SIMULATION OF PRODUCT CHANGE EFFECTS BASED ON DESIGN STRUCTURE AND DOMAIN MAPPING MATRICES

2012 ◽  
pp. 423-435 ◽  
Author(s):  
Sebastian Schneider ◽  
Christopher M. Schlick ◽  
Markus Röwenstrunk ◽  
Susanne Mütze-Niewöhner
Keyword(s):  
Design Structure ◽  
Domain Mapping

A DSM-Based Multiple-Domain Modeling of Product Information

2012 ◽  
Vol 201-202 ◽  
pp. 947-950
Author(s):  
Zhi Chuang Zhang ◽  
Xiao Ping Hu ◽  
Chang Qing Xi
Keyword(s):  
Collaborative Design ◽  
Product Information ◽  
Ship Design ◽  
Management Tool ◽  
Design Structure Matrix ◽  
Prototype System ◽  
Domain Modeling ◽  
Design Structure ◽  
Domain Mapping ◽  
Multiple Domain

Knowledge cannot be promptly shared is the main problem in current ship design processes. Knowledge sharing depended on complete expression of the product information. Therefore, the project management tool—design structure matrix was applied in ship design. Three domains of design structure matrixes including products, tasks and people were built; three domain mapping matrixes which contain each two of the three fields were built too; finally the multiple-domain matrix including these three domains were built. The models established the theory basis for the development of collaborative design prototype system.

Relating Two Domains via a Third: An Approach to Overcome Ambiguous Attributions Using Multiple Domain Matrices

2008 ◽  
Author(s):  
Matthias Kreimeyer ◽  
Stefanie Braun ◽  
Matthias Gu¨rtler ◽  
Udo Lindemann
Keyword(s):  
Matrix Notation ◽  
Additional Information ◽  
Design Structure ◽  
The Matrix ◽  
Domain Mapping ◽  
Spreadsheet Software ◽  
Multiple Domain ◽  
Square Matrix

Design Structure Matrices (DSM) and Domain Mapping Matrices (DMM) are commonly used to model and analyze the relationships within one domain (DSM) or between two domains (DMM). Being assembled into one larger square matrix, having DSMs on its diagonal and DMMs in all other fields, a so-called Multiple Domain Matrix (MDM) is formed. When relating two domains using a DMM, a problem arises when the nature of one individual relationship between the two domains is to be described. Usually, this is modeled by annotating each relationship with the additional information, much like comments in spreadsheet software. This, however, is yet impossible if the relationships should be in matrix notation to allow for algorithmic matrix analyses. Equally, this way, the annotations are not accessible as elements of another matrix, e.g. as DSM. This paper suggests a generic principle to solve the described problem in a way consistent with the matrix methodology. It proposes an approach using MDM and is thereby able to unambiguously provide the nature of each relationship between the elements of two domains. As a DSM is a mere case of a DMM having two identical domains, the approach proposed can equally be used to enrich the relationships within a DSM.

Modeling and Simulation of Service Systems with Design Structure and Domain Mapping Matrices

2014 ◽  
pp. 157-166 ◽  
Author(s):  
Andreas Petz ◽  
Sebastian Schneider ◽  
Sönke Duckwitz ◽  
Christopher M. Schlick
Keyword(s):  
Modeling And Simulation ◽  
Service Systems ◽  
Design Structure ◽  
Domain Mapping

A Unified Framework for Decomposition of Design Structure Matrix and Domain Mapping Matrix

2008 ◽  
Author(s):  
Simon Li ◽  
Li Chen
Keyword(s):  
Engineering Design ◽  
Applied Mathematics ◽  
Organization Structure ◽  
Product Architecture ◽  
Design Structure Matrix ◽  
Unified Framework ◽  
Structure Matrix ◽  
Cross Domain ◽  
Design Structure ◽  
Domain Mapping

In literature, design structure matrix (DSM), which is a square matrix, has been widely used to address single-domain dependency relationships (e.g., product architecture, process workflow, and organization structure). To extend the DSM efforts, a rectangular matrix becomes a logical format to capture and analyze cross-domain dependency relationships, namely, domain mapping matrix (DMM) [1]. In this context, this paper proposes a unified framework for decomposition of DSM and DMM. The unified framework consists of four methodological phases to offer the functions of DSM clustering, DSM sequencing, and DMM decomposition. To support the development of this framework, various decomposition-related techniques from applied mathematics and engineering design are reviewed. Three matrix examples have been used to illustrate the framework’s applicability.

scholarly journals Improving the systems engineering process with multilevel analysis of interactions

2014 ◽  
Vol 28 (4) ◽  
pp. 323-337 ◽  
Author(s):  
Steven D. Eppinger ◽  
Nitin R. Joglekar ◽  
Alison Olechowski ◽  
Terence Teo
Keyword(s):  
Systems Engineering ◽  
Process Model ◽  
Multiple Time ◽  
Engineering Project ◽  
Design Structure ◽  
Integration Test ◽  
Incomplete Coverage ◽  
Domain Mapping ◽  
Complex Engineering ◽  
Offshore Oil Industry

AbstractThe systems engineering V (SE-V) is an established process model to guide the development of complex engineering projects (INCOSE, 2011). The SE-V process involves decomposition and integration of system elements through a sequence of tasks that produce both a system design and its testing specifications, followed by successive levels of build, integration, and test activities. This paper presents a method to improve SE-V implementation by mapping multilevel data into design structure matrix (DSM) models. DSM is a representation methodology for identifying interactions between either components or tasks associated with a complex engineering project (Eppinger & Browning, 2012). Multilevel refers to SE-V data on complex interactions that are germane either at multiple levels of analysis (e.g., component versus subsystem) conducted either within a single phase or across multiple time phases (e.g., early or late in the SE-V process). This method extends conventional DSM representation schema by incorporating multilevel test coverage data as vectors into the off-diagonal cells. These vectors provide a richer description of potential interactions between product architecture and SE-V integration test tasks than conventional domain mapping matrices. We illustrate this method with data from a complex engineering project in the offshore oil industry. Data analysis identifies potential for unanticipated outcomes based on incomplete coverage of SE-V interactions during integration tests. In addition, assessment of multilevel features using maximum and minimum function queries isolates all the interfaces that are associated with either early or late revelations of integration risks based on the planned suite of SE-V integration tests.

Extending Design Structure Matrices and Domain Mapping Matrices by Multiple Design Structure Matrices

2006 ◽  
Author(s):  
Markus Eichinger ◽  
Maik Maurer ◽  
Udo Pulm ◽  
Udo Lindemann
Keyword(s):  
Product Development ◽  
Systems Design ◽  
Integrative Approach ◽  
Engineering Systems ◽  
Holistic View ◽  
Holistic Perspective ◽  
Design Structure ◽  
Domain Mapping ◽  
Process Behavior ◽  
Multiple Product

Design Structure Matrices (DSMs) and Domain Mapping Matrices (DMMs) are generally used by designers for dynamic optimization of engineering design processes and products. Both methodologies help producing valuable results; however, they are lacking a holistic view onto the processes and products. Dependencies that span multiple product development domains can therefore not be recognized with isolated DSM or DMM analysis. In this paper, we present an integrative approach that combines DSMs and DMMs to obtain the Multiple Design Structure Matrix (MDSM). This methodology offers the possibility to analyze multiple product development domains using one coherent matrix representation form. A holistic perspective helps the designer to identify domain-spanning structures that would not have been recognized with single-domain optimization approaches or isolated analysis of the DSMs and DMMs. Domain-spanning structures are important to identify, as they may cause unpredictable product or process behavior. Our research showed that a holistic perspective can help designers to identify important elements more easily and therefore save time and enhance quality in analysis of engineering systems design. The framework we present consists of a proposal for the selection of appropriate product development domains, their integration, and the derivation of analysis results.

Document- and Keyword-based Author Co-citation Analysis

2018 ◽  
Vol 2 (2) ◽  
pp. 70-82 ◽  
Author(s):  
Binglu Wang ◽  
Yi Bu ◽  
Win-bin Huang
Keyword(s):  
Citation Analysis ◽  
Semantic Similarity ◽  
Method Validation ◽  
New Method ◽  
Global Network ◽  
Network Visualization ◽  
Knowledge Domain ◽  
Knowledge Domains ◽  
Domain Mapping ◽  
The Relationship

AbstractIn the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.

Sign in / Sign up

Export Citation Format

Share Document