Tolga Kurtoglu

A Computational Technique for Concept Generation

Few computational tools exist to assist designers during the conceptual phase of design, and design success is often heavily weighted on personal experience and innate ability. Many well-known methods (e.g. brainstorming, intrinsic and extrinsic searches, and morphological analysis) are designed to stimulate a designer’s creativity, but ultimately still rely heavily on individual bias and experience. Under the premise that quality designs comes from experienced designers, experience in the form of design knowledge is extracted from existing products and stored for reuse in a web-based repository. This paper presents an automated concept generation tool that utilizes the repository of existing design knowledge to generate and evaluate conceptual design variants. This tool is intended to augment traditional conceptual design phase activities and produce numerous feasible concepts early in the design process.Copyright

A Graph-Based Fault Identification and Propagation Framework for Functional Design of Complex Systems

In this paper, the functional-failure identification and propagation (FFIP) framework is introduced as a novel approach for evaluating and assessing functional-failure risk of physical systems during conceptual design. The task of FFIP is to estimate potential faults and their propagation paths under critical event scenarios. The framework is based on combining hierarchical system models of functionality and configuration, with behavioral simulation and qualitative reasoning. The main advantage of the method is that it allows the analysis of functional failures and fault propagation at a highly abstract system concept level before any potentially high-cost design commitments are made. As a result, it provides the designers and system engineers with a means of designing out functional failures where possible and designing in the capability to detect and mitigate failures early on in the design process. Application of the presented method to a fluidic system example demonstrates these capabilities.

Automated synthesis of electromechanical design configurations from empirical analysis of function to form mapping

For an ideal design process, designers envision a configuration of components prior to determining dimensions or sizes of these components. Given the breadth of the component space, the design of any future artefact must be carefully planned to take advantage of the diverse set of possibilities. We conjecture that computational design tools could be developed to help designers navigate the design space in creating configurations from detailed specifications of function. In this research, a methodology is developed that extracts design knowledge from an expanding online library of engineering artefacts in the form of grammar rules. From an initial implementation of 189 rules extracted from 23 products, we demonstrate a computational process that builds new design configurations by borrowing concepts from how common functions are solved in related designs.

Integrating system health management into the early design of aerospace systems using Functional Fault Analysis

This paper introduces a systematic design methodology, namely the functional fault analysis (FFA), developed with the goal of integrating SHM into early design of aerospace systems. The basis for the FFA methodology is a high-level, functional model of a system that captures the physical architecture, including the physical connectivity of energy, material, and data flows within the system. The model also contains all sensory information, failure modes associated with each component of the system, the propagation of the effects of these failure modes, and the characteristic timing by which fault effects propagate along the modeled physical paths. Using this integrated model, the designers and system analysts can assess the sensor suitepsilas diagnostic functionality and analyze the ldquoracerdquo between the propagation of fault effects and the fault detection isolation and response (FDIR) mechanisms designed to compensate and respond to them. The Ares I Crew Launch Vehicle has been introduced as a case example to illustrate the use of the Functional Fault Analysis (FFA) methodology during system design.

Automating the conceptual design process: “from black box to component selection”

Abstract Conceptual design is a vital part of the design process during which designers first envision new ideas and then synthesize them into physical configurations that meet certain design specifications. In this research, a suite of computational tools is developed that assists the designers in performing this nontrivial task of navigating the design space for creating conceptual design solutions. The methodology is based on automating the function-based synthesis paradigm by combining various computational methods. Accordingly, three nested search algorithms are developed and integrated to capture different design decisions at various stages of conceptual design. The implemented system provides a method for automatically generating novel alternative solutions to real design problems. The application of the approach to the design of an electromechanical device shows the methods range of capabilities and how it serves as a comparison to human conceptual design generation and as a tool suite to complement the skills of a designer.

A Validation Study of an Automated Concept Generator Design Tool

The current version of the Concept Generator, an automated mathematically-based design tool, is studied in an effort to validate its general approach and establish research goals for further development. As part of the study, four undergraduate engineering researchers from the University of Missouri-Rolla and University of Texas at Austin execute a qualitative study of the software’s effectiveness at producing useful design solutions. The students engage in several activities designed to test the capabilities of this early version of the software. A report of their results and analyses identifies the benefits and disadvantages of the software (and underlying method) as viewed at this stage of development. Furthermore, the design solution data collected by the undergraduate researchers is analyzed more quantitatively during a post-study investigation. Both the qualitative and quantitative studies indicate that the Concept Generator is a promising first step toward the creation of an effective design tool for the conceptual phase of design. Furthermore, the student reports on their hands-on experiences with the software identify strengths and weaknesses of this early version of the Concept Generator and help establish many avenues for further development of the design tool.Copyright

A Component Taxonomy as a Framework for Computational Design Synthesis

In this paper, we present our findings on the development of a taxonomy for electromechanical components. In building this taxonomy, we have two main objectives: First, we strive to establish a framework for future computational tools that archive, search, or reuse component knowledge during the conceptual phase of design. Second, we aim to define a standard vocabulary that derives uniformity and consistency in the representation of electromechanical component space. Through both empirically dissecting existing products and defining categories based on functional analysis, we defined 135 generic component types. The use and necessity of the resulting taxonomy by a suite of computational design tools are illustrated in two applications of conceptual design.

Capturing Empirically Derived Design Knowledge for Creating Conceptual Design Configurations

In an ideal design process, designers envision a configuration of components prior to determining dimensions or sizes of these components. Given the breadth of suppliers and production methods that exist today, most engineered artifacts are a mix of both custom-made parts and OEM (original equipment manufacturer) parts. The design of any future artifact must be carefully planned to take advantage of the diverse set of possibilities. We conjecture that computational design tools could be developed to help designers navigate the design space in creating configurations from detailed specifications of function. In this research, a methodology is developed that extracts design knowledge from an expanding online library of components in the form of grammar rules. From an initial implementation of forty-five rules compiled from 15 components extracted from three products, we demonstrate a computational process that builds a new design configuration by borrowing concepts from how common functions are solved in related designs.

Flow State Logic (FSL) for Analysis of Failure Propagation in Early Design

For safety critical complex systems, reliability and risk analysis are important design steps. Implementing these analyses early in the design stage can reduce costs associated with redesign and provide important information on design viability. In the past several years, various research methods have been presented in the design community to move reliability analysis into the early conceptual design stages. These methods all use a functional representation as the basis for reliability analysis. This paper asserts that, in non-nominal system states, the functional representation limits the scope of failure analysis. Specifically, when failures are modeled to propagate along energy, material, and signal (EMS) flows, a nominal-state functional model is insufficient for modeling all types of failures. To capture possible failure propagation paths, a function-based reliability method must consider all potential flows, and not be limited to the function structure of the nominal state. In this light, this paper introduces the Flow State Logic (FSL) method as a means for reasoning on the state of EMS flows that allows the assessment of failure propagation over potential flows that were not considered in a functional representation of a “nominally functioning” design. A liquid fueled rocket engine serves as a case study to illustrate the benefits of the methodology.Copyright

A framework for systematic benchmarking of monitoring and diagnostic systems

In this paper, we present an architecture and a formal framework to be used for systematic benchmarking of monitoring and diagnostic systems and for producing comparable performance assessments of different diagnostic technologies. The framework defines a number of standardized specifications, which include a fault catalog, a library of modular test scenarios, and a common protocol for gathering and processing diagnostic data. At the center of the framework are 13 benchmarking metric definitions. The calculation of metrics is illustrated on a probabilistic model-based diagnosis algorithm utilizing Bayesian reasoning techniques. The diagnosed system is a real-world electrical power system, namely the Advanced Diagnostics and Prognostics Testbed (ADAPT) developed and located at the NASA Ames Research Center. The proposed benchmarking approach shows how to generate realistic diagnostic data sets for large-scale, complex engineering systems, and how the generated experimental data can be used to enable ldquoapples to applesrdquo assessments of the effectiveness of different diagnostic and monitoring algorithms.