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Approaches to Modularity in Product Architecture
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Machine Elements.
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Modular product architecture is characterized by the existence of standardized interfaces between the physical building blocks. A module is a collection of technical solutions that perform a function, with interfaces selected for company-specific strategic reasons. Approaches to modularity are the structured methods by which modular product architectures are derived. The approaches include Modular Function Deployment (MFD), Design Structure Matrix (DSM), Function Structure Heuristics and many other, including hybrids. The thesis includes a survey of relevant theory and a discussion of four challenges in product architecture research, detailed in the appended papers.

One common experience from project work is structured methods such as DSM or MFD often do not yield fully conclusive results. This is usually because the algorithms used to generate modules do not have enough relevant data. Thus, we ask whether it is possible to introduce new data to make the output more conclusive. A case study is used to answer this question. The analysis indicates that with additional properties to capture product geometry, and flow of matter, energy, or information, the output is more conclusive.

If product development projects even have an architecture definition phase, very little time is spent actually selecting the most suitable tool. Several academic models are available, but they use incompatible criteria, and do not capture experience-based or subjective criteria we may wish to include. The research question is whether we can define selection criteria objectively using academic models and experience-based criteria. The author gathers criteria from three academic models, adds experience criteria, performs a pairwise comparison of all available criteria and applies a hierarchical cluster analysis, with subsequent interpretation. The resulting evaluation model is tested on five approaches to modularity. Several conclusions are discussed. One is that of the five approaches studied, MFD and DSM have the most complementary sets of strengths and weaknesses, and that hybrids between these two fundamental approaches would be particularly interesting.

The majority of all product development tries to improve existing products. A common criticism against all structured approaches to modularity is they work best for existing products. Is this perhaps a misconception? We ask whether MFD and DSM can be used on novel product types at an early phase of product development. MFD and DSM are applied to the hybrid drive train of a Forwarder. The output of the selected approaches is compared and reconciled, indicating that conclusions about a suitable modular architecture can be derived, even when many technical solutions are unknown. Among several conclusions, one is the electronic inverter must support several operating modes that depend on high-level properties of the drive train itself (such as whether regeneration is used). A modular structure for the electronic inverter is proposed.

Module generation in MFD is usually done with Hierarchical Cluster Analysis (HCA), where the results are presented in the form of a Dendrogram. Statistical software can generate a Dendrogram in a matter of seconds. For DSM, the situation is different. Most available algorithms require a fair amount of processing time. One popular algorithm, the Idicula-Gutierrez-Thebeau Algorithm (IGTA), requires a total time of a few hours for a problem of medium complexity (about 60 components). The research question is whether IGTA can be improved to execute faster, while maintaining or improving quality of output. Two algorithmic changes together reduce execution time required by a factor of seven to eight in the trials, and improve quality of output by about 15 percent.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. , 50 p.
Series
Trita-MMK, ISSN 1400-1179 ; 2012:11
Keyword [en]
Clustering Algorithm, Design Structure Matrix, Modular Function Deployment, Product architecture, Product family, Product platform
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-96491ISBN: 978-91-7501-390-9 (print)OAI: oai:DiVA.org:kth-96491DiVA: diva2:530891
Presentation
2012-06-11, Rum B242, Brinellvägen 83, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
QC 20120605Available from: 2012-06-05 Created: 2012-06-05 Last updated: 2012-06-07Bibliographically approved
List of papers
1. Improved Output in Modular Function Deployment Using Heuristics
Open this publication in new window or tab >>Improved Output in Modular Function Deployment Using Heuristics
2009 (English)In: Proceedings of the 17th International Conference on Engineering Design (ICED’09), Vol. 4, 2009, 1-12 p.Conference paper, Published paper (Refereed)
Abstract [en]

In Modular Function Deployment, technical solutions are grouped into modules according tothe product properties and the strategic intentions of the company. Statistical methods such ashierarchical clustering are useful in the formation of potential modules, but a significantamount of manual adjustment and application of engineering common sense is generallynecessary. We propose a method for promoting better output from the clustering algorithmused in the conceptual module generation phase by adding Convergence Properties, acollective reference to data identified as option properties, geometrical information, flowheuristics, and module driver compatibility. The method was tested in a case study based on acordless handheld vacuum cleaner.

Keyword
Conceptual product development, modular products, Modular Function Deployment, module drivers, clustering algorithm, hierarchical clustering, statistical approach, heuristic methods
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-96487 (URN)000302735800001 ()2-s2.0-84859254254 (Scopus ID)9-781904-670087 (ISBN)
Conference
17th International Conference on Engineering Design
Note

QC 20120605

Available from: 2012-06-05 Created: 2012-06-05 Last updated: 2012-09-18Bibliographically approved
2. A Systematic Qualitative Comparison of Five Approaches to Modularity
Open this publication in new window or tab >>A Systematic Qualitative Comparison of Five Approaches to Modularity
2010 (English)In: International Design Conference: Design 2010, 2010, 147-156 p.Conference paper, Published paper (Refereed)
Abstract [en]

An approach to modularity is used to mean the method by which a modular architecture is defined. This paper presents a method by which such approaches can be compared, incorporating both academic and experience-based criteria. The proposed method, based on dendrograms, is applied on MFD, Component-based DSM, Heuristics, and two derived approaches. Derived approaches seem to offer improvements, but also introduce new disadvantages which are absent in the methods on which they build.

Keyword
Modular Function Deployment, Design Structure Matrix, Heuristics, Design for X, qualitative comparison
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-96488 (URN)000301582200016 ()2-s2.0-84861506533 (Scopus ID)
Conference
11th International Design Conference (DISIGN), Dubrovnik, CROATIA
Note

QC 20120605

Available from: 2012-06-05 Created: 2012-06-05 Last updated: 2012-09-05Bibliographically approved
3. Modularization of novel machines: motives, means and opportunities
Open this publication in new window or tab >>Modularization of novel machines: motives, means and opportunities
2010 (English)In: Proceedings of NordDesign 2010, the 8th International NordDesign Conference: Chalmers University of Technology,Gothenburg, Sweden, August 25-27, 2010, 2010, 435-444 p.Conference paper, Published paper (Refereed)
Abstract [en]

Modularization approaches are often used to restructure mature products with known technical content, but not to assist new development of products with a high innovation content or soft interactive requirements. This paper investigates if various clustering techniques can be used to identify module candidates in matrix representations of evolving product properties, including interactive properties, and component architectures. The proposed approach is tested on the hybrid drive train of a novel forwarder. Forwarders are used in the forestry industry to transport logs from the felling area to a landing area close to a road accessible by trucks. Continuous efficiency improvements, new emission requirements, and the need to configure machine for different applications stresses the need for a modular product architecture.

Keyword
DSM, forwarder, hybrid technology, new development, dendrogram
National Category
Other Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-96489 (URN)2-s2.0-84859899408 (Scopus ID)
Conference
8th International NordDesign Conference, NordDesign 2010; Goteborg; Sweden; 25 August 2010 through 27 August 2010
Note

QC 20120605

Available from: 2012-06-05 Created: 2012-06-05 Last updated: 2014-09-02Bibliographically approved
4. Improved Clustering Algorithm for Design Structure Matrix
Open this publication in new window or tab >>Improved Clustering Algorithm for Design Structure Matrix
2012 (English)In: Proceedings of the ASME 2012 International Design EngineeringTechnical Conferences & Computers and Information in Engineering Conference, 2012Conference paper, Published paper (Refereed)
Abstract [en]

For clustering a large Design Structure Matrix (DSM), computerized algorithms are necessary. A common algorithm by Thebeau uses stochastic hill-climbing to avoid local optima. The output of the algorithm is stochastic, and to be certain a very good clustering solution has been obtained, it may be necessary to run the algorithm thousands of times. To make this feasible in practice, the algorithm must be computationally efficient. Two algorithmic improvements are presented. Together they improve the quality of the results obtained and increase speed by a factor of seven to eight for normal clustering problems. The proposed new algorithm is applied to a cordless handheld vacuum cleaner.

Keyword
Design Structure Matrix; Clustering algorithm; Stochastic hill-climbing
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-96490 (URN)
Conference
ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference
Note

QC 20120605

Available from: 2012-06-05 Created: 2012-06-05 Last updated: 2012-10-18Bibliographically approved

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