Miyako Wilson

SLIM: collaborative model-based systems engineering workspace for next-generation complex systems

Development of complex systems is a collaborative effort spanning disciplines, teams, processes, software tools, and modeling formalisms. It is the vision of model-based systems engineering (MBSE) to enable a consistent, coherent, interoperable, and evolving model of a system throughout its lifecycle. However, no currently available modeling language can represent all aspects of a system (including system-of-systems) at all levels of abstraction across the lifecycle.

4.3.1 Satellites to Supply Chains, Energy to Finance —SLIM for Model-Based Systems Engineering

Development of complex systems is a collaborative effort spanning disciplines, teams, processes, software tools, and modeling formalisms. Increasing system complexity, reduction in available resources, globalized and competitive supply chains, and volatile market forces necessitate that a unified model-based systems engineering environment replace ad-hoc, document-centric and point-to-point environments in organizations developing complex systems. To address this challenge, we envision SLIM—a collaborative, model-based systems engineering workspace for realizing next-generation complex systems. SLIM uses SysML to represent the front-end conceptual abstraction of a system that can “co-evolve” with the underlying fine-grained connections to models in discipline-specific tools and standards. With SLIM, system engineers can drive automated requirements verification, system simulations, trade studies and optimization, risk analyses, design reviews, system verification and validation, and other key systems engineering tasks from the earliest stages of development directly from the SysML-based system model. SLIM provides analysis tools that are independent of any systems engineering methodology, and integration tools that connect SysML with a wide variety of COTS and in-house design and simulation tools. We are presenting SLIM and its applications in two papers. In Part 1 (this paper), we present the motivation and challenges that led to SLIM. We describe the conceptual architecture (section 1) and use cases (section 2) of SLIM followed by tools available for production and evaluation usage (section 3). In Part 2 paper—SLIM Applications—we present the applications of SLIM tools to a variety of domains, both in traditional as well as non-traditional domains of systems engineering. Representative examples from space, energy, infrastructure, manufacturing and supply chain, military operations, and bank systems are presented. * Corresponding author: Manas Bajaj, manas.bajaj@intercax.com, phone: +1-404-592-6897. Preferred citation: Bajaj, M., Zwemer, D., Peak, R., Phung, A., Scott, A. and Wilson, M. (2011). Satellites to Supply Chains, Energy to Finance — SLIM for Model-Based Systems Engineering, Part 1: Motivation and Concept of SLIM. 21st Annual INCOSE International Symposium, Denver, CO, June 20-23, 2011.

Towards next-generation design-for-manufacturability (DFM) frameworks for electronics product realization

This paper elucidates the process architecture of a pilot implementation of a DFM Framework (specifically the SFM DFM Framework or SDF), which consists of four key ingredients. The first ingredient is a Design Integrator that acquires product design information from an ECAD tool and in-house sources (each populating a subset of the design) and consolidates them into a STEP AP210 model. The second ingredient is a Rule-based Expert System (initiated at Boeing) that captures the manufacturability constraints as DFM rules and evaluates printed circuit assembly (PCA) designs against them. The third ingredient is a Design View Generator that extracts design information from the AP210 model (first ingredient) and library database and derives a Kappa design model for the expert system (second ingredient) to evaluate. The fourth ingredient is the Results Viewer that helps the user browse DFM analysis results and identify design improvement opportunities. This implementation of the SDF demonstrates the ability to extract PCA design information and build a higher fidelity standards-based design model. Additionally, it also shows the capability of Rule-based Expert Systems to emulate manufacturability checks on product (PCAs in this case) designs as well as increase analysis coverage and reduce human checking time via automation.

4.3.3 Satellites to Supply Chains, Energy to Finance -SLIM for Model-Based Systems Engineering: Part 2: Applications of SLIM

Development of complex systems is a collaborative effort spanning disciplines, teams, processes, software tools, and modeling formalisms. Increasing system complexity, reduction in available resources, globalized and competitive supply chains, and volatile market forces necessitate that a unified model-based systems engineering environment replace ad-hoc, document-centric and point-to-point environments in organizations developing complex systems. To address this challenge, we envision SLIM—a collaborative, model-based systems engineering workspace for realizing next-generation complex systems. SLIM uses SysML to represent the front-end conceptual abstraction of a system that can “co-evolve” with the underlying fine-grained connections to models in discipline-specific tools and standards. With SLIM, system engineers can drive automated requirements verification, system simulations, trade studies and optimization, risk analyses, design reviews, system verification and validation, and other key systems engineering tasks from the earliest stages of development directly from the SysML-based system model. SLIM provides analysis tools that are independent of any systems engineering methodology, and integration tools that connect SysML with a wide variety of COTS and in-house design and simulation tools. We are presenting SLIM and its applications in two papers. In Part 1 paper—Motivation and Concept of SLIM—we presented the motivation and challenges that led to SLIM, the conceptual architecture of SLIM, and SLIM tools available for production and evaluation usage. In Part 2 (this paper), we present the applications of SLIM tools to a variety of domains, both in traditional as well as non-traditional domains of systems engineering. Representative SysML models and results of trade studies, risk analysis, and other system engineering tasks performed using SLIM tools are presented for the following domains—space systems, energy systems, infrastructure systems, manufacturing and supply chain systems, military operations, and bank systems. * Corresponding author: Manas Bajaj, manas.bajaj@intercax.com, phone: +1-404-592-6897. Preferred citation: Bajaj, M., Zwemer, D., Peak, R., Phung, A., Scott, A. and Wilson, M. (2011). Satellites to Supply Chains, Energy to Finance — SLIM for Model-Based Systems Engineering, Part 1: Motivation and Concept of SLIM. 21st Annual INCOSE International Symposium, Denver, CO, June 20-23, 2011.

Analysis building blocks: a rich information model context for knowledge-based finite element analysis

In a product design and analysis process, engineers have different usage views towards product information models. The heterogeneous transformation problem has been presented to characterize the resulting gap between design models and analysis models. The multi-representation architecture (MRA) has been developed to realize this transformation through four stepping-stone information representations, including analyzable product models, context-based analysis models, analysis building blocks (ABBs), and solution method models (SMMs). In this paper, our primary focus is on ABBs for solid mechanics and thermal systems that generate FEA SMMs to obtain their results. ABBs, which represent the analytical usage view for analysis engineers, are constructed using an objectoriented knowledge representation known as constrained objects (COBs). ABBs represent product-independent analysis concepts such as continuum mechanics bodies and idealized interconnections as semantically rich, reusable, modular, and tool-independent objects. To demonstrate the efficacy of the ABB model, an electronic chip package thermomechanical analysis test case is overviewed. This extended ABB approach provides an effective way to capture engineering knowledge and decrease FEA modeling time.

An Information-Driven FEA Model Generation Approach for Chip Package Applications

In the electronic chip package development process, Finite Element Analysis (FEA) modeling is widely used as a virtual prototyping technology to achieve good designs. Due to the complexity and variability in materials, geometric shapes, and connectivity configurations, etc. in a chip package, FEA modeling is a tedious and time-consuming activity. Typically finite element modeling takes hours or even days to complete an analysis for a single chip package design. The Multirepresentation Architecture (MRA) is presented as a framework to facilitate automatic transformations of design models into analysis models through four stepping-stone information representations: (1) analyzable product models (APM), (2) context-based analysis models (CBAM), (3) analysis building blocks (ABBs), and (4) solution method models (SMMs). The ABB models describe theoretical physical systems while SMMs represent the ABB models in solution technique-specific form, such as FEA. In this paper, we present an information-driven FEA modeling approach facilitating the mapping between ABBs and SMMs by first decomposing the geometry into meshable bodies and subsequently generating vendor-specific SMMs. To demonstrate this FEA modeling approach, a chip package thermomechanical analysis example is given. The informationdriven FEA modeling approach is shown to be an effective and efficient method for capturing engineering information in chip package products, as well as decreasing FEA modeling time.Copyright

Diagnosing Engineering Information Interoperability: Recognizing the Value of Standards-Based PLM — Part 1

The notion of an open standards-based product lifecycle management (PLM) framework is gaining momentum. In this paper, we describe the idea of a standards-based collective product model (CPM) and its interaction with domain models native to typical engineering tools. A critical hurdle in the development of the CPM from domain models is assessing the compatibility of information in these native models to its corresponding standards-based representation. To address this, we use the concept of “degree-of-openness” of engineering information. This concept comprises three metrics, namely compatibility, coverage and completeness that are used to evaluate the interoperability of information in tool-specific models with its corresponding standards-based representation. We also demonstrate GT-Diagnostics, a prototype tool that evaluates these metrics. Using electrical and mechanical CAD examples, we illustrate the value of these metrics in understanding the relative interoperability of information for engineering and business decision making. Results indicate that the metrics help to identify the sources of incompatibility of information and the areas of possible improvement in the compared schemas.© 2005 ASME

Metrics for Degree-of-Openness of Engineering Information: Recognizing the Value of Standards-Based PLM — Part 2

Over a product lifecycle, many engineering tools are used to create computer-based models that need to interact. This poses interoperability problems because of the conflicting formats of the models and differing scopes of the tools. One proposed solution is an open standards-based product lifecycle management (PLM) framework. However, the use of open standards is hindered by the lack of knowledge regarding their actual and potential usage in current engineering processes. To overcome this hurdle and evaluate the opportunities and extent to which open standards can be used in such PLM frameworks, we develop three metrics for degree-of-openness of engineering information: compatibility, coverage, and completeness. To demonstrate the usefulness of the proposed metrics, we assess circuit board design information that is transferred between native models of an electronic CAD system and the STEP AP210 standard (ISO 10303-210). This preliminary experience shows that each of the three useful metrics provides a limited aspect of degree-of-openness, and the combination of these metrics provides a single more holistic degree-of-openness indicator.Copyright