bluuebunny/crossref_metadata_2025 huggingface dataset:
Management of Modeling and Formulation in Reflective Design Process of Multidisciplinary System
Authors: Nomaguchi Yutaka , Mochizuki Ryota , Fujita Kikuo
Published: December 2016

Design optimization of a complicated system requires modeling multidisciplinary engineering analysis for the verification of its physical behavior, and sophisticated formalization of the optimization problem. Although a CAE system and a package software of optimization can support the calculation and visualization of the results, it is important to make the appropriate models and the appropriate formalization considering critical phenomena, modeling conditions, the level of details and so on. These processes remain with the realm of tacit knowledge of engineers. This paper proposes a new management method that facilitates a designer to clarify the empirical knowledge of modeling and formulation in the reflective design process of multidisciplinary system, and flexibly operate them during design process. A knowledge representation format based on a function modeling method of IDEFO is developed in order to represent and operate the whole/part relationships and the causal relationships among design parameters, and the contents of the optimization formulation. The ability of the proposed method is verified with a design example of a desiccant air-conditioning system.
Investigation of Power Transmission Mechanism Under Three-Axis Driving Planetary Gear Train Based on the Mechanism
Authors: Nakagawa Masao , Nishida Dai , Hirogaki Toshiki , Aoyama Eiichi
Published: December 2016

Planetary gear trains are presently widely used in various machines owing to their many advantages. They, however, suffer from problems of noise and vibration due to their structural complexity. Moreover, their dynamic characteristics are yet to be fully understood. Although several studies have been conducted on two-axis driving and displacement of planet gear, none has considered three-axis driving. In the present study, the general driving conditions of a planetary gear train, including during three-axis driving, were investigated based on the theory of instant center. Ideal driving condition is proposed based on the experimental result on three-axis driving which was tested on an original fully wireless test stand.
A Framework for Building Behavioral Models of Technical and Economic Systems
Authors: Ritola Tuomas , Coatanéa Eric , Micaëlli Jean-Pierre , Mokhtarian Hossein
Published: December 2016

Efforts towards a circular economy, increased possibilities of sensor technology and monitoring, and the developments in smart, connected products and systems have all contributed to the shift from selling products towards selling service-based offerings. Product-service systems are one example of service-based offerings, combining physical products or systems to service-based earnings logic.

Many traditional companies might benefit from exploring the possibilities of service-based offerings, but the tools for modeling, simulating and analyzing service-based offerings are somewhat lacking. There are numerous existing methods for modeling products on one hand, or business and economic models on the other, but fewer combining the two. This article presents a modeling framework for describing, analyzing and simulating offerings consisting of interdependent technical systems and business processes, based on a an extension of previous work on the Dimensional Analysis Conceptual Modeling (DACM) framework.

The goal of the framework is to allow modeling combinations of technical systems and business processes, resulting in flows of revenue between the stakeholders over a period of time. Further, the framework can be used to identify objectives of the stakeholders, and identify contradictions on a variable level, or conflicting objectives on a system level, and to propose solutions for solving the conflicts and contradictions based on general solution principles. In the article, the framework is applied on a case study of designing a reverse vending machine.
A Platform Model for Suppliers of Customized Systems: Creating an Ability to Master Fluctuating Requirements
Authors: André Samuel , Stolt Roland , Elgh Fredrik
Published: December 2016

Companies developing highly customized products within the supplier industry are continuously faced with fluctuating requirements during both the quotation process and continued development. This research proposes a platform approach to aid suppliers when modularity or platform scalability do not suffice. The platform approach, Design Platform, focuses on descriptions that not only contain information about tangible components and systems but also information, knowledge and methods supporting the actual design of the product. A support system called Design Platform Manager has been developed to aid in using the platform approach and is introduced at a supplier active in the automotive industry. The system enables creation of generic product items that can be structured and instantiated to become product variants as well as Design Elements that are blocks of knowledge that describe a design or supports the activity of designing. A first evaluation is made that overall shows good result according to the company representatives.
An Innovative Tool to Monitor and Represent Energy Value Stream of a Production System
Authors: Gregori Fabio , Luzi Andrea , Papetti Alessandra , Germani Michele , Camorani Fabio
Published: December 2016

Nowadays, the energy factor is growing in importance because it really affects the production costs of factories. Not least, energy regulation and rules are stricter as time goes by. Tools for energy monitoring are needed.

The objective of this work is to propose a tool aimed to assess the energy value flowing in a production system, according to the Energy Value Stream Mapping method (EVSM). The final goal is to increase the sustainability of the processes through identification of energy wastes, aiming at eliminating them. The tool is a lean graphic instrument; it permits to represent explicitly the energy flows along the process with respect to the concept of value creation.

The tool permits to clearly identify and quantify different types of energy flows concerning different carriers, even in a complex production plant where multiple energy carriers act at the same time. Finally, it will be shown the testing of the tool in a household appliances production system.
Design of Injection Nozzle in Direct Metal Deposition (DMD) Manufacturing of Thin-Walled Structures Based on 3D Models
Authors: Yan Jingyuan , Battiato Ilenia , Fadel Georges
Published: December 2016

The Direct Metal Deposition (DMD) process is one of the most important metal based additive manufacturing techniques available today. In this study, a print head design optimization methodology is proposed based on the finite element modeling of powder distribution and substrate temperature distribution. The design methodology is applied to the deposition of Ti-6Al-4V powder in building thin-walled (≈ 0.7 mm) structures, which is also applicable to solid parts. The design objective is to find the optimal design of the injection nozzle shape that can maximize the powder usage and minimize laser energy needs, later defined as powder and laser energy efficiencies. A neural network is built to investigate the nozzle shape parameters based on the results from the 3D powder flow model. With the methodology proposed in this study, the optimal injection nozzle design can be found.
Product Line Design Search Considering Reliability and Robustness Under Uncertainty in Discrete Choice Methods
Authors: Shin Jaekwan , Ferguson Scott
Published: December 2016

Point-estimates of part-worth values in customer preference models have been used in market-based product design under the simplying assumption that customer preferences can be treated as deterministic. However, customer preferences are not only inherently stochastic, but are also statistical estimates that exhibit random errors in model formulation and estimation. Ignoring uncertainty in customer preferences and variability in estimates has caused concern about the reliability and robustness of an optimal product design solution. This study quantitatively defines reliability and robustness of a product design under uncertainty when using discrete choice methods. These metrics are then integrated into a multi-objective optimization problem to search for product line solutions considering reliability and robustness under uncertainty when using discrete choice methods.
Multibody Modeling of Sloshing in Spacecraft Ascent and Landing Maneuvers
Authors: Lunghi Paolo , Masarati Pierangelo , Lavagna Michéle
Published: December 2016

Sloshing of liquids in tanks has been always a problem in the design of space vehicles. This is especially true in launch and powered landing systems, in which a significant fraction of the mass is made up of propellant. In such systems, uncontrolled or unexpected violent sloshing phenomena can even lead to the loss of the spacecraft. A typical method to cope with sloshing is to ensure that the attitude control system operates at frequencies much higher than those of the sloshing motion of the fuel. In this case, the project of the controller is realized assuming the liquid as static [1].
Design and 3D Printing of Hierarchical Tissue Engineering Scaffolds Based on Mechanics and Biology Perspectives
Authors: Egan Paul , Ferguson Stephen J. , Shea Kristina
Published: December 2016

Continued scientific research is crucial for developing new biomedical products, such as tissue engineering scaffolds, that are difficult to optimize due to the complexity of interfacing mechanical and biological systems. In this paper, mechanical and biological perspectives are used to propose and implement an approach for designing hierarchical scaffolds that provide structural support in the body as tissue regenerates. Three sequential steps are proposed for defining design needs, generating design alternatives, and fabricating design prototypes. Design needs are determined by considering mechanical and biological performance requirements, experimental procedures, and fabrication constraints. The primary mechanical requirement is a scaffold’s need to maintain structural integrity, while biologically the scaffold should promote cellular growth. Scaffold design alternatives of four topology types are generated by altering design parameters that describe a scaffold’s structure. Trade-offs are revealed for scaffold porosity and surface area properties that are known to influence mechanical and biological scaffold performance. Scaffolds of each topology type are designed with 80% porosity and fabricated, which enables their potential use in scientific experiments to measure how property trade-offs influence scaffold performance. On the basis of currently available knowledge, a to-scale spinal scaffold implant is designed and fabricated with a graphically maximized surface area to porosity ratio for a hierarchical scaffold, which represents a potentially high performing design from both mechanical and biological perspectives. These results demonstrate the importance of multidisciplinary approaches for designing complex biomedical tissue scaffolds that could significantly improve healthcare through the development of new clinical products.
Design of a Virtual Reality Haptic Robotic Central Venous Catheterization Training Simulator
Authors: Pepley David , Yovanoff Mary , Mirkin Katelin , Han David , Miller Scarlett , Moore Jason
Published: December 2016

Central venous catheterization (CVC) is a medical procedure where a surgeon attempts to place a catheter in the jugular, subclavian, or femoral vein. While useful, this procedure places patients at risk of a wide variety of adverse effects. Traditionally, training is performed on CVC mannequins, but these mannequins cannot vary patient anatomy. This work describes the development of a mobile training platform utilizing a haptic robotic arm and electromagnetic tracker to simulate a CVC needle insertion. A haptic robotic arm with custom syringe attachment used force feedback to provide the feeling of a needle insertion. A virtual ultrasound environment was created and made navigable by a mock ultrasound probe containing a magnetic tracking device. The effectiveness of the system as a training tool was tested on 12 medical students without CVC experience. An average increase in successful first insertion of 4.2% per practice scenario was seen in students who trained exclusively on the robotic training device. The robotic training device was able to successfully vary the difficulty of the virtual patient scenarios which in turn affected the success rates of the medical students. These results show that this system has the potential to successfully train medical residents for future CVC insertions.
Combining Strings and Fibers With Additive Manufacturing Designs
Authors: Kimmer C. J. , Harnett C. K.
Published: December 2016

High tensile strength cables, low-resistance motor windings, and shape memory actuators are common examples of technical fibers used in robots and other electromechanical assemblies. Because properties like tensile strength, crystal structure, and polymer alignment depend strongly on processing history, these materials cannot be 3D printed with the same properties they have on the spool. Strings and fibers are inserted in mechanical parts at the end of the manufacturing process for these assemblies. When the fibers take complex paths, the installation is often done by hand. This activity can dominate the process time, increase its human labor and reduce its social sustainability [1].

This paper applies the non-traditional approach of machine embroidery to insert sheets of patterned fibers in layered additive manufacturing processes such as 3D printing and lamination. Fibers are aligned with features in laser-cut or printed parts without the manual labor of hand threading. We demonstrate that water-soluble stabilizer materials originally designed for textiles can hold hard mechanical parts in a machine embroidery hoop with enough strength and rigidity to withstand sewing through pre-existing holes in the part. Alignment to within 250 microns has been demonstrated with a sub-$300 consumer embroidery machine.

Case studies in this paper include a cable-driven mechanism, a soft-to-hard electronic connection, and an electromechanical sensor. Process-compatible and commercially available materials that can be embroidered include conductive threads, shrinking threads, water-soluble threads and high tensile strength fibers.

The biggest hurdle for a user interested in this automated fiber installation process is linking the existing design file with an embroidery machine file. There is a much larger user base for 2D and 3D computer-assisted design (CAD) software than for expensive and proprietary embroidery digitizing software. We take the route chosen by the laser cutter industry, where the user produces a CAD file in their preferred editor, and makes annotations that communicate where and how densely to stitch. Translation software scans the file for a particular line style and generates stitch coordinates along it. Development is done in Jupyter/iPython notebooks that allow end-users to inspect, understand, and modify the conversion code. The intent is for users of existing planar fabrication technology (whether laser, printed circuit board, or micro/nano) to apply this method to their own CAD files for a versatile and straightforward way to put advanced materials in their devices without adding manual labor. This general approach can solve a class of assembly problems relevant to underactuated tendon-driven robotics and other electromechanical systems, expanding the range of devices that can be put together using automation.
Additive Manufacturing of Conductive Polymer Nanocomposites Under the Influence of External Magnetic Field
Authors: Koyalamudi Kiran Babu , Yang Ruoyu , Rai Rahul
Published: December 2016

Conductive polymer nanocomposites (CPNCs) have gained a lot of attention by the researchers, in recent times, due to their diverse technological applications in different domains. This paper discusses the additive manufacturing of conductive polymer nanocomposite. Maghemite-Multiwalled carbon nanotubes were synthesized, and later dispersed in an acrylate resin, followed by curing with UV DLP 3D printer, under the presence of external magnetic field. Maghemite-Multiwalled carbon nanotubes showed superior magnetic properties, when compared to Multiwalled carbon nanotubes and lead to improvements in preferential alignment of filler material in the polymer matrix. The initial experimental results show preferential alignment of Maghemite-Multiwalled carbon nanotubes in the polymer matrix under the influence of external uniform magnetic field, at an intensity of 120 Gauss.
User Extreme Conditions to Enhance Designer Empathy and Creativity: Applications Using Visual Impairment
Authors: Raviselvam Sujithra , Hölttä-Otto Katja , Wood Kristin L.
Published: December 2016

Designers often design for people unlike themselves. Many design tools and methods have been developed to support the designers in this task. One area is empathic design, where, simulated scenarios allow the designers to experience a situation that is less likely to be accessed otherwise. These simulated scenarios are widely used and past studies have shown these methods enhance designer creativity or evoke designer empathy. In this paper we investigate to what extent these simulated scenarios help increase designer empathy and creativity and how it compares to only being briefed about the target population. In this study 36 subjects took part in a workshop that included a briefing about the life of people with visual impairments as well as a simulation of such scenarios. Participants’ levels of creativity and empathy were assessed at three different stages during the workshop: (i) Pre-workshop, (ii) Post-briefing and (iii) Post-simulation. The results show that, the participants’ creativity in terms of novelty, quantity and breadth of the ideas was significantly high after the simulation when compared to only being briefed about the situation. There were no differences in the idea feasibility. All ideas were technically feasible. Also participant empathy increased significantly from before the workshop to post-simulation. A further comparison of the workshop reflections from both participants and volunteers with visual impairments were used to understand the extent to which the participants were able to empathize with people with visual impairments. We find the simulated scenario improved the participants’ ability to understand the simulated population compared to the before workshop state, but nevertheless, the participants were unable to match the level of detail given by the people with actual visual impairments.
Design of an Origami Fold Pattern for Shape-Morphing Using Triangles
Authors: Katz Andrew J. , Lusk Craig P.
Published: December 2016

This project was intended to serve two purposes, the first was to design an origami fold pattern which would be able to fold in a way that mimics an existing shape-morphing mechanism’s kinematics. The second purpose was to demonstrate a general method for using origami to morph one triangle into another triangle. Our method was to design the footprint (the outer edges) based on comparing the dimensions in the two triangles. Fold lines were then added to the footprint that were necessary to morph the larger dimensions into the smaller ones. Finally, fold lines were added to the interior of the design to satisfy the rules of origami i.e. to permit the morphing motion to happen. The result is an origami fold pattern that can fold to each of the required triangles.
Isogeometric Shape Optimization on Triangulations
Authors: Wang Cunfu , Xia Songtao , Wang Xilu , Qian Xiaoping
Published: December 2016

The paper presents an isogeometric shape optimization method that is based on Bézier triangles. Bézier triangles are used to represent both the geometry and physical fields. For a given physical domain defined by B-spline boundary, triangular Bézier parameterization can be automatically generated. This shape optimization method is thus applicable to structures of complex topology. Due to the use of B-spline parameterization of the boundary, the optimized shape can be compactly represented with a relatively small number of optimization variables. In order to ensure mesh validity during shape optimization, we adopt a bi-level mesh representation, where the coarse mesh is used to maintain mesh quality through positivity of Jacobian ordinates of the Bézier triangles. The fine mesh is used in isogeometric analysis for numerical accuracy. Numerical examples are presented to demonstrate the efficacy of the proposed method.
A Geometric Singular Characterization of the 6/6 Stewart Platform
Authors: Slavutin Michael , Sheffer Avshalom , Shai Offer
Published: December 2016

The paper introduces the 3D Kennedy theorem and applies it for characterizing of the singular configuration of 6/6 Stewart Platform (SP). The main idea underlying the proposed singular characterization is as follows: we search for two lines, which cross four of the six leg lines of the robot. For these two lines we find two parallel lines that cross the remaining leg lines 5 and 6. Each pair of parallel lines defines a plane. Let m be the intersection line of these two planes. The proposed singular characterization is: the 6/6 SP is in a singular configuration if and only if the line m is perpendicular to the common normal of leg lines 5 and 6.

In addition, the method developed for the singular characterization is also used for the analysis of the mobility of SP. Finally, the proposed method is compared to other singularity analysis methods, such as of Hunt’s and Fichter’s singular configuration and the 3/6 Stewart Platform singularity.

The relation between the reported characterizations of the 6/6 SP and other reported works is highlighted. Moreover, it is shown that the known 3/6 singular characterization is a special case of the work reported in the paper.
Kinematic Analysis of Hexapod Manipulation
Authors: Yang Fan , Ding Xilun , Chirikjian Gregory S.
Published: December 2016

This paper provides a method for modeling the center of mass (COM) of hexapod manipulation systems, which is based on the Statically Equivalent Serial Chain (SESC) model. First, the product of exponentials (POE) formula is used to construct the SESC model for the simple tree-like chain. Then, in order to apply this method to real scenarios, the situation when the robot stands on uneven terrain is studied. In addition, the static grasp constraints for the manipulation and the Jacobian matrix for the COM of the system are analyzed. Moreover, we present a modified tumble stability margin, which considers all of the possible ways that the robot can tumble. Finally, based on these kinematic analyses, a motion control scheme for statically stable manipulation is proposed. The results are validated with simulations.
Embedded Sensors and Feedback Loops for Iterative Improvement in Design Synthesis for Additive Manufacturing
Authors: Nourbakhsh Mehdi , Morris Nigel , Bergin Michael , Iorio Francesco , Grandi Daniele
Published: December 2016

Design problems are complex and not well-defined in the early stages of projects. To gain an insight into these problems, designers envision a space of various alternative solutions and explore various performance trade-offs, often manually. To assist designers with rapidly generating and exploring a design space, researchers introduced the concept of design synthesis methods. These methods promote innovative thinking and provide solutions that can augment a designer’s abilities to solve problems. Recent advances in technology push the boundaries of design synthesis methods in various ways: a vast number of novel solutions can be generated using high-performance computing in a timely manner, complex geometries can be fabricated using additive manufacturing, and integrated sensors can provide feedback for the next design generation using the Internet of things (IoT). Therefore, new synthesis methods should be able to provide designs that improve over time based on the feedback they receive from the use of the products. To this end, the objective of this study is to demonstrate a design synthesis approach that, based on high-level design requirements gathered from sensor data, generates numerous alternative solutions targeted for additive manufacturing. To demonstrate this method, we present a case study of design iteration on a car chassis. First, we installed various sensors on the chassis and measured forces applied during various maneuvers. Second, we used these data to define a high-level engineering problem as a collection of design requirements and constraints. Third, using an ensemble of topology and beam-based optimization techniques, we created a number of novel solutions. Finally, we selected one of the design solutions and because of some manufacturability constraints we, 3D-printed a prototype for the next generation of design at one third scale. The results show that designs generated from the proposed method were up to 28% lighter than the existing design. This paper also presents various lessons learned to help engineers and designers with a better understanding of challenges applying new technologies in this research.
Flaws Lurking in Engineering Design-Decision Making: The Attribute Set Dissociation Problem
Authors: Pandey Vijitashwa
Published: December 2016

The applicability of theoretical decision analysis, while rationally sound, has eluded mainstream engineering design. A reason commonly overlooked is that basic concepts in decision analysis do not scale naturally to multiple attributes — which are encountered in, by far, most design problems. In this paper, we document a paradox when dealing with transactions involving multiple attributes. We show the possibility of a money pump where if we dissociate part of an attribute from a design, the rest of the design can be manipulated to get either a better design or create wealth out of nothing. To reconcile with paradox, it is argued that there is a fundamental problem dealing with multiple attributes where a frame of reference chosen (purposefully) ignores external inputs, assuming that design decisions happen in the vacuum of the frame chosen. For example, in a simple design valuation decision, the money amount committed does not necessarily come from a fixed range of negotiability (upper and lower limits) but is subject to change if significant changes in other attributes are possible. The root cause of this issue is that fungible attributes such as money can form a part of the attribute set or be trivially dissociated from it, if needed. We argue that this is rational behavior on a decision maker’s part. However, most utility formulations do not model it and lead to the paradox. We call this the attribute dissociation problem. A specific definition is provided as well as implications on design as well as preference elicitation methods are considered. Finally, formulations are presented that avoid this problem and recommendations are provided.
Cyber-Empathic Design: A Data Driven Framework for Product Design
Authors: Ghosh Dipanjan D. , Kim Junghan , Olewnik Andrew , Lakshmanan Arun , Lewis Kemper E.
Published: December 2016

One of the critical tasks in product design is to map information from the consumer space to the design space. Currently, this process is largely dependent on the designer to identify and map how psychological and consumer level factors relate to engineered product attributes. In this way current methodologies lack provision to test a designer’s cognitive reasoning and could therefore introduce bias while mapping from consumer to design space. Also, current dominant frameworks do not include user-product interaction data in design decision making and neither do they assist designers in understanding why a consumer has a particular perception about a product. This paper proposes a new framework — Cyber-Empathic Design — where user-product interaction data is acquired via embedded sensors in the products. To understand the motivations behind consumer perceptions, a network of latent constructs is used which forms a causal model framework. Structural Equation Modeling is used as the parameter estimation and hypothesis testing technique making the framework falsifiable in nature. To demonstrate the framework and demonstrate its effectiveness a case study of sensor integrated shoes is presented in this work, where two models are compared — one survey based and using the Cyber-Empathic framework model. It is shown that the Cyber-Empathic framework results in improved fit. The case study also demonstrates the technique to test a designers’ cognitive hypothesis.
Development of a Village-Scale, Solar-Powered Reverse Osmosis System
Authors: Bian David W. , Sokol Julia A. , Yun Janet H. , Mascarenhas Craig A. , Emeghara Chinasa , Watson Sterling M. , Buresh Christopher , Vander Werff Annie , Wright Natasha C. , Winter Amos G.
Published: December 2016

This paper details the development of a photovoltaic reverse osmosis water desalination system for a groundwater well in Bercy, Haiti. The well was constructed to provide potable drinking and agricultural water for the 300-person community. However, its water has a salinity level of 5,290 ppm, rendering it harmful for both human consumption and soil fertility. This reverse osmosis system is designed to be low-cost and operational off-grid while providing 900 gallons per day of desalinated water for the community. The system is composed of a photovoltaic power system, a submersible solar pump, and three reverse osmosis membranes. The system is designed to have a material cost significantly below that of any commercially-available system of similar scale. Furthermore, it has an average water production cost of $1.21/m3 and an average specific energy of 1.2 kWh/m3. Its performance was tested in the laboratory by connecting the desalination module to a DC power supply, demonstrating good agreement with its modeled performance. The installation of the full system with the PV module will take place on-site in the summer of 2016. Following implementation, the system will be monitored and compared against predicted performance. The first attempt is meant to serve as a verification and validation of the system as a whole. However, successful operation within the given cost target could pave the way for wider use of off-grid reverse osmosis systems at many remote locations with limited freshwater access around the world.
Significance, Prevalence and Implications for Bio-Inspired Design Courses in the Undergraduate Engineering Curriculum
Authors: Nagel Jacquelyn K. S. , Pidaparti Ramana M.
Published: December 2016

Engineers in the 21st century can no longer isolate themselves and must be prepared to work across disciplinary, cultural, political, and economic boundaries to meet challenges facing the US and the world. Recently, a greater emphasis is being placed on understanding social, economic and environmental impacts of engineered solutions. Undergraduate education must train students to not only solve engineering challenges that transcend disciplinary boundaries, but also communicate, transfer knowledge, and collaborate across technical and non-technical boundaries. One approach to achieving this goal is through introducing bio-inspired design in the engineering curriculum. Bio-inspired design encourages learning from nature to generate innovative designs for man-made technical challenges that are more economic, efficient and sustainable than ones conceived entirely from first principles. This paper reviews the literature pertaining to current approaches to teaching bio-inspired design in and engineering curriculum curriculum at different institutions as well as the essential competencies of the 21st century engineering. At James Madison University a Concept-Knowledge Theory instructional approach was adopted for teaching sophomore engineering design students bio-inspired design to foster many of the 21st century competencies. A pilot study was conducted to demonstrate that the 21st century competencies can be targeted and achieved. The results of study are presented, and the significance and implications of teaching bio-inspired design in an engineering curriculum are discussed.
Evaluating the Use of Artificial Neural Networks, Graph Theory, and Complexity Theory to Predict Automotive Assembly Defects
Authors: Patel Apurva , Andrews Patrick , Summers Joshua D.
Published: December 2016

Artificial Neural Networks (ANNs) have been used to predict assembly time and market value from assembly models. This was done by converting the assembly models into bipartite graphs and extracting 29 graph complexity metrics which were used to train the ANN prediction models. This paper presents the use of sub-assembly models instead of the entire assembly model to predict assembly quality defects at an automotive OEM. The size of the training set, order of the bipartite graph, selection of training set, and defect type were experimentally studied. With a training size of 28 parts, an interpolation focused training set selection, and second order graph seeding, over 70% of the predictions were within 100% of the target value. The study shows that with an increase in training size and careful selection of training sets, assembly defects can be predicted reliably from sub-assemblies complexity data.
The Effect of an Added Mass on the Frequency Shifts of a Clamped-Clamped Microbeam for Bio-Mass Detection
Authors: Bouchaala Adam , Nayfeh Ali H. , Younis Mohammad I.
Published: December 2016

We present analytical formulations to calculate the induced resonance frequency shifts of electrically actuated clamped-clamped microbeams due to an added mass. Based on the Euler-Bernoulli beam theory, we investigate the linear dynamic responses of the beams added masses, which are modeled as discrete point masses. Analytical expressions based on perturbation techniques and a one-mode Galerkin approximation are developed to calculate accurately the frequency shifts under a DC voltage as a function of the added mass and position. The analytical results are compared to numerical solution of the eigenvalue problem. Results are shown for the fundamental as well as the higher-order modes of the beams. The results indicate a significant increase in the frequency shift, and hence the sensitivity of detection, when scaling down to nano scale and using higher-order modes.
A Novel Mechanism Model of Actual Precision Transmission Devices
Authors: Dong Huimin , Wang Delun , Wang Zhi , Wu Yu , Yu Shudong
Published: December 2016

A mechanism approach is presented in this paper to deal with machining errors and model the accuracy of a precision transmission device in connection with kinematic geometry. The 3D motion of a rotor with six DOFs is perfectly represented by a redundant mechanism [1]. Positions and orientations of two rotors are determined by solving the vector equations of the redundant mechanisms at different instants. The geometric properties of loci traced by the characteristic points and lines of the rotors are analyzed. The invariants of the discrete line-trajectories, the image spherical curve and striction curve, are introduced into the accuracy evaluation for the precision transmission device. The rotary table of a machine tool is used as an example to test the proposed model. The results show that the kinematic geometry is advantageous in modeling effects of errors in multiple body mechanical systems.
An Information-Theoretic Model of Project Schedule Overruns Caused by Task Rework: A Case for Newspeak
Authors: Rooney Warren , Allaire Douglas
Published: December 2016

Many large-scale, complex engineering systems experience significant cost and schedule overruns during their developments. There are many factors that contribute to these overruns, including increased system complexity, task rework, and the in-ability to exhaustively test all states and configurations of a given system, which often leads to re-design efforts. In this work, we focus specifically on task rework and its impact on project schedule overruns. We demonstrate that heavier tail phenomena present in large-scale program development duration can be caused by task rework. Within this context, we hypothesize that one cause of task rework in a project development effort is misinterpretation of task instructions. We develop a computational framework for estimating the information content of a set of task instructions and the expected time to task completion. This reveals that heavier tailed duration phenomena present in many large-scale project development efforts can arise due to task rework caused by misinterpretation.
Design for Ease-of-Repair: Insights From Consumers’ Repair Experiences
Authors: Huang Jida , Esmaeilian Behzad , Behdad Sara
Published: December 2016

With the increasing attention on the role of consumer behavior in sustainable development, consideration of consumer’s product repair and reuse behavior is becoming more and more important in the product design domain. In order to investigate the product ease-of-repair and its effect on future product purchase and recommendation decisions made by consumers, this paper studies the main reasons that consumers were not able to repair a product based on a survey data collected by a wiki-based website that offers repair manuals for consumer electronics. Two main questions have been asked in the survey: what is the last thing you personally fixed? And why did you not succeed in fixing it. The information of these questions and the available response options have been used to compared eleven types of electronics in terms of their ease-of-repair. A list of design features (e.g. openability, accessibility, standardization, and modularity) that may increase the repair adoption by individual consumers has been discussed. In addition, a Data Envelopment Analysis (DEA) method was introduced to compare different categories of products in terms of reparability efficiency. The findings on how repair experiences or efficiency of repair for different categories of devices influence consumers’ future purchase and recommendation decisions have been presented.
Development of Competencies and Their Inter-Relationships in an Engineering Design Course
Authors: Ramachandran Madhumitha , Siddique Zahed
Published: December 2016

Design courses in engineering play an important role to enhance development of competencies needed by students to excel in the 21st century workplace. Problems solved by undergraduate students in engineering programs are mostly well-structured, while real world engineering problems are most likely to be ill-structured and complex. These ill-structured problems have vaguely defined goals and constraints, which demand graduates to apply the learnt knowledge beyond the understanding of fundamental concepts. To prepare and educate the future workforce for engineering workplace, we must provide them with opportunities to learn how to internalize the principles of design and to develop competencies to tackle ill-structured problems through an authentic, immersive experience that involves designing, building and testing an artifact. In this paper, we use students’ self-reported level of competencies to see how students develop competencies and how the inter-relationships among these competencies change overtime in a senior-level design course. We performed this study in Principles of Design course, during fall semester of 2014, where students addressed an ill-structured design problem. Five questionnaires were developed and administered for self-reported assessment of competencies by students. The development of competencies was tracked over time across all five surveys, followed by t-tests to identify the significant patterns of change in the developed competency level. Students showed lack of confidence in competencies related to understanding problem, requirements, concept generation and selection. Communication did not vary significantly throughout the semester. The relationships among the competencies were examined using the correlational analysis at each point and over time to identify the core competencies. Competencies related to communication, understanding problem and understanding requirements are found to be the core competencies as the development of other competencies are dependent on the level of these competencies. Recommendations have been made to modify the course in the areas of core competencies, where students lack confidence. We believe continuous improvement of student professional competencies through course modifications will help students to develop more professional competencies in a semester long design course.
Quantification of Symmetry, Parallelism, and Continuity as Continuous Design Variables for Three-Dimensional Product Representations
Authors: Valencia-Romero Ambrosio , Lugo José E.
Published: December 2016

This work introduces a methodology to quantify the form of a three-dimensional (3D) product representation using the Gestalt principles of symmetry, parallelism, and continuity, and how they can be used as descriptive parameters in product design. First, consistent quantifications of these three Gestalt principles for parametrized 3D representations in a zero-one scale are presented. Then, a generalized methodology applicable to any product form is discussed. It starts with the identification of important aesthetic forms of the product shape and the Gestalt principles that best related to those forms, and ends with the quantification of these Gestalt principles of a 3D product representation. The expressions to quantify the Gestalt principles in question are validated through an online survey in which subjects indicated how much they recognize symmetry, parallelism, or continuity from irregular shapes. Finally, random-effects ordered logit regression is used to determine if the expressions effectively describe the level of recognition of each Gestalt principle. Results show that the proposed quantifications for symmetry, parallelism, and continuity are congruent with subjects perception of these Gestalt principles, and the implications for designers and future work are discussed. Further implications in the design process of these quantifications include the optimization of the product shape for aesthetic, semantic, and functional goals.
Improving Design Resource Management Using Bayesian Network Embedded in Task Network Method
Authors: Xin Chen Hilario Lorenzo , Moullec Marie-Lise , Ball Nigel , Clarkson P. John
Published: December 2016

In Product Development (PD), there is an inherent complexity in deciding what resources should perform which tasks taking into account their effectiveness towards completing the task, while adjusting to their availabilities. The right resources must be applied to the right tasks in the correct order. In this context, process modeling and simulation could aid in resource management decision making. However, most approaches define resources as elements needed to perform the activities without defining their characteristics, or use a single classification such as “designers”. Despite their crucial importance to the delivery of the product, resources such as computational hardware, software, testing resources, amongst others have been overlooked during process planning stages.

This paper presents a new method to model different resource types (designers, computational, testing) and studies the impact of using different options of those resources by simulating the model and analyzing the results. Thus, the new approach, which extends a task network model with Bayesian Networks (BN), allows testing the influence of using different resources on process performance. The method uses BN within each task to model different instances of resources that carries out the design activities (computational, designers and testing) along with its configurable attributes (time, risk, learning curve etc.), and tasks requirements. Thus, activity behavior is shaped depending on the chosen resource option to perform it. The approach enhances the capability to explore resource combination design space. It was applied to an aerospace case study to identify insights such as the best performing resource combinations, critical resources, resource sensitive activities, and the probability of a resource reaching performance targets.
Quantifying the Shape of a Pareto Front in Support of Many-Objective Trade Space Exploration
Authors: Unal Mehmet , Warn Gordon P. , Simpson Timothy W.
Published: December 2016

Complex design optimization problems typically include many conflicting objectives, and the resulting trade space is comprised of numerous design solutions. To efficiently explore a many-objective trade space, form preferences, and select a final design, one must identify and negotiate tradeoffs between multiple, often conflicting, objectives. Identifying conflicting objective pairs allows decision-makers to concentrate on these objectives when selecting preferred designs from the non-dominated solution set, i.e., the Pareto front. Techniques exist to identify and visualize tradeoffs between these conflicting objectives to support trade space exploration; however, these techniques do not quantify, or differentiate, the shape of the Pareto front, which might be useful information for a decision-maker. More specifically, designers could gain insight from the degree of diminishing returns among solutions on the Pareto front, which can be used to understand the extent of the tradeoffs in the problem. Therefore, the shape of the Pareto front could be used to prioritize exploration of conflicting objective pairs. In this paper, we introduce a novel index that quantifies the shape of the Pareto front to provide information about the degree of diminishing returns. The aim of the index is to help designers gain insight into the underlying tradeoffs in a many-objective optimization problem and support trade space exploration by prioritizing the negotiation of conflicting objectives. The proposed Pareto Shape Index is based on analytical geometry and derived from the coordinates of the Pareto solutions in the n objective trade space. The utility of the Pareto Shape Index in differentiating diminishing returns between conflicting objectives is demonstrated by application to an eight-objective benchmark optimization problem.
Application of Topology Optimization and Design for Additive Manufacturing Guidelines on an Automotive Component
Authors: Reddy K. Sai Nithin , Maranan Vincent , Simpson Timothy W. , Palmer Todd , Dickman Corey J.
Published: December 2016

Topology optimization is a well-established engineering practice to optimize the design and layout of parts to create lightweight and low-cost structures, which have historically been difficult, or impossible, to make. Additive Manufacturing (AM) provides the freedom to fabricate the complex and organic shapes that topology optimization often generates. In this paper we use topology optimization to create lightweight designs while conforming to additive manufacturing constraints related to overhanging features and unsupported surfaces when using metallic materials. More specifically, we use design for additive manufacturing (DfAM) rules along with topology optimization to study the tradeoffs between the weight of the part, support requirements, manufacturing costs, and performance. The case study entails redesigning an upright on the SAE Formula student racecar to reduce support structures and manufacturing and material cost when using Direct Metal Laser Sintering (DMLS). Manufacturing the optimized design without applying DfAM rules required support material up to 202.4% of the volume of the model. Using DfAM, the upright is redesigned and manufactured with supports requiring less than 15% of the volume of the model. The results demonstrate the challenges in achieving a balance between weight reduction, manufacturing costs, and factor of safety of the design.