate processes and tools that allow problem designers to assist in framing and resolving complex design problems can extend the power of the individual working memory, according to previous research. This current research investigates the behavior of engineers working on a parameter design experiment. In the study, 30 subjects solved parameter design problems with both coupled and uncoupled variables. Results showed a relationship among designers’ actions and other features such as gender, recorded error, problem complexity, and performance. These findings can guide future research into engineering design and can inform ideas for better strategies for various aspects of parameter designing.

Interdisciplinary Graduate Design Programs: Results and Recommendations From a NSF Workshop

2009 ◽  
Author(s):  
Timothy W. Simpson ◽  
Samuel T. Hunter ◽  
Cari Bryant-Arnold ◽  
Matthew Parkinson ◽  
Russell R. Barton ◽  
...  
Keyword(s):  
Design Research ◽  
Well Being ◽  
Design Problems ◽  
Future Directions ◽  
Research And Teaching ◽  
Interdisciplinary Design ◽  
National Competitiveness ◽  
Complex Design ◽  
Design Activities ◽  
The Common

Improving the creativity and innovativeness of U.S. graduate students is a mandate for national competitiveness and social well-being. Despite this imperative, many are uncertain about how to best prepare students for tackling the complex design problems of the future, some that we know about and others yet to be uncovered. With this in mind, we convened a two-day workshop at the National Science Foundation (NSF) in Arlington, VA to discuss the challenges, successes, and future directions for interdisciplinary graduate design programs that have recently emerged or are being established to address this critical need. Not including NSF personnel, 42 people from academia and industry gathered to learn about nine existing interdisciplinary design programs. Three panels were also held to discuss: (1) overcoming interdisciplinary differences in research and teaching, (2) industry perspectives on interdisciplinary design programs, and (3) future directions and program developments. A number of common themes emerged from the workshop, including the disciplinary characteristics of interdisciplinary design, the varying perspectives on the design process, pedagogical approaches toward teaching interdisciplinary design, structuring interdisciplinary design degrees, and sustainability of an interdisciplinary design discipline. Based on the dialogue at the workshop and our analysis of the common themes, we offer ten recommendations divided into three areas: (1) advance interdisciplinary design activities, (2) enhance interdisciplinary design programs, and (3) support interdisciplinary design research.

scholarly journals DECOMPOSITION AND RECOMPOSITION STRATEGIES OF PROFESSIONAL ENGINEERING DESIGN TEAMS

2021 ◽  
Vol 1 ◽  
pp. 871-880
Author(s):  
Julie Milovanovic ◽  
John Gero ◽  
Kurt Becker
Keyword(s):  
Design Process ◽  
Design Theory ◽  
Design Teams ◽  
Theoretical Understanding ◽  
Design Problems ◽  
Engineering Teams ◽  
Complex Design ◽  
Decomposition Strategies ◽  
Design Proposal ◽  
Empirical Foundation

AbstractDesigners faced with complex design problems use decomposition strategies to tackle manageable sub-problems. Recomposition strategies aims at synthesizing sub-solutions into a unique design proposal. Design theory describes the design process as a combination of decomposition and recomposition strategies. In this paper, we explore dynamic patterns of decomposition and recomposition strategies of design teams. Data were collected from 9 teams of professional engineers. Using protocol analysis, we examined the dominance of decomposition and recomposition strategies over time and the correlations between each strategy and design processes such as analysis, synthesis, evaluation. We expected decomposition strategies to peak early in the design process and decay overtime. Instead, teams maintain decomposition and recomposition strategies consistently during the design process. We observed fast iteration of both strategies over a one hour-long design session. The research presented provides an empirical foundation to model the behaviour of professional engineering teams, and first insights to refine theoretical understanding of the use decomposition and recomposition strategies in design practice.

Managing User-Centered Design Activities in Distributed Agile Development

2021 ◽  
Author(s):  
Sultan Alyahya ◽  
Ohoud Almughram
Keyword(s):  
Participatory Design ◽  
Agile Development ◽  
Design Teams ◽  
User Centered Design ◽  
Management Tools ◽  
Daily Work ◽  
Development Teams ◽  
Design Activities ◽  
Computer Based ◽  
User Centered

Abstract The integration of user-centered design (UCD) activities into agile information systems development has become more popular recently. Despite the fact that there are many ways the merging of UCD activities into agile development can be carried out, it has been widely recognized that coordinating design activities with development activities is one of the most common problems, especially in distributed environments where designers, developers and users are spread over several sites. The main approach to coordinate UCD activities with distributed agile development is the use of informal methods (e.g. communication through using video conference tools). In addition to the temporal, geographical and socio-cultural barriers associated with this type of methods, a major limitation is a lack of awareness of how UCD activities and development activities affect each other. Furthermore, some agile project management tools are integrated with design platforms but fail to provide the necessary coordination that helps team members understand how the design and development activities affect their daily work. This research aims to support the effective management of integrating UCD activities into distributed agile development by (i) identifying the key activity dependencies between UX design teams and development teams during distributed UCD/agile development and (ii) designing a computer-based system to provide coordination support through managing these activity dependencies. In order to achieve these objectives, two case studies are carried out. Our findings revealed 10 main dependencies between UCD design teams and development teams as shown by six types of activity. In addition, the participatory design approach shows that developing a computer-based system to manage seven of these selected dependencies is achievable.

Multi-Objective Optimization of an Autonomous Underwater Vehicle

2009 ◽  
Vol 43 (2) ◽  
pp. 48-60 ◽  
Author(s):  
M. Martz ◽  
W. L. Neu
Keyword(s):  
Design Space ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Design Problems ◽  
Single Measure ◽  
Design Variables ◽  
Complex Design ◽  
Final Design ◽  
Undersea Vehicle ◽  
Hierarchy Process

AbstractThe design of complex systems involves a number of choices, the implications of which are interrelated. If these choices are made sequentially, each choice may limit the options available in subsequent choices. Early choices may unknowingly limit the effectiveness of a final design in this way. Only a formal process that considers all possible choices (and combinations of choices) can insure that the best option has been selected. Complex design problems may easily present a number of choices to evaluate that is prohibitive. Modern optimization algorithms attempt to navigate a multidimensional design space in search of an optimal combination of design variables. A design optimization process for an autonomous underwater vehicle is developed using a multiple objective genetic optimization algorithm that searches the design space, evaluating designs based on three measures of performance: cost, effectiveness, and risk. A synthesis model evaluates the characteristics of a design having any chosen combination of design variable values. The effectiveness determined by the synthesis model is based on nine attributes identified in the U.S. Navy’s Unmanned Undersea Vehicle Master Plan and four performance-based attributes calculated by the synthesis model. The analytical hierarchy process is used to synthesize these attributes into a single measure of effectiveness. The genetic algorithm generates a set of Pareto optimal, feasible designs from which a decision maker(s) can choose designs for further analysis.

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