Decomposition and Representation Methods in Mechanical Design

Kusiak, Andrew; Larson, Nick

doi:10.1115/1.2836453

Cited by 65 publications

(20 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the world of design, there are three types of design decomposition, including product decomposition, problem decomposition and process decomposition (Kusiak & Larson, 1995).…”

Section: Problem Decomposition/recompositionmentioning

confidence: 99%

Expert vs. novice: Problem decomposition/recomposition in engineering design

Song

Becker

2014

2014 International Conference on Interactive Collaborative Learning (ICL)

View full text Add to dashboard Cite

The purpose of this research was to investigate the differences of using problem decomposition and problem recomposition among dyads of engineering experts, dyads of engineering seniors, and dyads of engineering freshmen. Fifty participants took part in this study. Ten were engineering design experts, 20 were engineering seniors, and 20 were engineering freshmen. Participants worked in dyads to complete an engineering design challenge within an hour. The entire design process was video and audio recorded.After the design session, members participated in a group interview.This study used protocol analysis as the methodology. Video and audio data were transcribed, segmented, and coded. Two coding systems including the FBS ontology and "levels of the problem" were used in this study. A series of statistical techniques were iv used to analyze data. Interview data and participants' design sketches also worked as supplemental data to help answer the research questions.By analyzing the quantitative and qualitative data, it was found that students used less problem decomposition and problem recomposoition than engineer experts in engineering design. This result implies that engineering education should place more importance on teaching problem decomposition and problem recomposition. Students were found to spend less cognitive effort when considering the problem as a whole and interactions between subsystems than engineer experts. In addition, students were also found to spend more cognitive effort when considering details of subsystems. These results showed that students tended to use dept-first decomposition and experts tended to use breadth-first decomposition in engineering design. The use of Function (F), Behavior (B), and Structure (S) among engineering experts, engineering seniors, and engineering freshmen was compared on three levels. Level 1 represents designers consider the problem as an integral whole, Level 2 represents designers consider interactions between subsystems, and Level 3 represents designers consider details of subsystems. The results showed that students used more S on Level 1 and 3 but they used less The purpose of this research was to investigate the design behavior. A commonly used design strategy called "problem decomposition and recomposition" was the focus of the study. Dyads of engineering experts, dyads of engineering seniors, and dyads of engineering freshmen completed an engineering design challenge within an hour. The entire design process was video and audio recorded. After the design session, participants participated in a group interview.The conversation and behavior from the design were transcribed, segmented, and coded. Two coding systems including the FBS ontology and "levels of the problem" were used in this study. A series of statistical techniques were used to analyze data. Interview data and participants' design sketches also worked as supplemental data to help answer the research questions.There were a series of interesting findings that emerged from analyzing the quantitat...

show abstract

“…In the world of design, there are three types of design decomposition, including product decomposition, problem decomposition and process decomposition (Kusiak & Larson, 1995).…”

Section: Problem Decomposition/recompositionmentioning

confidence: 99%

Expert vs. novice: Problem decomposition/recomposition in engineering design

Song

Becker

2014

2014 International Conference on Interactive Collaborative Learning (ICL)

View full text Add to dashboard Cite

show abstract

“…The use of matrices and graphs to specify the partitioning becomes prohibitive for larger systems due to the large number of variables and functions. Alternative matrix and graph representations have appeared in research on the decomposition of the system design process into individual design tasks (see, e.g., Steward 1981;Eppinger et al 1994;Kusiak and Larson 1995;Browning 2001). The transfer of information between engineers defines precedence relations between the individual tasks that can be captured in matrices or graphs.…”

Section: Existing Approaches For Specification Of the Partitioned Promentioning

confidence: 99%

“…Several representations have appeared in research focused on model-based partitioning (see, e.g., Kusiak and Larson 1995;Krishnamachari and Papalambros 1997;Michelena and Papalambros 1997;Chen et al 2005). Model-based partitioning methods typically rely on matrix or graph abstractions of the couplings between variables and functions to define a sparsity structure of the integrated problem (1).…”

Section: Existing Approaches For Specification Of the Partitioned Promentioning

confidence: 99%

A specification language for problem partitioning in decomposition-based design optimization

Tosserams

Hofkamp

Etman

et al. 2010

Struct Multidisc Optim

View full text Add to dashboard Cite

Decomposition-based design optimization consists of two steps: partitioning of a system design problem into a number of subproblems, and coordination of the design of the decomposed system. Although several generic frameworks for coordination method implementation are available (the second step), generic approaches for specification of the partitioned problem (the first step) are rare. Available specification methods are often based on matrix or graph representations of the entire system. For larger systems these representations become intractable due to the large number of design variables and functions. This article presents a new linguistic approach for specification of partitioned problems in decomposition-based design optimization. With the elements of the proposed specification language, called (the Greek letter "Psi"), a designer can define subproblems, and assemble these into larger systems in a bottom-up fashion. The assembly process allows the system designer to control the complexity and tractability of the problem partitioning task. To facilitate coupling to generic coordination frameworks, a compiler has been developed for that generates an interchange file in the INI format. This INI-definition of the partitioned problem can easily be interpreted by programs written in other languages. The flexibility provided by the language and

show abstract

“…Some examples of coordination algorithms include optimization algorithms (e.g., Collaborative Optimization (CO) [4]), fixed point iteration (e.g., Analytical Target Cascading (ATC) [5]), Newton's method (e.g., ATC [6]), and penalty methods (e.g., ATC and Augmented Lagrangian Decomposition (ALD) [7]). Distributed methods are appropriate when systems are large and sparsely connected [8], when the design environment is distributed [9], or when specialized optimization algorithms can be exploited for solving particular subproblems [10,11]. The techniques introduced in this article can be used to assess quantitatively whether distributed optimization is appropriate for a particular problem.…”

Section: Decomposition-based System Designmentioning

confidence: 99%

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design Optimization

Allison

Kokkolaras

Papalambros

2007

Volume 6: 33rd Design Automation Conference, Parts a and B

View full text Add to dashboard Cite

Solution of complex system design problems using distributed, decomposition-based optimization methods requires determination of appropriate problem partitioning and coordination strategies. Previous optimal partitioning techniques have not addressed the coordination issue explicitly. This article presents a formal approach to simultaneous partitioning and coordination strategy decisions that can provide insights on whether a decomposition-based method will be effective for a given problem. Pareto-optimal solutions are generated to quantify tradeoffs between the sizes of subproblems and coordination problems, as measures of the computational costs resulting from different partitioning-coordination strategies. Promising preliminary results with small test problems are presented. The approach is illustrated on an electric water pump design problem. IntroductionNumerous methods have been developed to solve complex system design problems partitioned into smaller subproblems. This decomposition-based approach can ease several difficulties encountered in system design, such as computational expense and management of complex interactions between system elements. Solving a problem in this way requires system designers to decide how to partition the system into subproblems and how to coordinate solution of subproblems toward a consistent, optimal system design. Partitioning decisions have been studied analytically, while only qualitative guidance exists in the literature

show abstract

Decomposition and Representation Methods in Mechanical Design

Cited by 65 publications

References 17 publications

Expert vs. novice: Problem decomposition/recomposition in engineering design

Expert vs. novice: Problem decomposition/recomposition in engineering design

A specification language for problem partitioning in decomposition-based design optimization

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design Optimization

Contact Info

Product

Resources

About