A macro-micro system architecture analysis framework applied to Smart Grid meter data management systems by Sooraj Prasannan.

Thesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 109-111).This thesis proposes a framework for architectural analysis of a system at the Macro and Micro levels. The framework consists of two phases -- Formulation and Analysis. Formulation is made up of three steps -- Identifying the System Boundary, Identifying the Object-Process System levels using the Object-Process Methodology (OPM) and then creating the Dependency Matrix using a Design Structure Matrix (DSM). Analysis is composed of two steps -- Macro-Level and Micro-Level Analysis. Macro-Level analysis identifies the system modules and their interdependencies based on the OPM and DSM clustering analysis and Visibility-Dependency Signature Analysis. The Micro-Level analysis identifies the central components in the system based on the connectivity metrics of Indegree centrality, Outdegeree centrality, Visibility and Dependency. The conclusions are drawn based on simultaneously interpreting the results derived from the Macro-Level and Micro-Level Analysis. Macro-Analysis is vital in terms of comprehending system scalability and functionality. The modules and their interactions influence the scalability of the system while the absence of certain modules within a system might indicate missing system functionality. Micro-Analysis classifies the components in the system based on connectivity and can be used to guide redesign/design efforts. Understanding how the redesign of a particular node will affect the entire system helps in planning and implementation. On the other hand, design Modification/enhancement of nodes with low connectivity can be achieved without affecting the performance or architecture of the entire system. Identifying the highly central nodes also helps the system architect understand whether the system has enough redundancy built in to withstand the failure of the central nodes. Potential system bottlenecks can also be identified by using the micro-level analysis. The proposed framework is applied to two industry leading Smart Grid Meter Data Management Systems. Meter Data Management Systems are the central repository of meter data in the Smart Grid Information Technology Layer. Exponential growth is expected in managing electrical meter data and technology firms are very interested in finding ways to leverage the Smart Information Technology market. The thesis compares the two Meter Data Management System architectures, and proposes a generic Meter Data Management System by combining the strengths of the two architectures while identifying areas of collaboration between firms to leverage this generic architecture.S.M.in System Design and Managemen

Search-based system architecture development using a holistic modeling approach

This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii

A process model in platform independent and neutral formal representation for design engineering automation

An engineering design process as part of product development (PD) needs to satisfy ever-changing customer demands by striking a balance between time, cost and quality. In order to achieve a faster lead-time, improved quality and reduced PD costs for increased profits, automation methods have been developed with the help of virtual engineering. There are various methods of achieving Design Engineering Automation (DEA) with Computer-Aided (CAx) tools such as CAD/CAE/CAM, Product Lifecycle Management (PLM) and Knowledge Based Engineering (KBE). For example, Computer Aided Design (CAD) tools enable Geometry Automation (GA), PLM systems allow for sharing and exchange of product knowledge throughout the PD lifecycle. Traditional automation methods are specific to individual products and are hard-coded and bound by the proprietary tool format. Also, existing CAx tools and PLM systems offer bespoke islands of automation as compared to KBE. KBE as a design method incorporates complete design intent by including re-usable geometric, non-geometric product knowledge as well as engineering process knowledge for DEA including various processes such as mechanical design, analysis and manufacturing. It has been recognised, through an extensive literature review, that a research gap exists in the form of a generic and structured method of knowledge modelling, both informal and formal modelling, of mechanical design process with manufacturing knowledge (DFM/DFA) as part of model based systems engineering (MBSE) for DEA with a KBE approach. There is a lack of a structured technique for knowledge modelling, which can provide a standardised method to use platform independent and neutral formal standards for DEA with generative modelling for mechanical product design process and DFM with preserved semantics. The neutral formal representation through computer or machine understandable format provides open standard usage. This thesis provides a contribution to knowledge by addressing this gap in two-steps: • In the first step, a coherent process model, GPM-DEA is developed as part of MBSE which can be used for modelling of mechanical design with manufacturing knowledge utilising hybrid approach, based on strengths of existing modelling standards such as IDEF0, UML, SysML and addition of constructs as per author’s Metamodel. The structured process model is highly granular with complex interdependencies such as activities, object, function, rule association and includes the effect of the process model on the product at both component and geometric attributes. • In the second step, a method is provided to map the schema of the process model to equivalent platform independent and neutral formal standards using OWL/SWRL ontology for system development using Protégé tool, enabling machine interpretability with semantic clarity for DEA with generative modelling by building queries and reasoning on set of generic SWRL functions developed by the author. Model development has been performed with the aid of literature analysis and pilot use-cases. Experimental verification with test use-cases has confirmed the reasoning and querying capability on formal axioms in generating accurate results. Some of the other key strengths are that knowledgebase is generic, scalable and extensible, hence provides re-usability and wider design space exploration. The generative modelling capability allows the model to generate activities and objects based on functional requirements of the mechanical design process with DFM/DFA and rules based on logic. With the help of application programming interface, a platform specific DEA system such as a KBE tool or a CAD tool enabling GA and a web page incorporating engineering knowledge for decision support can consume relevant part of the knowledgebase

Function Modelling of Complex Multidisciplinary Systems. Development of a System State Flow Diagram Methodology for Function Decomposition of Complex Multidisciplinary Systems

The complexity of technical systems has increased significantly in order to address evolving customer needs and environmental concerns. From a product development process viewpoint, the pervasive nature of multi-disciplinary systems (i.e. mechanical, electrical, electronic, control, software) has brought some important integration challenges to overcome conventional disciplinary boundaries imposed by discipline specific approaches. This research focuses on functional reasoning, aiming to develop a structured framework based on the System State Flow Diagram (SSFD) for function modelling of complex multidisciplinary systems on a practical and straightforward basis. The framework is developed at two stages. 1) The development of a prototype for the SSFD framework. The proposed SSFD framework are tested and validated through application to selected desktop case studies. 2) Further development and extension of the SSFD framework for the analysis of complex multidisciplinary systems with multiple operation modes and functional requirements. The developed framework is validated on real world case studies collaborated with industrial partners. The main conclusion of this research is that the SSFD framework offers a rigorous and coherent function modelling methodology for the analysis of complex multidisciplinary systems. Further advantages of the SSFD framework is that 1) the effectiveness of the Failure Mode Avoidance (FMA) process can be enhanced by integrating the SSFD framework with relevant tools of the FMA process, and 2) the integration of the SSFD with the SysML systems engineering diagrams is doable, which can promote the take-up of the approach in industry.Automotive Research Centr