A Model-Based Functional Modeling and Library Approach for Mechatronic Systems in SysML

2012 ◽  
Author(s):  
Benjamin Kruse ◽  
Clemens Münzer ◽  
Stefan Wölkl ◽  
Arquimedes Canedo ◽  
Kristina Shea
Keyword(s):  
Functional Model ◽  
Mechatronic Systems ◽  
Component Structure ◽  
Functional Basis ◽  
Model Based ◽  
Modeling Approach ◽  
Electric Car ◽  
Functional Models ◽  
Computer Based ◽  
Early Phases

Even though the concept development phase in product development is arguably the most important phase in mechanical and mechatronics design, the available computer-based support for this stage is marginal. This paper presents a new computational model-based method to improve the early phases of mechatronic product design and to facilitate the application from early designs to detailed designs. The paper focuses on model-based Function-Behavior-Structure (FBS) libraries in SysML to support both the manual and computational generation of standard and innovative concepts. In this paper, an approach to re-usable functional models in SysML is presented. The method uses an operator-flow formulation of functions, based on the NIST functional basis, and is validated against a model of an electric car. The generated functional models are validated with respect to the consistency of the flows and tested by associating the functional model directly to the target product component structure. The results of the research are a new modeling approach for function and component libraries in SysML, an associated workflow for modeling of mechatronic systems, and the necessary extensions of the NIST functional basis. The modeling approach provides means for formal functional decomposition followed by an allocation of the functions to structural components that form the target structure.

A Semantic Framework to Integrate Healthcare and Clinical Knowledge in Medical Device Innovation and Design

2014 ◽  
Author(s):  
Thomas J. Hagedorn ◽  
Ian R. Grosse ◽  
Sundar Krishnamurty ◽  
Jack C. Wileden
Keyword(s):  
Engineering Design ◽  
Medical Device ◽  
Functional Model ◽  
Medical Knowledge ◽  
Medical Procedure ◽  
Clinical Knowledge ◽  
Functional Basis ◽  
Functional Models ◽  
Effective Transfer ◽  
Early Phases

Within the medical field, there has been significant progress in the development of ontologies and their subsequent use to represent and utilize knowledge more effectively. These have culminated in the creation of large, curated medical ontologies for use in a wide array of applications, as well as higher level frameworks to organize and mitigate conflicts between disparate ontologies. While the engineering field has not been a similar progress in developing and adopting curated ontologies, there has been extensive research into how to effectively use semantic frameworks in engineering knowledge management and design in general, and specifically for the effective creation and documentation of functional basis models. Functional models are a useful tool in the early phases of product design, as they can help more effectively define goals and represent how a product must behave to accomplish these goals. In the specific realm of medical device design however, this process is complicated by a number of factors, including the complexity of the healthcare system and clinical knowledge, as well as a lack of domain specific expertise in the engineering field. Because of these challenges, effective transfer of information from medical domain experts to an engineering context and subsequent utilization of this information are essential to the success of a medical device innovation project. Despite the magnitude and importance of this challenge, few tools exist to help designers record, contextualize, and utilize medical knowledge for the specific purpose of engineering design. In this paper, we present a framework for directly integrating clinical knowledge relating to medical science and practice into the early phases of the engineering process to assist in medical device innovation and design. To accomplish this, existing medical and engineering ontologies were researched, obtained, and interlinked so as to explicitly tie functional models of medical device designs to the underlying medical clinical knowledge and procedures that define a product’s operational environment. The result is a framework that unifies the knowledge embodied in large medical ontologies with the functional basis ontology. This integration facilitates the effective preservation and use of medical knowledge in functional model creation and in the engineering design innovation process in general. To demonstrate the potential usefulness of this framework, we present a simple example of how our framework can be used to associate a functional model with a deconstructed medical procedure, thus enabling the seamless integration of a medical perspective directly into an engineering model.

Development of a Functional Basis for Design

1999 ◽  
Author(s):  
Robert B. Stone ◽  
Kristin L. Wood
Keyword(s):  
Classification Scheme ◽  
Mechanical Design ◽  
Functional Model ◽  
Coding System ◽  
Structure Generation ◽  
Functional Basis ◽  
Product Function ◽  
Functional Models ◽  
Functional Representations ◽  
Architecture Development

Abstract Functional models represent a form independent blueprint of a product. As with any blueprint or schematic, a consistent language or coding system is required to ensure others can read it. This paper introduces such a design language, called a functional basis, where product function is characterized in a verb-object (function-flow) format. The set of functions and flows is intended to comprehensively describe the mechanical design space. Clear definitions are provided for each function and flow. The functional basis is compared to previous functional representations and is shown to subsume these attempts as well as offer a more consistent classification scheme. An example is provided for using the functional basis to form a functional model. Applications to the areas of product architecture development, function structure generation, and design information archival and transmittal are discussed.

Question-by-Question Interrater Analysis and Suggestions for Improvements of a Functional Model Scoring Rubric

2018 ◽  
Author(s):  
Alexander R. Murphy ◽  
Jacob T. Nelson ◽  
Matt R. Bohm ◽  
Robert L. Nagel ◽  
Julie S. Linsey
Keyword(s):  
Interrater Reliability ◽  
Functional Model ◽  
System Function ◽  
Functional Modeling ◽  
Component Structure ◽  
Functional Models ◽  
Ongoing Development ◽  
Evaluation Metric ◽  
Vague Language ◽  
Functional Components

Functional modeling is a tool used for system abstraction. By divorcing system function from component structure, functional modeling allows designers to more easily identify design opportunities and compartmentalize product functions, which can lead to innovation during the ideation process. In this paper, we examine the reliability of a rubric used to evaluate student-generated functional models by comparing interrater reliabilities on a question-by-question basis from a previous study where an examination of the reliability of each question was not assessed. We then suggest changes to the rubric in order to improve the rubric’s overall interrater reliability as well as its question-by-question interrater reliability. These rubric alterations include clarification of vague language, inclusion of examples and counter examples, and a procedure for handling nonexistent functional components as opposed to incorrect or “nonsensical” functional components. This work is in contribution to the ongoing development of this functional modeling rubric as an education instrument. As functional modeling becomes more widely accepted in the design community and in engineering curricula, it is important to have a validated evaluation metric with which to assess student-generated functional models.

A Theory for the Development of Conceptual Functional Models for Automation of Manual Processes

2007 ◽  
Author(s):  
Robert L. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Conceptual Design ◽  
Functional Model ◽  
Process Models ◽  
Functional Modeling ◽  
Functional Basis ◽  
Functional Models ◽  
Electromechanical Products ◽  
The Creation

Conceptual design is a vital stage in the development of any product, and its importance only increases with the complexity of a design. Functional modeling with the Functional Basis provides a framework for the conceptual design of electromechanical products. This framework is just as applicable to the conceptual design of automated solutions where an engineered product with components spanning multiple engineering domains is designed to replace or aid a human and his or her tools in a human-centric process. This paper presents research toward the simplification of the generation of conceptual functional models for automation solutions. The presented methodology involves the creation of functional and process models to fully explore existing human operated tasks for potential automation. Generated functional and process models are strategically combined to create a new conceptual functional model for an automation solution to potentially automate the human-centric task. The presented methodology is applied to the generation of a functional model for a conceptual automation solution. Then conceptual automation solutions generated through the presented methodology are compared to existing automation solutions to demonstrate the effectiveness of the presented methodology.

Towards Rules for Functional Composition

2008 ◽  
Author(s):  
Benjamin W. Caldwell ◽  
Gregory M. Mocko
Keyword(s):  
Conceptual Design ◽  
Functional Model ◽  
Functional Composition ◽  
Functional Decomposition ◽  
Functional Basis ◽  
Functional Models ◽  
Hierarchical Levels ◽  
Unknown Solution

Functional decomposition is used in conceptual design to divide an overall problem with an unknown solution into smaller problems with known solutions. The procedure for functional decomposition, however, has not been formalized. In a larger effort to understand and develop rules for functional decomposition, this paper develops rules for composition of reverse-engineered functional models. First, the functional basis hierarchy is used in an attempt to compose the functional model of a hair dryer, which does not produce the desired results. Second, a set of rules for composition is presented and applied to the hair dryer functional model. This composed functional model is more similar to the desired decomposition result than the functional model developed by changing hierarchical levels. Ten additional functional models are also composed and the results shown. The findings demonstrate that composition rules can be developed empirically through analysis of functional models.

Functional device models and model-Based diagnosis in adaptive design

1996 ◽  
Vol 10 (4) ◽  
pp. 355-370 ◽  
Author(s):  
Ashok K. Goel ◽  
Eleni Stroulia
Keyword(s):  
Adaptive Design ◽  
Functional Model ◽  
Knowledge System ◽  
Causal Knowledge ◽  
Specific Kind ◽  
Structural Element ◽  
Model Based ◽  
Functional Models ◽  
Behavior Function ◽  
Types Of Information

AbstractWe analyze the diagnosis task in the context of adaptive design and redesign of physical devices. We identify three types of diagnosis tasks that differ in the types of information they take as input: the design does not achieve a desired function of the device, the design results in an undesirable behavior, and a specific structural element in the design misbehaves. We describe a model-based approach for solving the diagnosis task in the context of adaptive design and redesign. This approach uses functional models that explicitly represent the device functions and use them to organize teleological and causal knowledge about the device. In particular, we describe a specific kind of functional model called structure—behavior—function (SBF) models in which the causal behaviors of the device are specified in terms of flow of substances through components. We illustrate the use of SBF models with three examples from Kritik2, a knowledge system that designs new devices by retrieving, diagnosing, and adapting old device designs.

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