bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Network Partitioning to Design a Green Supply Chain
Authors: Williams Jack , Alizadeh Reza , Allen Janet K. , Mistree Farrokh 
Published: November 2020

Abstract
In supply chain network design, a retailer may determine the number and locations of facilities based on the cost of opening the facility, a customer driving to the facility, and a replenishment truck driving to the facility from a warehouse. However, this does not include the system’s greenhouse gas (GHG) emissions. Given the existential threat posed by global warming, it is pertinent to consider how the design of the system affects its GHG emissions. We model the supply chain as a network of customers and store locations, with customers driving in cars to and from stores and the retailer resupplying the stores from a central warehouse. The number and location of stores is determined while minimizing the GHG emission. Our contributions are (1) to remove the assumption of uniform demand, and instead build a model of a GSC based on population data; (2) to model the GSC as a two-echelon k-median problem. We conduct a sensitivity analysis to study the effect of a carbon tax in encouraging a greener system considering various scenarios under which emissions might increase or decrease. Specific scenarios lead to a lower overall GHG emission. For example, doubling the fuel efficiency of cars decreases emissions by 46% compared to the baseline scenario. The proposed design approach is not limited to GSC design and can be extended to many design problems, including manufacturing, material design, and healthcare.
Design and Modeling of a Variable Stiffness Barrel Mechanism for Ankle Exoskeleton
Authors: Soliman Ali M. , Hussain Irfan , Awad Mohammad I. , Gan Dongming 
Published: November 2020

Abstract
In this paper, we present a novel variable-stiffness joint for a walking assistance ankle exoskeleton. This design is adaptive to user needs in the sense that it can aid in different types of motion, i.e. walking, jogging and running, through different stiffness levels. We created a concept that utilizes multiple springs that could contort into different orientations in order to create a fully compliant ankle exoskeleton. The design provides a wide range of assistive torques without constant replacement of parts or springs for each type of activity. This design can be utilized by a wide range of people engaging in different types of activities. Those could be individuals with an active lifestyle or the elderly suffering from muscular atrophy.
Analytical Mechatronic Modeling and Analysis for Anti-Walkout of PTU Actuator With ADAMS-Simulink Co-Simulation
Authors: Liao Cong , Zhang Haiyan H. , Berry Fred , Chung Jerry , Dessai Ravi 
Published: November 2020

Abstract
A spline clutch maneuvered by an actuator provides a Power Transfer Unit (PTU), the functions of power disconnection, or speed selection. In the driveline system, the PTU actuator is the core mechatronic component to realize the essential functionality. This paper focuses on increasing the performance and stability of the PTU using analytical mechatronic modeling and analysis with ADAMS-Simulink co-simulation. By utilizing the Adams, the PTU was modeled, and the characteristics of the sleeve walk-out were revealed. The motor and partial mechanical components were modeled in the Simulink and combined with the Adams model for co-simulation. The fuzzy logic with PID position control is developed to suppress the on-set of the walk-out. The effectiveness of the control strategy was validated by the co-simulation. This method can be extended to other actuators with spline clutch applications to minimize the risk of walk-out.
Design of Trustworthy Cyber-Physical-Social Systems With Discrete Bayesian Optimization
Authors: Wang Yan 
Published: November 2020

Abstract
Cyber-physical-social systems (CPSS) with highly integrated functions of sensing, actuation, computation, and communication are becoming the mainstream consumer and commercial products. The performance of CPSS heavily relies on the information sharing between devices. Given the extensive data collection and sharing, security and privacy are of major concerns. Thus one major challenge of designing those CPSS is how to incorporate the perception of trust in product and systems design. Recently a trust quantification method was proposed to measure trustworthiness of CPSS by quantitative metrics of ability, benevolence, and integrity. In this paper, the applications of ability and benevolence metrics in design optimization of CPSS architecture are demonstrated. A Bayesian optimization method is developed to perform trust based CPSS network design, where the most trustworthy network with respect to a reference node can be selected to collaborate and share information with.
Machine Learning Augmentation in Micro-Sensor Assemblies
Authors: Hasan Mohammad H. , Alsaleem Fadi , Abbasalipour Amin , Pourkamali Anaraki Siavash , Emad-Un-Din Muhammad , Jafari Roozbeh 
Published: November 2020

Abstract
The size and power limitations in small electronic systems such as wearable devices limit their potential. Significant energy is lost utilizing current computational schemes in processes such as analog-to-digital conversion and wireless communication for cloud computing. Edge computing, where information is processed near the data sources, was shown to significantly enhance the performance of computational systems and reduce their power consumption. In this work, we push computation directly into the sensory node by presenting the use of an array of electrostatic Microelectromechanical systems (MEMS) sensors to perform colocalized sensing-and-computing. The MEMS network is operated around the pull-in regime to access the instability jump and the hysteresis available in this regime. Within this regime, the MEMS network is capable of emulating the response of the continuous-time recurrent neural network (CTRNN) computational scheme. The network is shown to be successful at classifying a quasi-static input acceleration waveform into square or triangle signals in the absence of digital processors. Our results show that the MEMS may be a viable solution for edge computing implementation without the need for digital electronics or micro-processors. Moreover, our results can be used as a basis for the development of new types of specialized MEMS sensors (ex: gesture recognition sensors).
Dichotomy of Design Experience: A Case Study of One Student’s Experience With Problem Typology and His Perceptions of Design
Authors: Olewnik Andrew , Yerrick Randy , Simmons Amanda , Lee Yonghee 
Published: November 2020

Abstract
This paper presents a case study of Jeff, a mechanical engineering senior, and his experience with design in two different contexts — one in the classroom and one extracurricular. After a year-long study of undergraduate engineers, Jeff revealed marked differences in his uptake of design principles and reflexivity toward his thinking within the discipline. We explored with Jeff the critical differences and experiences that led to his changes once we had completed data collection with his peer cohort of undergraduates. We explored Jeff’s interpretation of the differences he considered as positive changes, the attributes of applying principles of problem typology, and the requisite context required to achieve these changes as a student. Through qualitative analysis four assertions are examined — improved approach to design problem solving, broadened view of design, engineering as multiple types of problems, and relevance to the profession — and validated through a member check. Potential implications for engineering education, especially as it pertains to design education are briefly described.
Expected Uncertainty Reduction for Sequential Kriging-Based Reliability Analysis
Authors: Li Meng , Shen Sheng , Barzegar Vahid , Sadoughi Mohammadkazem , Laflamme Simon , Hu Chao 
Published: November 2020

Abstract
Several acquisition functions have been proposed to identify an optimal sequence of samples in sequential kriging-based reliability analysis. However, no single acquisition function provides better performance over the others in all cases. To address this problem, this paper proposes a new acquisition function, namely expected uncertainty reduction (EUR), that serves as a meta-criterion to select the best sample from a set of optimal samples, each identified from a large number of candidate samples according to the criterion of an acquisition function. EUR directly quantifies the expected reduction of the uncertainty in the prediction of limit-state function by adding an optimal sample. The uncertainty reduction is quantified by sampling over the kriging posterior. In the proposed EUR-based sequential sampling framework, a portfolio that consists of four acquisition functions is first employed to suggest four optimal samples at each iteration of sequential sampling. Then, EUR is employed as the meta-criterion to identify the best sample among those optimal samples. The results from two mathematical case studies show that (1) EUR-based sequential sampling can perform as well as or outperform the single use of any acquisition function in the portfolio, and (2) the best-performing acquisition function may change from one problem to another or even from one iteration to the next within a problem.
Evaluating Supply Chain Resource Limits From News Articles and Earnings Call Transcripts: An Application of Integrated Factor Analysis and Analytical Network Process
Authors: Chu Chih-Yuan , Gunay Elif E. , Al-Araidah Omar , Kremer Gül E. 
Published: November 2020

Abstract
Due to the impact of globalization, companies have extended their borders across nations to launch products more competitively. However, globalization affects various uncertainties and risks that may limit the performance of supply chains. Research indicates that models that incorporate uncertainties and risks will help to improve the resilience of global supply chains. In the era of technology, we experience the abundance of textual data from various web-media resources related to companies, which can be deployed to understand the impact of risks on the chain. Accordingly, this study aims to utilize textual data collected from news articles and earnings call transcripts to assess the vulnerability of the suppliers and the chain. Among many, we considered supply chain resource limits as a subcomponent of vulnerability and collected textual data associated with its sub-factors. Then, we proposed an integrated factor analysis and Analytical Network Process (ANP) method to model the company’s supply chain resource limits index. Specifically, factor analysis was used to determine the latent constructs of the variables that are grouped under resource limits and their correlations. This latent construct and correlations were then applied as the interdependencies among variables in the ANP to discover the final importance weights of the variables in terms of supply chain resource limits. The results of the study showed that the shortages of capacity, components, and energy supply are the most critical sub-factors. The company’s supply chain resource limits index (SCRLI) can be further calculated to assist decision-makers of an enterprise in supply chain configuration design, and improve the supply chain resilience.
The Impact of Prototyping Strategies on Crowdfunding Success
Authors: Srinivasan Sriram , Li Zhuoxuan Fanny , Han Yu Lee , Camburn Bradley A. 
Published: November 2020

Abstract
Innovative design and technology startups often struggle to gain market success when launching a new product. Research in business management highlights the impact of strategic marketing to foster launch success. Prototyping plays a critical role in demonstrating the potential of the said new technologies and innovations into the market. Prototypes can engage users or highlight the potential of an opportunity to investors. The design performance impact of prototyping strategies has been evaluated in recent studies. This work explores the impact that strategic prototyping (defined here as the use of techniques such as: subsystem isolation, or scale modeling), has on market outcome. Pilot analysis of two hundred launch campaigns on the marketing and sales platform - Kickstarter.com, is conducted. This database provides clear documentation of the information that is provided to said investors or ‘backers’, and resulting funds received. The relative usage frequency of various strategies is reported from a subset of product launch efforts after which the correlations between the demonstration of the strategies and funding received is calculated. These preliminary observations may support designers in managing project resources while developing prototypes to launch new products.
Reliability-Informed Life-Cycle Warranty Cost Analysis: A Case Study on a Transmission in Agricultural Equipment
Authors: Li Meng , Liu Jinqiang , Nemani Venkat Pavan , Ahmed Navaid , Kremer Gül E. , Hu Chao 
Published: November 2020

Abstract
In agricultural and industrial equipment, both new and remanufactured systems are often available for warranty coverage. In such cases, it may be challenging for equipment manufacturers to properly trade-off between the system reliability and the cost associated with a replacement option (e.g., replace with a new or remanufactured system). To address this problem, we present a reliability-informed life-cycle warranty cost (LCWC) analysis framework that enables equipment manufacturers to evaluate different warranty policies. These warranty policies differ in whether a new or remanufactured system is used for replacement in the case of product failure. The novelty of this LCWC analysis framework lies in its ability to incorporate real-world field reliability data into warranty policy assessment using probabilistic warranty cost models that consider multiple life cycles. First, the reliability functions for the new and remanufactured systems are built as the time-to-failure distributions that provide the best-fit to the field reliability data. Then, these reliability functions and their corresponding warranty policies are used to build the LCWC models according to the specific warranty terms. Finally, Monte Carlo simulation is used to propagate the time-to-failure uncertainty of each system, modeled by its reliability function, through each LCWC model to produce a probability distribution of the LCWC. The effectiveness of the proposed reliability-informed LCWC analysis framework is demonstrated with a real-world case study on a transmission used in some agricultural equipment.
Architecting the Cooperative 3D Printing System
Authors: Poudel Laxmi , Marques Lucas Galvan , Williams Robert Austin , Hyden Zachary , Guerra Pablo , Fowler Oliver Luke , Moquin Stephen Joe , Sha Zhenghui , Zhou Wenchao 
Published: November 2020

Abstract
Cooperative 3D printing (C3DP) is a novel approach to additive manufacturing, where multiple mobile 3D printing robots work together cooperatively to print the desired part. At the core of C3DP lies the chunk-based printing strategy. This strategy splits the desired part into smaller chunks, and then the chunks are assigned and scheduled to be printed by individual printing robots. In our previous work, we presented various hardware and software components of C3DP, such as mobile 3D printers, chunk-based slicing, scheduling, and simulation. In this study, we present a fully integrated and functional C3DP platform with all necessary components, including chunker, slicer, scheduler, printing robots, build floor, and outline how they work in unison from a system-level perspective. To realize C3DP, new developments of both hardware and software are presented, including new chunking approaches, scalable scheduler for multiple robots, SCARA-based printing robots, a mobile platform for transporting printing robots, modular floor tiles, and a charging station for the mobile platform. Finally, we demonstrate the capability of the system using two case studies. In these demonstrations, a CAD model of a part is fed to the chunker, divided into smaller chunks, passed to the scheduler, and assigned and scheduled to be printed by the scheduler with a given number of robots. The slicer generates G-code for each of the chunks and combines G-code into one file for each robot. The simulator then uses the G-code generated by the slicer to generate animations for visualization purposes.
Vibration Suppression of a Harmonically Forced Oscillator Using a Passive Nonlinear Vibration Absorber
Authors: Yu Bo 
Published: November 2020

Abstract
In this paper, the performance of a nonlinear vibration absorber with different nonlinearity is studied. The analytical solutions of periodic motions are obtained using the general harmonic balance method. As the nonlinear strength is weak, the effectiveness of the absorber is discussed. For strong nonlinearities, unstable parodic motions can be obtained and stabilities of the periodic motions are determined through the eigenvalue analysis. The Hopf and saddle bifurcations are observed. Numerical simulations are illustrated for both masses at the resonance peaks. The harmonic amplitude spectrums show the harmonic effects on periodic motions, and the corresponding accuracy of approximate analytical solutions.
Uncertainty Quantification With Maximum Entropy Method for Fatigue Life Estimation
Authors: Nielsen S. M. , Hougaard H. A. , Balling O. 
Published: November 2020

Abstract
Use of high-fidelity fatigue models that incorporate not only material uncertainty but also part variability and operational uncertainties can improve the accuracy of predictive maintenance and thus decrease operational cost. However, due to the large number of computationally expensive cost function evaluations necessary, little work has been done to explore this field. In this research, the expected life probability distributions with low computational cost is estimated through a general statistical framework that applies Maximum Entropy Method (MEM), fractional statistical moments and Multiplicative Dimensional Reduction (M-DRM). The framework is tested on advanced models of a 6204 SKF ball bearing. The influence of critical part tolerances and load conditions on fatigue life with a probability density function with only 80 function evaluations is quantified in both a finite element analysis and a non-linear analytical model. The number of function evaluations is one order of magnitude lower than necessary for a comparable accuracy achieved by Monte Carlo simulation.
PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs
Authors: Chen Wei , Ahmed Faez 
Published: November 2020

Abstract
Deep generative models are proven to be a useful tool for automatic design synthesis and design space exploration. When applied in engineering design, existing generative models face three challenges: 1) generated designs lack diversity and do not cover all areas of the design space, 2) it is difficult to explicitly improve the overall performance or quality of generated designs, and 3) existing models generate do not generate novel designs, outside the domain of the training data. In this paper, we simultaneously address these challenges by proposing a new Determinantal Point Processes based loss function for probabilistic modeling of diversity and quality. With this new loss function, we develop a variant of the Generative Adversarial Network, named “Performance Augmented Diverse Generative Adversarial Network” or PaDGAN, which can generate novel high-quality designs with good coverage of the design space. Using three synthetic examples and one real-world airfoil design example, we demonstrate that PaDGAN can generate diverse and high-quality designs. In comparison to a vanilla Generative Adversarial Network, on average, it generates samples with 28% higher mean quality score with larger diversity and without the mode collapse issue. Unlike typical generative models that usually generate new designs by interpolating within the boundary of training data, we show that PaDGAN expands the design space boundary outside the training data towards high-quality regions. The proposed method is broadly applicable to many tasks including design space exploration, design optimization, and creative solution recommendation.
A Methodological Framework for Making the Transition From Traditional Innovation Teaching Towards Serious Games
Authors: Ma Yiming , Vallet Flore , Cluzel François , Yannou Bernard 
Published: November 2020

Abstract
Serious games (SGs) are motivational and practical pedagogical tools that have been widely used in design education. SGs seem to be an efficient way to give instructions on innovation processes (IPs), offering unique and attractive environments to support situated learning. While there has been much interest in SGs of the IPs type, there is very little research about the design framework to reduce the complexity and time consumption of their design process. This paper presents the preliminary results of our ongoing study: a design framework adapted to innovation SGs. The framework integrates eight general design frameworks/models/methodologies for SGs. Besides, it introduces a new stage “analysis of traditional teaching experience,” which conducive to the early phases of the design. We use a case study to prove the value of this stage. First, it aids designers in defining the teaching objectives of innovation SGs, that is, choosing required competencies from innovation competency frameworks. More importantly, it helps identify game mechanics that may contribute to the realization of teaching objectives. This stage should support designers successfully making the transition from traditional innovation teaching towards SGs.
A Primal Treatise of Constant-Force, Compliant Segments and Mechanisms
Authors: Midha Ashok , Lodagala Vamsi , Bagivalu Prasanna Pratheek , Komatireddy Jyothi 
Published: November 2020

Abstract
The evolution of constant-force mechanisms is propelled by a growing interest in being able to exert constant or near-constant force in various applications. Compliant mechanisms have recently received much attention in the design of constant-force mechanisms because of their several advantages, e.g. fewer parts, compact construct, natural energy storage, no backlash, among many others. There have been many research efforts in developing various techniques to design these mechanisms for applications in diverse fields. Several of these techniques require design optimization to generate a constant force over a desired range of motion. There is generally a lack of understanding of the mechanics of the generation of constant force. This paper presents the hypothesis that simple arrangements, such as a rigid link with a torsional spring, or compliant segments, under axial loading are capable of producing constant force. Three compliant segment types are considered herein: fixed-free, pinned-pinned, and fixed-guided beams under axial loading, to demonstrate that they can exert near-constant force, without the need for a design optimization. This paper further exemplifies that the proposed theory is the kernel to generating constant force by different mechanism configurations.