Improving Students' Functional Modeling Skills: A Modeling Approach and a Scoring Rubric

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
Robert L. Nagel ◽  
Matt R. Bohm ◽  
Julie S. Linsey ◽  
Marie K. Riggs
Keyword(s):  
Engineering Design ◽  
Functional Model ◽  
Concept Generation ◽  
Functional Modeling ◽  
Generate Functional ◽  
Algorithmic Approach ◽  
Functional Models ◽  
Grammar Rules ◽  
Students First ◽  
Scoring Rubric

An engineering design curriculum that introduces functional modeling methods is believed to enhance the ability to abstract complex systems, assist during the concept generation phase of design, and reduce design fixation. To that end, a variety of techniques for considering function during design have been proposed in the literature, yet there are a lack of validated approaches for teaching students to generate functional models and no reliable method for the assessment of functional models. This paper presents a study investigating students' ability to generate functional models during a homework assignment; the study includes three different treatment conditions: (1) students who receive only a lecture on functional modeling, (2) students who receive a lecture on functional modeling as well as a step-by-step example, and (3) students who receive a lecture, a step-by-step example, and an algorithmic approach with grammar rules. The experiment was conducted in a cornerstone, undergraduate engineering design course, and consequently, was the students' first exposure to functional modeling. To assess student generated functional models across all three conditions, an 18 question functional model scoring rubric was developed based on flow-based functional modeling standards. Use of the rubric to assess the student generated functional models resulted in high inter-rater agreement for total score. Results show that students receiving the step-by-step example perform as well as students receiving the step-by-step example and an algorithmic approach with grammar rules; both groups perform better than the lecture-only group.

An Investigation Into the Effectiveness of an Algorithmic Approach to Teaching Functional Modeling

2013 ◽  
Author(s):  
Robert L. Nagel ◽  
Matt R. Bohm ◽  
Julie S. Linsey
Keyword(s):  
Engineering Design ◽  
Positive Impact ◽  
Functional Model ◽  
Preliminary Evidence ◽  
Algorithmic Approach ◽  
Functional Models ◽  
Grammar Rules ◽  
Approach To Teaching ◽  
Teaching Function

The consideration of function is prevalent across numerous domains as a technique allowing complex problems to be abstracted into a form more readily solvable. In engineering design, functional models tend to be of a more generalized nature describing what a system should do based on customer needs, target specifications, objectives, and constraints. While the value of function in engineering design seems to be generally recognized, it remains a difficult concept to teach to engineering design students. In this paper, a study on the effectiveness of an algorithmic approach for teaching function and functional model generation is presented. This paper is a follow-up on to the 2012 ASME IDETC paper, An Algorithmic Approach to Teaching Functionality. This algorithmic approach uses a series of grammar rules to assemble function chains which then can be aggregated into a complete functional model. In this paper, the results of a study using the algorithmic approach at Texas A&M in a graduate level design course are presented. The analysis of the results is discussed, and the preliminary evidence shows promise toward supporting our hypothesis that the algorithmic approach has a positive impact on student learning.

An Algorithmic Approach to Teaching Functionality

2012 ◽  
Author(s):  
Robert L. Nagel ◽  
Matt R. Bohm ◽  
Josh Cole ◽  
Phillip Shepard
Keyword(s):  
Engineering Design ◽  
Functional Model ◽  
Black Box ◽  
Integrated System ◽  
Box Model ◽  
System Level ◽  
Algorithmic Approach ◽  
Functional Models ◽  
Grammar Rules ◽  
Approach To Teaching

The consideration of function is prevalent across numerous domains as a technique allowing complex problems to be abstracted into a form more readily solvable. In engineering design, functional models tend to be of a more generalized nature, and consequently, engineering design derived functional representations do not aim to replace domain specific models but to encapsulate those models at a higher and more integrated system level. While the value of function in engineering design seems to be generally recognized, it remains a difficult concept to teach to students of engineering design. In this paper, an algorithmic approach to teaching function and functional model generation is presented. The approach uses a series of grammar rules to assemble function chains from a list of enumerated functions desired of the final product. Function chains can then be aggregated into a complete functional model. The approach has been trialed with senior capstone design students taught about functionality as well as how to generate a black box model and how to enumerate functions. Student-generated functional models are compared to expert generated functional models in the paper. Preliminary results indicate that a student with limited functional modeling experience could follow the prescribed algorithm to generate an aggregated functional model based solely on a black box model.

Functional Modeling Experimental Studies

2001 ◽  
Author(s):  
Mark A. Kurfman ◽  
Robert B. Stone ◽  
Jagan R. Rajan ◽  
Kristin L. Wood
Keyword(s):  
Engineering Design ◽  
Functional Model ◽  
Experimental Studies ◽  
Design Engineering ◽  
Functional Modeling ◽  
Skill Levels ◽  
Functional Models ◽  
New Methodologies ◽  
Model Derivation ◽  
Derivation Method

Abstract As more design methodologies are researched and developed, the question arises as to whether these new methodologies are actually advancing the field of engineering design or instead cluttering the field with more theories. There is a critical need to test new methodologies for their contribution to the field of design engineering. This paper presents the results of research attempts to substantiate repeatability claims of the functional model derivation method. Three experiments are constructed and carried out with a participant pool that possesses a range of engineering design skill levels. The experiments test the utility of the functional model derivation method to produce repeatable functional models for a given product among different designers. Results indicate the method is largely successful and identify its key strengths as well as opportunities for improvement.

Some Ontological Distinctions of Function Based on the Role Concept

2009 ◽  
Author(s):  
Yoshinobu Kitamura ◽  
Riichiro Mizoguchi
Keyword(s):  
Life Cycle ◽  
Engineering Design ◽  
Product Life Cycle ◽  
Functional Modeling ◽  
Ontological Engineering ◽  
Product Life ◽  
Functional Models ◽  
Role Concept ◽  
Essential Function ◽  
The Relationship

Function is an important aspect of artifacts in engineering design. Although many definitions of function have been proposed in the extensive research mainly in engineering design and philosophy, the relationship among them remains unclear. Aiming at a contribution to this problem, this paper investigates some ontological issues based on the role concept in ontological engineering. We discuss some ontological distinctions of function such as essentiality and actuality and then propose some fundamental kinds of function such as essential function and capacity function. Based on them, we categorize some existing definitions in the literature and clarify the relationship among them. Then, a model of function in a product life-cycle is proposed. It represents the changes of existence of the individuals of each kind of function, which are caused by designing, manufacturing and use. That model enables us to give answers to some ontological questions such as when and where a function exists and what a function depends on. The consideration on these issues provides engineers with some differentiated viewpoints for capturing functions and thus contributes to consistent functional modeling from a specific viewpoint. The clarified relationships among the kinds of function including the existing definitions in the literature will contribute to interoperability among functional models based on the different kinds and/or definitions.

Experimental Studies Assessing the Repeatability of a Functional Modeling Derivation Method

2003 ◽  
Vol 125 (4) ◽  
pp. 682-693 ◽  
Author(s):  
Mark A. Kurfman ◽  
Michael E. Stock ◽  
Robert B. Stone ◽  
Jagan Rajan ◽  
Kristin L. Wood
Keyword(s):  
Design Research ◽  
Functional Model ◽  
Experimental Studies ◽  
Testing Procedure ◽  
Research Literature ◽  
Functional Modeling ◽  
Skill Levels ◽  
Functional Models ◽  
Model Derivation ◽  
Derivation Method

This paper presents the results of research attempts to substantiate repeatability and uniqueness claims of a functional model derivation method following a hypothesis generation and testing procedure outlined in design research literature. Three experiments are constructed and carried out with a participant pool that possesses a range of engineering design skill levels. The experiments test the utility of a functional model derivation method to produce repeatable functional models for a given product among different designers. In addition to this, uniqueness of the functional models produced by the participants is examined. Results indicate the method enhances repeatability and leads designers toward a unique functional model of a product. Shortcomings of the method and opportunities for improvement are also identified.

Mining Functional Model Graphs to Find Product Design Heuristics With Inclusive Design Illustration

2013 ◽  
Vol 13 (4) ◽  
Author(s):  
Shraddha Sangelkar ◽  
Daniel A. McAdams
Keyword(s):  
Data Mining ◽  
Functional Model ◽  
Inclusive Design ◽  
Generation Process ◽  
Graph Visualization ◽  
Concept Generation ◽  
Product Representation ◽  
Graph Data ◽  
Design Heuristics ◽  
Functional Models

Engineering design heuristics offer the potential to improve the design process and resultant designs. Currently, heuristics are empirically derived by experts. The goal of this paper is to automate the heuristics generation process. Functional modeling, a well-established product representation framework, is applied in this research to abstract the intended functionality of a product. Statistically significant heuristics, extracted from a database of functional models, serve as design suggestions or guidelines for concept generation. The heuristics can further be applied to automate portions of the concept generation process. Prior research efforts in automated concept generation rely heavily on the design repository. The repository needs to be appended for broader categories of design problems, and, at the same time, a tool for quick analysis of the expanded repository is required. An automated heuristic extraction process has the capability to efficiently mine the updated repositories and find new heuristics for design practice. A key objective of this research is to develop design heuristics applicable in the diverse and challenging domain of inclusive design. The research applies graph theory for mathematical representation of the functional model, graph visualization for comprehending graphs, and graph data mining to extract heuristics. The results show that the graphical representation of functional models along with graph visualization allows quick updates to the design repository. In addition, we show that graph data mining has the capability to efficiently search for new design heuristics from the updated repository.

An Engineering-to-Biology Thesaurus for Engineering Design

2010 ◽  
Author(s):  
Jacquelyn K. S. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Idea Generation ◽  
Natural World ◽  
Biological Information ◽  
Concept Generation ◽  
Functional Modeling ◽  
University Of Toronto ◽  
Engineering Designs ◽  
Design Activities

Engineering design is considered a creative field that involves many activities with the end goal of a new product that fulfills a purpose. Utilization of systematic methods or tools that aid in the design process is recognized as standard practice in industry and academia. The tools are used for a number of design activities (i.e., idea generation, concept generation, inspiration searches, functional modeling) and can span across engineering disciplines, the sciences (i.e., biology, chemistry) or a non-engineering domain (i.e., medicine), with an overall focus of encouraging creative engineering designs. Engineers, however, have struggled with utilizing the vast amount of biological information available from the natural world around them. Often it is because there is a knowledge gap or terminology is difficult, and the time needed to learn and understand the biology is not feasible. This paper presents an engineering-to-biology thesaurus, which we propose affords engineers, with limited biological background, a tool for leveraging nature’s ingenuity during many steps of the design process. Additionally, the tool could also increase the probability of designing biologically-inspired engineering solutions. Biological terms in the thesaurus are correlated to the engineering domain through pairing with a synonymous function or flow term of the Functional Basis lexicon, which supports functional modeling and abstract representation of any functioning system. The second version of the thesaurus presented in this paper represents an integration of three independent research efforts, which include research from Oregon State University, the University of Toronto, and the Indian Institute of Science, and their industrial partners. The overall approach for term integration and the final results are presented. Applications to the areas of design inspiration, comprehension of biological information, functional modeling, creative design and concept generation are discussed. An example of comprehension and functional modeling are presented.

Knowledge Retention and Scoring Metrics for Functional Modeling in an Engineering Design Context

2016 ◽  
Author(s):  
Marie Riggs ◽  
Philip Mountain ◽  
Robert L. Nagel ◽  
Matt R. Bohm ◽  
Julie S. Linsey
Keyword(s):  
Engineering Design ◽  
Engineering Students ◽  
Knowledge Retention ◽  
Functional Modeling ◽  
Design Synthesis ◽  
Functional Models ◽  
Data Points ◽  
Design Skills ◽  
Teaching Function ◽  
The Impact

Functional modeling as a design methodology is often covered in engineering design texts as a tool for transforming “customer speak” into “engineering speak.” There is little to no empirical data, though, that clearly demonstrates that learning functional modeling actually improves students’ engineering design skills. The overall objective of this project is to determine the impact of teaching function on engineering students’ design synthesis abilities. This paper focuses on preliminary data collected as a part of the longitudinal study. Students were asked to generate functional models of functionally similar systems at two points during an engineering design course: (1) once as a homework assignment immediately following the introduction of the topic and (2) again as a low stakes in-class activity seven weeks later. This paper will present the comparison of models created at both data points. Student models at each time point are analyzed using a validated 18-question rubric. The results provide promise that, in general, students retain their modeling ability, but there are noted characteristic differences between homework-generated functional models and those generated later in the semester during an in-class activity. These characteristics will be discussed as will potential improvements to the scoring rubric.

A state–behavior–function model for functional modeling of multi-state systems

2018 ◽  
Vol 233 (7) ◽  
pp. 2302-2317 ◽  
Author(s):  
Meng Zhao ◽  
Yong Chen ◽  
Linfeng Chen ◽  
Youbai Xie
Keyword(s):  
Functional Analysis ◽  
Engineering Design ◽  
Conceptual Design ◽  
Functional Modeling ◽  
Function Model ◽  
State Behavior ◽  
Proposed Model ◽  
Functional Models ◽  
Behavior Function ◽  
Prototype Software

Since functional modeling can be very useful in conceptual design, it has received considerable attention from engineering design community. However, existing functional models still cannot effectively assist designers in analyzing the functionalities of multi-state systems during conceptual design. As a result, designers often have to manually carry out functionality analysis according to their experiences, which are not only tedious, but also error-prone. Therefore, this paper proposes a state–behavior–function model for functional modeling of multi-state systems, which can provide designers with automated functional analysis support. The approach involves not only a state–behavior–function model for representing components, but also a model for representing the functionalities of multi-state systems. A prototype software is then developed for demonstrating the proposed model, with the functional modeling of a peeler centrifuge as an example to illustrate the proposed functional modeling approach.

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.

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