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Shop Floor Lot-Sizing And Scheduling With A Two-Stage Stochastic Programming Model Considering Uncertain Demand And Workforce Efficiency, Yihua Li, Guiping Hu 2017 Iowa State University

Shop Floor Lot-Sizing And Scheduling With A Two-Stage Stochastic Programming Model Considering Uncertain Demand And Workforce Efficiency, Yihua Li, Guiping Hu

Industrial and Manufacturing Systems Engineering Publications

Efficient and flexible production planning is necessary for the manufacturing industry to stay competitive in today’s global market. Shop floor lot-sizing and scheduling is one of the most challenging and rewarding subjects for the management. In this study, a two-stage stochastic programming model is proposed to solve a single-machine, multi-product shop floor lot-sizing and scheduling problem. Two sources of uncertainties are considered simultaneously: product demand from the market, and workforce efficiency, which is the major contribution of this study. The workforce efficiency affects the system productivity, and we propose different distributions to model its uncertainty with insufficient information.The ...


Interaction Of Automation Visibility And Information Quality In Flight Deck Information Automation View Document, Michael C. Dorneich, Rachel Dudley, Emmanuel Letsu-Dake, William Rogers, Stephen D. Whitlow, Michael Dillard, Erik Nelson 2017 Iowa State University

Interaction Of Automation Visibility And Information Quality In Flight Deck Information Automation View Document, Michael C. Dorneich, Rachel Dudley, Emmanuel Letsu-Dake, William Rogers, Stephen D. Whitlow, Michael Dillard, Erik Nelson

Industrial and Manufacturing Systems Engineering Publications

An empirical study evaluated key human factors issues related to automation visibility and information quality, based on a refined definition of information automation. Next-generation air transportation system operational concepts will dramatically affect the types and amount of information available on flight decks. Information automation systems collect, process, and present information to support pilot tasks and awareness. The definition of flight deck information automation was refined to differentiate it from other types of automation. Pilots interacted with an example information automation system to investigate the premise that automation visibility will have an impact on the ability of pilots to detect problems ...


Sequential Exploration-Exploitation With Dynamic Trade-Off For Efficient Reliability Analysis Of Complex Engineered Systems, Mohammadkazem Sadoughi, Chao Hu, Cameron A. MacKenzie, Amin Toghi Eshghi, Soobum Lee 2017 Iowa State University

Sequential Exploration-Exploitation With Dynamic Trade-Off For Efficient Reliability Analysis Of Complex Engineered Systems, Mohammadkazem Sadoughi, Chao Hu, Cameron A. Mackenzie, Amin Toghi Eshghi, Soobum Lee

Industrial and Manufacturing Systems Engineering Publications

A new sequential sampling method, named sequential exploration-exploitation with dynamic trade-off (SEEDT), is proposed for reliability analysis of complex engineered systems involving high dimensionality and a wide range of reliability levels. The proposed SEEDT method is built based on the ideas of two previously developed sequential Kriging reliability methods, namely efficient global reliability analysis (EGRA) and maximum confidence enhancement (MCE) methods. It employs Kriging-based sequential sampling to build a surrogate model (i.e., Kriging model) that approximates the performance function of an engineered system, and performs Monte Carlo simulation on the surrogate model for reliability analysis. A new acquisition function ...


Models Of Models: The Symbiotic Relationship Between Models And Wargames, Vikram Mittal, Jeffrey B. Demarest, Kennon S. Gilliam, Robert L. Page 2017 United States Military Academy

Models Of Models: The Symbiotic Relationship Between Models And Wargames, Vikram Mittal, Jeffrey B. Demarest, Kennon S. Gilliam, Robert L. Page

West Point Research Papers

Military planning uses wargames to model the processes and decisions of an operation. As these operations become increasingly complex, the wargames similarly become more complex. Complex wargames are difficult to design and execute. As such, computer-based modeling and simulation can aid the wargame development, ensuring smooth execution. In particular, computer-based modeling and simulation can develop and validate the processes, determine initial conditions, evaluate the rules, and aid in validation. In turn, the wargame can provide useful data that can be fed into detailed models that can provide quantitative analysis to decision-makers.


Graduated Stress Exposure Of Spaceflight Hazards In A Virtual Environment, Tor Finseth, Nir Keren, Warren D. Franke, Michael C. Dorneich, Clayton C. Anderson 2017 Iowa State University

Graduated Stress Exposure Of Spaceflight Hazards In A Virtual Environment, Tor Finseth, Nir Keren, Warren D. Franke, Michael C. Dorneich, Clayton C. Anderson

Warren D Franke

Stress experienced by astronauts during high-level hazardous situations may poses risk to personnel wellbeing and to mission success. Stress inoculation training (SIT) provides individuals with experience of minor stressors and coping skills during non-critical times to enhance their resistance to stress. This study evaluates the effect of exposure to a low level stressor on physiological response and cognitive load in high level stressor setting. Simulation of fire emergency on the International Space Station (ISS) in a full-scale, immersive, interactive, 3D virtual reality environment facilitated a process for stress inoculation. The experimental settings included two groups that have been exposed to ...


Incorporation Of Future Building Operating Conditions Into The Modeling Of Building–Microclimate Interaction: A Feasibility Approach, Kelly Kalvelage, Ulrike Passe, Caroline Krejci, Michael C. Dorneich 2017 Iowa State University

Incorporation Of Future Building Operating Conditions Into The Modeling Of Building–Microclimate Interaction: A Feasibility Approach, Kelly Kalvelage, Ulrike Passe, Caroline Krejci, Michael C. Dorneich

Ulrike Passe

This paper presents a novel modeling methodology that integrates the near building environmental conditions (or microclimate), whole-building design, and occupant behavior. Accurate predictions of the future building operating conditions lead to designs that serve the building’s purpose – to support occupants’ tasks. This study bridges the gap between human factors and architecture to include physical, cognitive, and organizational systems into building information modeling using future typical meteorological year climate data, canyon air temperature microclimate model, and a whole-building energy simulation to investigate the impact of future microclimate conditions on a “typical” single-occupant office. Additionally, to capture the effects of building ...


One-Sample Bayes Inference For Symmetric Distributions Of 3-D Rotations, Yu Qiu, Danial J. Nordman, Stephen B. Vardeman 2017 Iowa State University

One-Sample Bayes Inference For Symmetric Distributions Of 3-D Rotations, Yu Qiu, Danial J. Nordman, Stephen B. Vardeman

Stephen B. Vardeman

A variety of existing symmetric parametric models for 3-D rotations found in both statistical and materials science literatures are considered from the point of view of the “uniform-axis-random-spin” (UARS) construction. One-sample Bayes methods for non-informative priors are provided for all of these models and attractive frequentist properties for corresponding Bayes inference on the model parameters are confirmed. Taken together with earlier work, the broad efficacy of non-informative Bayes inference for symmetric distributions on 3-D rotations is conclusively demonstrated.


Bayes Inference For A Tractable New Class Of Non-Symmetric Distributions For 3-Dimensional Rotations, Melissa Ann Bingham, Danial J. Nordman, Stephen B. Vardeman 2017 University of Wisconsin - La Crosse

Bayes Inference For A Tractable New Class Of Non-Symmetric Distributions For 3-Dimensional Rotations, Melissa Ann Bingham, Danial J. Nordman, Stephen B. Vardeman

Stephen B. Vardeman

Both existing models for non-symmetric distributions on 3-dimensional rotations and their associated one-sample inference methods have serious limitations in terms of both interpretability and ease of use. Based on the intuitively appealing Uniform Axis- Random Spin (UARS) construction of Bingham, Nordman, and Vardeman (2009) for symmetric families of distributions, we propose new highly interpretable and tractable classes of non-symmetric distributions that are derived from mixing UARS distributions. These have an appealing Preferred Axis-Random Spin (PARS) construction and (unlike existing models) directly interpretable parameters. Non-informative one-sample Bayes inference in these models is a direct generalization of UARS methods introduced in Bingham ...


A Pseudo-Likelihood Analysis For Incomplete Warranty Data With A Time Usage Rate Variable And Production Counts, Yu Qiu, Danial J. Nordman, Stephen B. Vardeman 2017 Iowa State University

A Pseudo-Likelihood Analysis For Incomplete Warranty Data With A Time Usage Rate Variable And Production Counts, Yu Qiu, Danial J. Nordman, Stephen B. Vardeman

Stephen B. Vardeman

The most direct purpose of collecting warranty data is tracking associated costs. However, they are also useful for quantifying a relationship between use rate and product time-to-first-failure and for estimating the distribution of product time-to-first-failure (which is modeled in this article as depending on use rate and a unit potential life length under continuous use). Employing warranty data for such reliability analysis purposes is typically complicated by the fact that some parts of some warranty data records are missing. A pseudo-likelihood methodology is introduced to deal with some kinds of incomplete warranty data (such as that available in a motivating ...


Majority Voting By Independent Classifiers Can Increase Error Rates, Stephen B. Vardeman, Max Morris 2017 Iowa State University

Majority Voting By Independent Classifiers Can Increase Error Rates, Stephen B. Vardeman, Max Morris

Stephen B. Vardeman

The technique of “majority voting” of classifiers is used in machine learning with the aim of constructing a new combined classification rule that has better characteristics than any of a given set of rules. The “Condorcet Jury Theorem” is often cited, incorrectly, as support for a claim that this practice leads to an improved classifier (i.e., one with smaller error probabilities) when the given classifiers are sufficiently good and are uncorrelated. We specifically address the case of two-category classification, and argue that a correct claim can be made for independent (not just uncorrelated) classification errors (not the classifiers themselves ...


Elementary Statistical Methods And Measurement Error, Stephen B. Vardeman, Joanne Wendelberger, Tom Burr, Michael S. Hamada, Leslie M. Moore, Marcus Jobe, Max Morris, Huaiqing Wu 2017 Iowa State University

Elementary Statistical Methods And Measurement Error, Stephen B. Vardeman, Joanne Wendelberger, Tom Burr, Michael S. Hamada, Leslie M. Moore, Marcus Jobe, Max Morris, Huaiqing Wu

Stephen B. Vardeman

How the sources of physical variation interact with a data collection plan determines what can be learned from the resulting dataset, and in particular, how measurement error is reflected in the dataset. The implications of this fact are rarely given much attention in most statistics courses. Even the most elementary statistical methods have their practical effectiveness limited by measurement variation; and understanding how measurement variation interacts with data collection and the methods is helpful in quantifying the nature of measurement error. We illustrate how simple one- and two-sample statistical methods can be effectively used in introducing important concepts of metrology ...


Capturing Cognitive Fingerprints From Keystroke Dynamics, J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen B. Gilbert, Amed E. Kamal, Sun-Yuan Kung 2017 Iowa State University

Capturing Cognitive Fingerprints From Keystroke Dynamics, J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen B. Gilbert, Amed E. Kamal, Sun-Yuan Kung

Morris Chang

Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous. Its effectiveness has been verified through a large-scale dataset. This article ...


A Multiperiod Generalized Network Flow Model Of The U.S. Integrated Energy System: Part I—Model Description, Ana Quelhas, Esteban Gil, James D. McCalley, Sarah M. Ryan 2017 Iowa State University

A Multiperiod Generalized Network Flow Model Of The U.S. Integrated Energy System: Part I—Model Description, Ana Quelhas, Esteban Gil, James D. Mccalley, Sarah M. Ryan

James McCalley

This paper is the first of a two-part paper presenting a multiperiod generalized network flow model of the integrated energy system in the United States. Part I describes the modeling approach used to evaluate the economic efficiencies of the system-wide energy flows, from the coal and natural gas suppliers to the electric load centers. Under the proposed problem formulation, fuel supply and electricity demand nodes are connected via a transportation network, and the model is solved for the most efficient allocation of quantities and corresponding prices. The methodology includes physical, economic, and environmental aspects that characterize the different networks. Part ...


Spatial Sampling Strategies With Multiple Scientific Frames Of Reference, Paul B. Reverdy, Thomas F. Shipley, Daniel E. Koditschek 2017 University of Pennsylvania

Spatial Sampling Strategies With Multiple Scientific Frames Of Reference, Paul B. Reverdy, Thomas F. Shipley, Daniel E. Koditschek

Departmental Papers (ESE)

We study the spatial sampling strategies employed by field scientists studying aeolian processes, which are geophysical interactions between wind and terrain. As in geophysical field science in general, observations of aeolian processes are made and data gathered by carrying instruments to various locations and then deciding when and where to record a measurement. We focus on this decision-making process. Because sampling is physically laborious and time consuming, scientists often develop sampling plans in advance of deployment, i.e., employ an offline decision-making process. However, because of the unpredictable nature of field conditions, sampling strategies generally have to be updated online ...


Development Of Learning Modules For Sustainable Life Cycle Product Design: A Constructionist Approach, MD Tarique Hasan Khan, Kamyar Raoufi, Kijung Park, Tasnia Reza, Carolyn E. Psenka, Kathy Schmidt-Jackson, Karl R. Haapala, Gul E. Okudan-Kremer, Kyoung-Yun Kim 2017 Wayne State University

Development Of Learning Modules For Sustainable Life Cycle Product Design: A Constructionist Approach, Md Tarique Hasan Khan, Kamyar Raoufi, Kijung Park, Tasnia Reza, Carolyn E. Psenka, Kathy Schmidt-Jackson, Karl R. Haapala, Gul E. Okudan-Kremer, Kyoung-Yun Kim

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Constructionism is an approach to learning in which learners construct their own understanding and knowledge through making a meaningful product. A cyberlearning environment for sustainable life cycle engineering design has been developed based upon this approach through a multi-university research project funded by the NSF entitled “Constructionism in Learning: Sustainable Life Cycle Engineering (CooL:SLiCE).” The pedagogic significance of CooL:SLiCE is to better enable university students to learn about sustainable product life cycle engineering design by realizing effective learning modules for personalized environmentally-responsible product design. The CooL:SliCE platform has developed a web-based portal with three learning modules: 1 ...


Constructionism In Learning: Sustainable Life Cycle Engineering Project (Cool:Slice), Kyoung-Yun Kim, Carolyn E. Psenka, Karl R. Haapala, Kathy Schmidt-Jackson, Gul E. Okudan-Kremer 2017 Wayne State University

Constructionism In Learning: Sustainable Life Cycle Engineering Project (Cool:Slice), Kyoung-Yun Kim, Carolyn E. Psenka, Karl R. Haapala, Kathy Schmidt-Jackson, Gul E. Okudan-Kremer

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

CooL:SLiCE, a distributed cyberlearning environment to facilitate consideration of engineering design impacts on the natural environment across product life cycles has been developed at XXX University, XXX University, and XXX University. CooL:SLiCE supports a constructionist line of inquiry within design practice by providing learners with technologies and other learning resources for experimentation and collaboration. By scaffolding these resources, CooL:SLiCE enables students to attain a deeper conceptual understanding of sustainable lifecycle product design.

This poster will feature the elements of the CooL:SLiCE platform, pilot projects, and learning studies. The platform modules include 1) the Online Computer Aided ...


Designing Adaptive Instruction For Teams: A Meta-Analysis, Robert A. Sottilare, C. Shawn Burke, Eduardo Salas, Anne M. Sinatra, Joan H. Johnston, Stephen B. Gilbert 2017 United States Army Research Laboratory

Designing Adaptive Instruction For Teams: A Meta-Analysis, Robert A. Sottilare, C. Shawn Burke, Eduardo Salas, Anne M. Sinatra, Joan H. Johnston, Stephen B. Gilbert

Industrial and Manufacturing Systems Engineering Publications

The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or educational experience tailored by artificially-intelligent, computer-based tutors with the goal of optimizing learner outcomes (e.g., knowledge and skill acquisition, performance, enhanced retention, accelerated learning, or transfer of skills from instructional environments to work environments). The core contribution of this research was the identification of behavioral markers associated with the antecedents ...


The Application Of Artificial Neural Networks For Prioritization Of Independent Variables Of A Discrete Event Simulation Model In A Manufacturing Environment, Rebecca Pires dos Santos 2017 Brigham Young University

The Application Of Artificial Neural Networks For Prioritization Of Independent Variables Of A Discrete Event Simulation Model In A Manufacturing Environment, Rebecca Pires Dos Santos

Theses and Dissertations

The high complexity existent in businesses has required managers to rely on accurate and up to date information. Over the years, many tools have been created to give support to decision makers, such as discrete event simulation and artificial neural networks. Both tools have been applied to improve business performance; however, most of the time they are used separately. This research aims to interpret artificial neural network models that are applied to the data generated by a simulation model and determine which inputs have the most impact on the output of a business. This would allow prioritization of the variables ...


Measuring The Robustness Of Forensic Tools' Ability To Detect Data Hiding Techniques, Samuel Isaiah Moses 2017 Brigham Young University

Measuring The Robustness Of Forensic Tools' Ability To Detect Data Hiding Techniques, Samuel Isaiah Moses

Theses and Dissertations

The goal of this research is to create a methodology that measures the robustness and effectiveness of forensic tools' ability to detect data hiding. First, an extensive search for any existing guidelines testing against data hiding was performed. After finding none, existing guidelines and frameworks in cybersecurity and cyber forensics were reviewed. Next, I created the methodology in this thesis. This methodology includes a set of steps that a user should take to evaluate a forensic tool. The methodology has been designed to be flexible and scalable so as new anti-forensic data hiding methods are discovered and developed, they can ...


Quasi-Static And Dynamic Mismatch For Door Opening And Stair Climbing With A Legged Robot, T. Turner Topping, Gavin Kenneally, Daniel E. Koditschek 2017 University of Pennsylvania

Quasi-Static And Dynamic Mismatch For Door Opening And Stair Climbing With A Legged Robot, T. Turner Topping, Gavin Kenneally, Daniel E. Koditschek

Departmental Papers (ESE)

This paper contributes to quantifying the notion of robotic fitness by developing a set of necessary conditions that determine whether a small quadruped has the ability to open a class of doors or climb a class of stairs using only quasi-static maneuvers. After verifying that several such machines from the recent robotics literature are mismatched in this sense to the common human scale environment, we present empirical workarounds for the Minitaur quadrupedal platform that enable it to leap up, force the door handle and push through the door, as well as bound up the stairs, thereby accomplishing through dynamical maneuvers ...


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