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Reliability-Informed Life Cycle Warranty Cost And Life Cycle Analysis Of Newly Manufactured And Remanufactured Units, Meng Li, Venkat P. Nemani, Jinqiang Liu, Michael A. Lee, Navaid Ahmed, Gül E. Okudan Kremer, Chao Hu 2021 Iowa State University

Reliability-Informed Life Cycle Warranty Cost And Life Cycle Analysis Of Newly Manufactured And Remanufactured Units, Meng Li, Venkat P. Nemani, Jinqiang Liu, Michael A. Lee, Navaid Ahmed, Gül E. Okudan Kremer, Chao Hu

Industrial and Manufacturing Systems Engineering Publications

Standard life cycle techniques such as life cycle warranty cost (LCWC) analysis and life cycle analysis (LCA) are used to respectively quantify the relative economical and environmental advantages of remanufactured goods while simultaneously identifying avenues for improvement. In this paper, we contribute to the literature on life cycle studies by incorporating reliability into LCWC analysis and LCA with the goal of improving long-term/multiple life cycle decision making. We develop a branched power-law model to incorporate the physical degradation mechanisms leading to reduced reuse rates of system parts over multiple life cycles. We then follow a standard LCA protocol to ...


Comparing And Improving The Design Of Physical Activity Data Visualizations, Peter M. Frackleton 2021 University of Massachusetts Amherst

Comparing And Improving The Design Of Physical Activity Data Visualizations, Peter M. Frackleton

Masters Theses

Heart disease is a leading cause of death in the United States, and older adults are at highest risk of being diagnosed with heart disease. Consistent physical exercise is an effective means of deterring onset of heart disease, and physical activity tracking devices can inspire greater activity in older adults. However, physical activity tracking device abandonment is quite common due to limitations on what can be learned from the activity data that is collected. Better data visualization of physical data presents an opportunity to surpass these limitations. In this thesis, a task-based human subject study was performed with three different ...


Robustness Of Supply Chain Synchronization Strategies, Andrew Frere 2021 University of Massachusetts Amherst

Robustness Of Supply Chain Synchronization Strategies, Andrew Frere

Masters Theses

Modern manufacturing systems dealing with complex assemblies with large numbers of parts present particular challenges in the realm of supply chain management. Complex assemblies, such as those found in aerospace and automobile manufacturing, require thousands of parts to come together at the right time for final assembly. The large number of parts, often coming from hundreds of suppliers, combined with unreliable delivery times and high cost of many of these components can lead to incredibly high inventory costs and assembly delays. Typically, variable delays in part delivery are compensated for by either keeping a buffer of safety stock or a ...


Thin Safety Margin: The Sefor Super-Prompt-Critical Transient Experiments, Ozark Mountains, Arkansas 1970–1971, Jerry Havens, Collis Geren 2021 University of Arkansas, Fayetteville

Thin Safety Margin: The Sefor Super-Prompt-Critical Transient Experiments, Ozark Mountains, Arkansas 1970–1971, Jerry Havens, Collis Geren

Arkansas Scholarly Editions

Thin Safety Margin charts the history of SEFOR, a twenty-megawatt reactor that operated for three years in the rural Ozark Mountains of Arkansas as part of an internationally sponsored program designed to demonstrate the Doppler effect in plutonium-oxide-fueled fast reactors. Authors Jerry Havens and Collis Geren draw upon this history to assess the accidental explosion risk inherent in using fast reactors to reduce the energy industry’s carbon dioxide emissions.

If a sufficiently powerful fast-neutron explosion were to cause the containment of a reactor such as SEFOR’s to fail, the reactor’s radiotoxic plutonium fuel could vaporize and escape ...


Ergonomic Risk Assessment In Automotive Welding Lines And Comparison Of Method Output, Aynur Gürsoy Özcan 2021 Kocaeli University, Industrial Engineering

Ergonomic Risk Assessment In Automotive Welding Lines And Comparison Of Method Output, Aynur Gürsoy Özcan

Dicle University Journal of Engineering

There are many studies in the literature on ergonomic risk assessment, but there are limited studies on the Germany Federal Institute for Occupational Safety and Health (BAUA) method. The aim of this study is to examine the compatibility between Rapid Entire Body Assessment (REBA) and BAUA and the ability of the methods to correctly classify the risk level of risky tasks, and to make ergonomic improvements to reduce the physical strains. The welding processes of the automotive company were examined and ergonomic risk assessment was made by using REBA and BAUA for four tasks with the most strains. The evaluation ...


Hidden In Plain Sight: Why Sustainment Is So Critical To The Circular Supply Chains For Technical Products, Dave Peterson 2021 University of Arkansas, Fayetteville

Hidden In Plain Sight: Why Sustainment Is So Critical To The Circular Supply Chains For Technical Products, Dave Peterson

Operations Management Presentations

  • Technical products are typically complex, long-lived and high-cost equipment—such as: aircraft, vehicles, ships, capital equipment/machinery and utilities infrastructure. While many technical products are manufactured via traditional linear supply chains, their useful lives often rely upon sustainment systems incorporating significant aspects of circular supply chains. This webinar takes a closer look at technical products and the critical role of systems sustainment to achieve and fulfill circular supply chains. The key takeaways from this webinar are:
    • The Earth is running out of resources which will have a direct impact upon maintaining/improving our quality of life.
    • The circular economy philosophy ...


Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj 2021 New Jersey Institute of Technology

Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj

Dissertations

This dissertation focuses on developing new modeling and solution approaches based on multi-stage stochastic programming and reinforcement learning for tackling biological invasions in forests and human populations. Emerald Ash Borer (EAB) is the nemesis of ash trees. This research introduces a multi-stage stochastic mixed-integer programming model to assist forest agencies in managing emerald ash borer insects throughout the U.S. and maximize the public benets of preserving healthy ash trees. This work is then extended to present the first risk-averse multi-stage stochastic mixed-integer program in the invasive species management literature to account for extreme events. Significant computational achievements are obtained ...


Stochastic Programming And Agent-Based Simulation Approaches For Epidemics Control And Logistics Planning, Xuecheng Yin 2021 New Jersey Institute of Technology

Stochastic Programming And Agent-Based Simulation Approaches For Epidemics Control And Logistics Planning, Xuecheng Yin

Dissertations

This dissertation addresses the resource allocation challenges of fighting against infectious disease outbreaks. The goal of this dissertation is to formulate multi-stage stochastic programming and agent-based models to address the limitations of former literature in optimizing resource allocation for preventing and controlling epidemics and pandemics. In the first study, a multi-stage stochastic programming compartmental model is presented to integrate the uncertain disease progression and the logistics of resource allocation to control a highly contagious infectious disease. The proposed multi-stage stochastic program, which involves various disease growth scenarios, optimizes the distribution of treatment centers and resources while minimizing the total expected ...


“Surviving And Growing Up With Illegal Status”: The Analysis Of Socio–Economic Household, Potential Conflict, The Environmental Damage, And Vulnerability Of Local Community To Disaster, Sofyan Syahnur, Yossi Diantimala 2021 Universitas Syiah Kuala

“Surviving And Growing Up With Illegal Status”: The Analysis Of Socio–Economic Household, Potential Conflict, The Environmental Damage, And Vulnerability Of Local Community To Disaster, Sofyan Syahnur, Yossi Diantimala

Journal of Sustainable Mining

This study aims to analyze, from social-economics and environmental perspectives, how illegal gold mining survives and grows with its illegal status. Generally, illegal mining has a positive impact on the socio-economy of all parties involved. However, mining activities cause environmental damage and pollution so that the local community is vulnerable to disaster and potential conflict. This research was conducted at an illegal mining site in Aceh, the western province of Indonesia. To describe the primary data, it employs a descriptive qualitative method. The purposive sampling method is used to select key informants. The results show an increasing income of all ...


Critical Chain – Or Why Wedding Planners Get Ulcers, Greg Hutto 2021 University of Arkansas, Fayetteville

Critical Chain – Or Why Wedding Planners Get Ulcers, Greg Hutto

Operations Management Presentations

Planning a wedding is one of the most challenging projects in a young life… So much to do! A respected journal in the project management literature -- Southern Bride -- advises well-off young couples to escape stress and employ a professional wedding planner+. In today's webinar we will contrast two project planning methods in examining one such wedding project -- hastily planned and beset with troubles. We will shed light on the science & art of project management and possibly help our wedding planners (both professional and amateur) avoid stress-induced medical complications. In this webinar, we’ll be spending time with Greg Hutto ...


Motivation Dynamics For Autonomous Composition Of Navigation Tasks, Paul B. Reverdy, Vasileios Vasilopoulos, Daniel E. Koditschek 2021 University of Pennsylvania

Motivation Dynamics For Autonomous Composition Of Navigation Tasks, Paul B. Reverdy, Vasileios Vasilopoulos, Daniel E. Koditschek

Departmental Papers (ESE)

We physically demonstrate a reactive sensorimotor architecture for mobile robots whose behaviors are generated by motivation dynamics. Motivation dynamics uses a continuous dynamical system to reactively compose low-level control vector fields using valuation functions which capture the potentially competing influences of external stimuli relative to the system's own internal state. We show that motivation dynamics 1) naturally accommodates external stimuli through standard signal processing tools, and 2) can effectively encode a repetitive higher-level task by composing several low-level controllers to achieve a limit cycle in which the robot repeatedly navigates towards two alternatively valuable goal locations in a commensurately ...


Evaluating Decision Making In Sustainable Project Selection Between Literature And Practice, Rakan Alyamani, Suzanna Long, Mohammad Nurunnabi 2021 Missouri University of Science and Technology

Evaluating Decision Making In Sustainable Project Selection Between Literature And Practice, Rakan Alyamani, Suzanna Long, Mohammad Nurunnabi

Engineering Management and Systems Engineering Faculty Research & Creative Works

A robust project selection process is critical for the selection of sustainable projects that meet the needs of an organization or community. There are multiple factors or criteria that can be considered in the selection of the appropriate sustainable project, but it can be challenging to find sufficient depth of expert opinion to perform a strong evaluation of these criteria. Several researchers have turned to the sustainable project literature as a source of expert opinion to evaluate the criteria used in sustainable project selection and rank them based on importance using different multi-criteria decision-making (MCDM) methodologies. However, using the literature ...


Quality And Productivity Improvements In Additive Manufacturing, Huseyin Kose 2021 University of Tennessee, Knoxville

Quality And Productivity Improvements In Additive Manufacturing, Huseyin Kose

Doctoral Dissertations

Additive manufacturing (AM) is a relatively new manufacturing technology compared to the traditional manufacturing methods. Even though AM processes have many advantages, they also have a series of challenges that need to be addressed to adapt this technology for a wide range of applications and mass production.

AM faces a number of challenges, including the absence of methods/models for determining whether AM is the best manufacturing process for a given part. The first study of this thesis proposes a framework for choosing specific AM processes by considering the complexity level of a part. It has been proven that the ...


Automated Warehouse Systems: A Guideline For Future Research, Wenquan Dong 2021 University of Tennessee, Knoxville

Automated Warehouse Systems: A Guideline For Future Research, Wenquan Dong

Doctoral Dissertations

This study aims to provide a comprehensive tool for the selection, design, and operation of automated warehouse systems considering multiple automated storage and retrieval system (AS/RS) options as well as different constraints and requirements from various business scenarios.

We first model the retrieval task scheduling problem in crane-based 3D AS/RS with shuttle-based depth movement mechanisms. We prove the problem is NP-hard and find an optimality condition to facilitate the development of an efficient heuristic. The heuristic demonstrates an advantage in terms of solving time and solution quality over the genetic algorithms and the other two algorithms taken from ...


Improving Reinforcement Learning Techniques For Medical Decision Making, Matthew Baucum 2021 University of Tennessee, Knoxville

Improving Reinforcement Learning Techniques For Medical Decision Making, Matthew Baucum

Doctoral Dissertations

Reinforcement learning (RL) is a powerful tool for developing personalized treatment regimens from healthcare data. In RL, an agent samples experiences from an environment (such as a model of patient health) to learn a policy that maximizes long-term reward. This dissertation proposes methodological and practical developments in the application of RL to treatment planning problems.

First, we develop a novel time series model for simulating patient health states from observed clinical data. We use a generative neural network architecture that learns a direct mapping between distributions over clinical measurements at adjacent time points. We show that this model produces realistic ...


Optimization Of Islanded Utility-Microgrids After Natural Disasters, Rodney Kizito 2021 University of Tennessee, Knoxville

Optimization Of Islanded Utility-Microgrids After Natural Disasters, Rodney Kizito

Doctoral Dissertations

Natural disasters can cause widespread disturbances/power outages within distribution networks and hinder a utility’s ability to provide uninterrupted power supply to the critical public buildings (e.g., hospitals, grocery stores, fire, police and gas stations) within the utility’s serviced region. Backup generators, which are typically relied on during power interruptions, have limited capacities and have been reported to experience failures during usage. Microgrids, defined as localized power grids that incorporate distributed generators (DGs) and energy storage systems (ESSs) to allow them to operate independent of the main grid (i.e., island mode), can help utilities provide disaster ...


Micro Scalable Graphene Oxide Productions Using Controlled Parameters In Bench Reactor, Carolina S. Andrade, Anna Paula Godoy, Marcos Antônio Gimenes Benega, Ricardo J. E. Andrade, Rafael Cardoso Andrade, Wellington Marcos Silva, Josué Marciano de Oliveira Cremonezzi, Waldemar Augusto de Almeida Macedo, Hélio Ribeiro, Jaime Taha-Tijerina 2021 The University of Texas Rio Grande Valley

Micro Scalable Graphene Oxide Productions Using Controlled Parameters In Bench Reactor, Carolina S. Andrade, Anna Paula Godoy, Marcos Antônio Gimenes Benega, Ricardo J. E. Andrade, Rafael Cardoso Andrade, Wellington Marcos Silva, Josué Marciano De Oliveira Cremonezzi, Waldemar Augusto De Almeida Macedo, Hélio Ribeiro, Jaime Taha-Tijerina

Manufacturing & Industrial Engineering Faculty Publications and Presentations

The detailed study of graphene oxide (GO) synthesis by changing the graphite/oxidizing reagents mass ratios (mG/mROxi), provided GO nanosheets production with good yield, structural quality, and process savings. Three initial samples containing different amounts of graphite (3.0 g, 4.5 g, and 6.0 g) were produced using a bench reactor under strictly controlled conditions to guarantee the process reproducibility. The produced samples were analyzed by Raman spectroscopy, atomic force microscopy (AFM), x-ray diffraction (XDR), X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared spectroscopy (FTIR) and thermogravimetry (TGA) techniques. The results showed that the major GO product comprised of ...


Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James SINGH, Akshat KUMAR, Hoong Chuin LAU 2021 Singapore Management University

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective ...


Periodic Replenish And Recount Policy To Address Record Inaccuracy From Stock Loss, Colton K. Ku 2021 University of Tennessee, Knoxville

Periodic Replenish And Recount Policy To Address Record Inaccuracy From Stock Loss, Colton K. Ku

Masters Theses

Inventory record inaccuracy (IRI) often arises in retail environments due to unaccounted stock loss. Theft, misplacement, spoilage, and transaction errors will reduce the true inventory values without changing the inventory record. As previous inventory replenishment policies assume perfect record accuracy, increasing IRI can cause unexpected stockout events, mistimed reorders and replenishment freezes. Solutions to rectifying IRI vary from the use of improved tracking technologies to prevent it initially occurring at all to recounting programs which estimate true inventory value. Unfortunately, in retail environments, high‑tracking technology is unsuitable and continuous counting programs are too costly. To address the limitations of ...


Uht Milk: Supply Chain Based Shelf Life Assessment And Risk Mitigation, Sagar Rameshwar Padghan 2021 University of Tennessee, Knoxville

Uht Milk: Supply Chain Based Shelf Life Assessment And Risk Mitigation, Sagar Rameshwar Padghan

Masters Theses

Transportation and storage conditions in the perishable food supply chain play a vital role in product shelf life. This study focuses on UHT milk, a variant of milk that has a shelf life of up to 12 months in ideal conditions. However, poor transportation and storage practices can diminish its shelf life and result in quality losses resulting from milk spoilage. UHT milk literature focuses on chemical and physical analysis of changes in milk. There have been limited number of studies that characterize supply chain effects on the shelf life of milk and other perishable products.

This study analyzes supply ...


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