bluuebunny/crossref_metadata_2025_split huggingface dataset:
Additive Manufacture of Fibre-Reinforced Structures: Design Process and Principles
Authors: Camburn Bradley , Ismail Elyud , Perez K. Blake , Lauff Carlye , Wood Kristin 
Published: November 2019

Abstract
Fiber-reinforcement of structures built with additive manufacturing (AM) has been the focus of many recent innovations in the AM space. These innovations have further enabled AM’s progress from a prototyping technology to a viable manufacturing process for end use parts under normal load conditions. This paper introduces a set of design principles to drive innovation and the creation of novel AM technologies capable of producing fiber-reinforced components. The principles were developed through a comprehensive survey of the literature and patents to identify fundamental design insights that made the published achievements and innovations possible. From the collected body of insights, 23 unique design principles are identified. These principles are formalized and organized within the framework of a matrix representation, connecting established fiber-reinforced composite guidelines to specific sub-functions of AM. Finally, a fiber-reinforced additive manufacturing machine is developed by employing a subset of the identified principles as a demonstration of their utility.
Post-Disruption Performance Recovery to Enhance Resilience of Interconnected Network Systems
Authors: Wu Jiaxin , Wang Pingfeng 
Published: November 2019

Abstract
Mitigating the effect of potential disruptive events at the operating phase of an engineered system therefore improving the system’s failure resilience is an importance yet challenging task in system operation. For complex networked system, different stakeholders complicate the analysis process by introducing different characteristics, such as different types of material flow, storage, response time, and flexibility. With different types of systems, the resilience can be improved by enhancing the failure restoration capability of the systems with appropriate performance recovery strategies. These methods include but not limit to, rerouting paths, optimal repair sequence and distributed resource centers. Considering different characteristics of disruptive events, effective recovery strategies for the failure restoration must be selected correspondingly. However, the challenge is to develop a generally applicable framework to optimally coordinate different recovery strategies and thus lead to desirable failure restoration performances. This paper presents a post-disruption recovery decision-making framework for networked systems, to help decision-makers optimize recovery strategies, in which the overall recovery task is formulated as an optimization problem to achieve maximum resilience. A case study of an electricity distribution system is used to demonstrate the feasibility of the developed framework and the comparison of several recovery strategies for disruption management.
Nonlinear Vibration Analysis of a Flexible Rotor Supported by a Journal Bearing Considering Journal Angular Motion
Authors: Koondilogpiboon Nuntaphong , Inoue Tsuyoshi 
Published: November 2019

Abstract
The effect of bearing length to diameter (L/D) ratio and large disk position on nonlinear vibration (limit cycle and bifurcation type) of a flexible rotor-bearing system is investigated. The rotor consists of a shaft modeled by 1-D finite elements (FE), two small disks and a large disk. It is supported by a self-aligning ball bearing and an axial-groove journal bearing with L/D ratio of 0.4 and 0.6. Two large disk positions: 340 and 575 mm measured from the ball bearing are investigated. The journal angular motion, which is essential for the highly flexible rotor but typically not considered in the previous nonlinear vibration literature; is considered in nonlinear bearing force calculation. The degrees of freedom (DOF) of the rotor-bearing system are reduced to those of the node that the nonlinear journal bearing force and moment act on by real mode component mode synthesis (CMS) that retains only the 1st forward and backward modes. Shooting method and Floquet multiplier analysis are applied to the reduced rotor-bearing system to obtain limit cycles and their stability of each bearing L/D ratio and large disk position case. Numerical results indicate that supercritical Hopf bifurcation only occurs in the case of L/D = 0.4 and large disk position 575 mm, otherwise subcritical occurs. However, if the typical bearing model that does not consider journal angular motion is used, the bifurcation type for the case of L/D = 0.6 with large disk position 575 mm will change to supercritical. Lastly, the experiments with the same L/D ratio and large disk position investigated in the calculation are performed as a validation. The experimental result of each case shows the same bifurcation type as the calculation result using the bearing model that considers the journal angular motion.
Motivations for Users Participating in Co-Innovation Communities: A Case Study of Local Motors
Authors: Zheng Qing , Guo Wei 
Published: November 2019

Abstract
Online user collaborative innovation (co-innovation) community is increasingly used to involve customers in product and service innovation. Why users participate in the innovation is a critical problem for firms managing the community. However, little is known about user motivations. The purpose of this paper is to identify the motivations for users participating in online co-innovation communities. Based on the expectancy theory, this study employs netnography to investigate user motivations with user actual participation behaviors. In accordance with the procedures of netnography, user participation data is collected though web mining. Then, four behavior properties are defined according to behavior characteristics. Finally, six different motivations are identified. The results show that a small number of users are inspired by status and reputation and individuality demands. Monetary rewards is one of the main motivations that make users contributing to the complex technical product process. Social relations and interest and curiosity are also important factors that drive users participating. The most of users partake for interest and curiosity. According to the different motivations, this study provides several managerial insights on how to successfully attract and motivate more users to contribute to product development in co-innovation communities. This paper contributes a systematic and efficient method for identifying user motivations. In addition, the study provides a better theoretical understanding of user motivations and offers practice guidance on inspiring and managing users for co-innovation community practitioners.
Power Loss Measurements of Rolling Element Bearings Subject to Combined Radial and Axial Loads
Authors: Vedera Kevin , Hong Isaac , Talbot David , Kahraman Ahmet , Zhou Sen 
Published: November 2019

Abstract
Power losses of load carrying gear and bearing components of automotive transmissions have become a major research area in recent years. Measurement of power loss of a gearbox is a routine task where losses from rolling element bearings, gear meshes and seals collectively define the total loss. However, separating bearing and gear mesh losses is not possible, as a gear mesh cannot be operated without support bearings. This study aims at developing a methodology for measuring power losses of rolling element bearings of different types operated under realistic load, speed and temperature conditions. A test machine concept is implemented to apply combined radial and axial loads to a pair of test bearings in a stable and repeatable manner, with rotational speed and lubrication parameters controlled tightly during tests. The proposed test methodology is employed to evaluate power loss for three different types of bearings. Load-dependent and load-independent components of power loss are separated, and influence of speed and load values on bearing mechanical loss are quantified. A repeatability study of the machine and methodology is also presented to demonstrate the accuracy of the proposed setup.
Shape Optimization Framework for the Path of the Primary Compliance Vector in Compliant Mechanisms
Authors: Kooistra Hylke , Kim Charles J. , van de Sande Werner W. P. J. , Herder Just L. 
Published: November 2019

Abstract
The primary compliance vector captures the predominant kinematic degree of freedom of a mechanism. Its displacement describes large deformation mechanism behavior and can be an optimization objective in detailed compliant mechanism design. This paper presents a general framework for the optimization of the PCV path of compliant mechanisms using unified stiffness characterization, Fourier descriptors, and surrogate-based optimization. We found a meaningful objective formulation that evaluates PCV path shape independently. Furthermore, we reason that design variables should effect mechanism shape. Lastly, we apply the framework to a design example.
Complex Solutions for Complex Problems?: Exploring the Effects of Task Complexity on Student Use of Design for Additive Manufacturing and Creativity
Authors: Prabhu Rohan , Miller Scarlett R. , Simpson Timothy W. , Meisel Nicholas A. 
Published: November 2019

Abstract
The integration of additive manufacturing (AM) processes in many industries has led to the need for AM education and training, particularly on design for AM (DfAM). To meet this growing need, several academic institutions have implemented educational interventions, especially project- and problem-based, for AM education; however, limited research has explored how the choice of the problem statement influences the design outcomes of a task-based AM/DfAM intervention. This research explores this gap in the literature through an experimental study with 222 undergraduate engineering students. Specifically, the study compared the effects of restrictive and dual (restrictive and opportunistic) DfAM education, when introduced through either a simple or complex design task. The effects of the intervention were measured through (1) changes in student DfAM self-efficacy, (2) student self-reported emphasis on DfAM, and (3) the creativity of student AM designs. The results show that the complexity of the design task has a significant effect on the participants’ self-efficacy with, and self-reported emphasis on, certain DfAM concepts. The results also show that the complex design task results in participants generating ideas with greater median uniqueness compared to the simple design task. These findings highlight the importance of the chosen problem statement on the outcomes of a DfAM educational intervention, and future work is also discussed.
The Prototyping Behaviors of Startups: Exploring the Relationship Between Prototyping Behavior and the Financial Success of Startups
Authors: Nelson Jacob , Mahan Tobias , McComb Christopher , Menold Jessica 
Published: November 2019

Abstract
Prototyping is a crucial part of new product development and engineers and designers rely on prototyping to bring novel technologies to market. In recent years, tech-based startups like Tesla or Udacity have revolutionized their respective industries. However, many tech-based startups are unable to create a viable product with their available resources, and fail before ever making it to market. In this work, we analyze survey responses from 34 startup representatives to investigate the relationship between prototyping practice, startup success, and perceived difficulty of startup tasks. K-means cluster analysis shows three distinct groups, differentiated by (1) their amount of available funding, (2) their use of prototyping best practices, and (3) their reported difficulty in startup tasks. High-performing startups reported having the highest funding, experiencing less difficulty in startup tasks, and using prototyping best practices more frequently than their peers.
But Will it Print?: Assessing Student Use of Design for Additive Manufacturing and Exploring its Effect on Design Performance and Manufacturability
Authors: Prabhu Rohan , Miller Scarlett R. , Simpson Timothy W. , Meisel Nicholas A. 
Published: November 2019

Abstract
Additive manufacturing (AM) enables engineers to improve the functionality and performance of their designs by adding complexity at little to no additional cost. However, AM processes also exhibit certain unique limitations, such as the presence of support material, which must be accounted for to ensure that designs can be manufactured feasibly and cost-effectively. Given these unique process characteristics, it is important for an AM-trained workforce to be able to incorporate both opportunistic and restrictive design for AM (DfAM) considerations into the design process. While AM/DfAM educational interventions have been discussed in the literature, limited research has investigated the effect of these interventions on students’ use of DfAM. Furthermore, limited research has explored how DfAM use affects the performance of students’ AM designs. This research explores this gap through an experimental study with 123 undergraduate students. Specifically, participants were exposed to either restrictive DfAM or dual DfAM (both opportunistic and restrictive) and then asked to participate in an AM design challenge. The students’ final designs were evaluated for (1) performance with respect the design objectives and constraints, and (2) the use of the various aspects of DfAM. The results showed that the use of certain DfAM considerations, such as minimum feature size and support material mass, successfully predicted the performance of the AM designs. Further, while the variations in DfAM education did not influence the performance of the AM designs, it did have an effect on the students’ use of certain DfAM concepts in their final designs. These results highlight the influence of DfAM education in bringing about an increase in students’ use of DfAM. Moreover, the results demonstrate the potential influence of DfAM in reducing build time and build material of the students’ AM designs, thus improving design performance and manufacturability.
Model Predictive Control of General Fractional Order Systems Using a General Purpose Optimal Control Problem Solver: RIOTS
Authors: Dehghan Sina , Zhao Tiebiao , Chen YangQuan , Homayouni Taymaz 
Published: November 2019

Abstract
RIOTS is a Matlab toolbox capable of solving a very general form of integer order optimal control problems. In this paper, we present an approach for implementing Model Predictive Control (MPC) to control a general form of fractional order systems using RIOTS toolbox. This approach is based on time-response-invariant approximation of fractional order system with an integer order model to be used as the internal model in MPC. The implementation of this approach is demonstrated to control a coupled MIMO commensurate fractional order model. Moreover, the performance and its application process is compared to examples reported in the literature.
Robust Optimization With Mixed Interval and Probabilistic Parameter Uncertainties, Model Uncertainty, and Metamodeling Uncertainty
Authors: Zhang Yanjun , Xia Tingting , Li Mian 
Published: November 2019

Abstract
Various types of uncertainties, such as parameter uncertainty, model uncertainty, metamodeling uncertainty may lead to low robustness. Parameter uncertainty can be either epistemic or aleatory in physical systems, which have been widely represented by intervals and probability distributions respectively. Model uncertainty is formally defined as the difference between the true value of the real-world process and the code output of the simulation model at the same value of inputs. Additionally, metamodeling uncertainty is introduced due to the usage of metamodels. To reduce the effects of uncertainties, robust optimization (RO) algorithms have been developed to obtain solutions being not only optimal but also less sensitive to uncertainties. Based on how parameter uncertainty is modeled, there are two categories of RO approaches: interval-based and probability-based. In real-world engineering problems, both interval and probabilistic parameter uncertainties are likely to exist simultaneously in a single problem. However, few works have considered mixed interval and probabilistic parameter uncertainties together with other types of uncertainties. In this work, a general RO framework is proposed to deal with mixed interval and probabilistic parameter uncertainties, model uncertainty, and metamodeling uncertainty simultaneously in design optimization problems using the intervals-of-statistics approaches. The consideration of multiple types of uncertainties will improve the robustness of optimal designs and reduce the risk of inappropriate decision-making, low robustness and low reliability in engineering design. Two test examples are utilized to demonstrate the applicability and effectiveness of the proposed RO approach.
Effect of Assistive Methods on the Sense of Fulfillment With Agency: Modeling With Flow and Attribution Theories
Authors: Nanno Dan , Yanagisawa Hideyoshi 
Published: November 2019

Abstract
Several assistive technologies for users’ operations have been recently developed. A user’s sense of agency (SoA) decreases with increasing system assistance, possibly resulting in a decrease in the user’s sense of fulfillment. This study aims to provide a design guideline for an assistive method to maintain and improve the sense of fulfillment with SoA. We propose a mathematical model describing the mechanisms by which the assistive method affects SoA and SoA induces a sense of fulfillment. The experience in the flow state is assumed to be a sense of fulfillment. The assistance effect on the skill-challenge plane in flow theory is defined as an increase in skill and decrease in challenge. The factor that separates the two effects from attribution theory is the locus of causality, which is matched to the judgement of agency (JoA) from the two-step account of agency. We hypothesized that the assistance increases the perception of skill and sense of fulfillment is greater when the locus of causality is internal, rather than external. To verify this hypothesis, a game task experiment was conducted with assistance that varied with the ease of recognition. We hypothesized that a player’s JoA is internal for hard-to-recognize assistance, resulting in a high sense of fulfillment. Experimental results supported this hypothesis.
Improving Hole-Searching Accuracy for Peg-in-Hole Assembly With Manipulator Harmonic Drive Uncertainty
Authors: Chen Po-Yu , Chan Kuei-Yuan 
Published: November 2019

Abstract
Uncertainties of a robot manipulator include the inaccurate transformation between each coordinate, (e.g., robot base, flange, camera, tool, and workpiece) and the inherent variations within each links and mechanical components. In this work we consider the impact of harmonic drive uncertainty in peg-in-hole assembly. We investigate the accumulations of transmission errors within robot dynamic and nonlinear process in rotation. Models of manipulators with uncertainty parameters in harmonic drive systems are developed. The parameters in our harmonic drive model with uncertainty are identified through testing. The transformation metrics between each coordinate are also determined by detecting fiducial pattern and marker with well-calibrated camera. As a result we have a virtual robot model with parameters and uncertainties much closer to the real system. The simulation results show that the accuracy of hole-searching can reach 0.50 mm position error and 0.16 degree orientation error for hole locations that are not known as a priori.
Development of a Compact and Cost Effective MSL System Based on a Compliant Nanomanipulator
Authors: Liu Zheng , Zhang Zhen , Guan Yingchun 
Published: November 2019

Abstract
This paper proposes a compact and cost-effective MSL (Micro Stereo Lithography) prototyping system. A self-developed compliant XY nanomanipulating stage is responsible for the fabrication quality in one layer. And a blu-ray LED laser module is utilized as a cost-effective light source. The experimental results show that the MSL prototyping system is capable of achieving ∼ 2 μm cured width for circular patterns.
Reconciling Co-Evolving Engineering and Customer Requirements With a Looped Bayesian Model
Authors: Slon Christopher , Pandey Vijitashwa 
Published: November 2019

Abstract
Engineering and manufacturing abilities of firms evolve with every passing year and so do the preferences of the customers buying their products. Reconciling this coevolution is essential to staying competitive in the marketplace. In this paper, we provide a looped Bayesian framework to accomplish this so that designs can evolve as engineering capabilities increase and customer preferences change. We begin with an approach to incorporating the voice of the customer through the multi-attribute utility function, the core of decision-based design. We consider the utility to be a stochastic function governed by shape parameters that are random variables. Typically, a representative preference or utility function is used or the function is aggregated over many decision makers and regarded as a deterministic function of specified shape parameters. In our approach, the shape parameters represent the stochastic nature of preference behavior either due to variation in a decision maker’s state of mind from one decision to another, or due to a multiplicity of decision makers. The novelty of this approach is in taking a Bayesian perspective on the stochastic utility function. We consider the utility distribution in the design phase as a prior distribution and we update the prior to a posterior with feedback on the actual product in production. The method is valuable in providing a means to improve the level of informativeness of the design level utility function for adjustments to the design or for the next design revision in the cycle of continuous improvement. We present our approach on a real-life assembly problem in an automotive manufacturing floor.
Design and Analysis of a Tensegrity Mechanism for a Bio-Inspired Robot
Authors: Venkateswaran Swaminath , Furet Matthieu , Chablat Damien , Wenger Philippe 
Published: November 2019

Abstract
Piping inspection robots are of greater interests in industries such as nuclear, chemical and sewage. The design of such robots is highly challenging owing to factors such as locomotion inside pipes with varying diameters, cable management, and complex pipe bends (or) junctions. A rigid bio-inspired caterpillar type piping inspection robot was developed at LS2N, France. By introducing tensegrity mechanisms and four-bar wheel mechanisms, the design of this robot is modified into a reconfigurable system. The tensegrity mechanism employs a passive universal joint with three tension springs and three cables for actuation. The positioning of the end effector with respect to the base of the mechanism plays an important role in determining the maximum tilt angle (or) bending limit of the system. By workspace analysis of three case studies, the best solution is chosen which generates the maximum tilt. A static force analysis is then performed on the mechanism to determine its stability under the influences of preload. By the modification of design parameters, stable configurations are determined followed by which cable actuation of mechanism is analyzed for estimating applied forces.