@article{kelly_wysk_harrysson_king_mcconnell_2024, title={Automatic Feature Based Inspection and Qualification for Additively Manufactured Parts with Critical Tolerances}, volume={38}, url={http://dx.doi.org/10.1504/IJMTM.2023.10059964}, DOI={10.1504/IJMTM.2023.10059964}, number={3}, journal={International Journal of Manufacturing Technology and Management}, author={Kelly, C.J. and Wysk, R.A. and Harrysson, O.A. and King, R.E. and McConnell, B.M.}, year={2024}, pages={236–264} }
 @article{fukuzawa_mcconnell_kay_thoney-barletta_warsing_2024, title={Implementing trades of the National Football League Draft on blockchain smart contracts}, volume={1}, ISSN={["2515-7841"]}, url={https://doi.org/10.1108/IJSMS-09-2023-0185}, DOI={10.1108/IJSMS-09-2023-0185}, abstractNote={PurposeDemonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.Design/methodology/approachUsing Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.FindingsThe authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.Research limitations/implicationsFurther work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.Practical implicationsCutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.Social implicationsFull-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.Originality/valueThis research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.}, journal={INTERNATIONAL JOURNAL OF SPORTS MARKETING & SPONSORSHIP}, author={Fukuzawa, Mathew B. and McConnell, Brandon M. and Kay, Michael G. and Thoney-Barletta, Kristin A. and Warsing, Donald P.}, year={2024}, month={Jan} }
 @article{nelson_werner_kay_king_mcconnell_thoney-barletta_2023, title={Two-stage stochastic programming model of US Army aviation allocation of utility helicopters to task forces}, volume={11}, ISSN={["1557-380X"]}, url={https://doi.org/10.1177/15485129231209039}, DOI={10.1177/15485129231209039}, abstractNote={US Army aviation units often organize into task forces to meet mission requirements. The manner in which they allocate assets affects their long-term capabilities to provide aviation support. We propose a model to allocate utility helicopters across geographically separated task forces to minimize the total time of flight and unsupported air movement air mission requests (AMRs) by priority level. We model the allocation problem with a two-stage stochastic program, with the first-stage problem allocating a fleet’s helicopter teams to task forces. The stochastic demand for each task force is then revealed. The second-stage US Army aviation air movement operations planning problem is modeled as a stochastic mixed integer linear program (MILP). A practical application uses the air movement operations planning heuristic to solve the second-stage problem at scale and generate an optimal stochastic solution task force allocation. This paper provides evidence for the practical use of the proposed two-stage stochastic programming model for US Army aviation asset allocation by military decision-makers. Furthermore, this research provides a novel first formulation of a stochastic programming dial-a-ride problem with multinode refuel and a sound framework for military aviation asset allocation decision-making.}, journal={JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS}, author={Nelson, Russell J. and Werner, Jack and Kay, Michael G. and King, Russell E. and McConnell, Brandon M. and Thoney-Barletta, Kristin}, year={2023}, month={Nov} }
 @article{nelson_king_mcconnell_thoney-barletta_2023, title={US Army Aviation air movement operations assignment, utilization and routing}, volume={7}, url={https://doi.org/10.1108/JDAL-11-2022-0013}, DOI={10.1108/JDAL-11-2022-0013}, abstractNote={PurposeThe purpose of this study was to create an air movement operations planning model to rapidly generate air mission request (AMR) assignment and routing courses of action (COA) in order to minimize unsupported AMRs, aircraft utilization and routing cost.Design/methodology/approachIn this paper, the US Army Aviation air movement operations planning problem is modeled as a mixed integer linear program (MILP) as an extension of the dial-a-ride problem (DARP). The paper also introduces a heuristic as an extension of a single-vehicle DARP demand insertion algorithm to generate feasible solutions in a tactically useful time period.FindingsThe MILP model generates optimal solutions for small problems (low numbers of AMRs and small helicopter fleets). The heuristic generates near-optimal feasible solutions for problems of various sizes (up to 100 AMRs and 10 helicopter team fleet size) in near real time.Research limitations/implicationsDue to the inability of the MILP to produce optimal solutions for mid- and large-sized problems, this research is limited in commenting on the heuristic solution quality beyond the numerical experimentation. Additionally, the authors make several simplifying assumptions to generalize the average performance and capabilities of aircraft throughout a flight.Originality/valueThis research is the first to solve the US Army Aviation air movement operations planning problem via a single formulation that incorporates multiple refuel nodes, minimization of unsupported demand by priority level, demand time windows, aircraft team utilization penalties, aircraft team time windows and maximum duration and passenger ride time limits.}, number={1}, journal={Journal of Defense Analytics and Logistics}, publisher={Emerald}, author={Nelson, Russell and King, Russell and McConnell, Brandon M. and Thoney-Barletta, Kristin}, year={2023}, month={Sep}, pages={2–28} }
 @article{lawrence_mittal_evangelista_mcconnell_2022, title={A Data-Centric Approach to Analyze Military Operations Leveraging National Training Center Data}, volume={5}, number={4}, journal={Journal of DoD Research and Engineering}, author={Lawrence, B. and Mittal, V. and Evangelista, P. and McConnell, B.M.}, year={2022}, month={Dec}, pages={1–9} }
 @article{nelson_t._mcconnell_2022, title={Army Aviation Air Movement Automation for the Mission Planner}, url={https://home.army.mil/rucker/index.php/download_file/view/2218/934}, journal={Aviation Digest}, publisher={Army}, author={Nelson, R.Espinoza and T. and McConnell, B.M.}, year={2022}, month={Mar} }
 @article{perera_hey_chen_morello_mcconnell_ivy_2022, title={Checklists in Healthcare: Operational Improvement of Standards using Safety Engineering-Project CHOISSE-A framework for evaluating the effects of checklists on surgical team culture}, volume={103}, ISSN={["1872-9126"]}, url={https://doi.org/10.1016/j.apergo.2022.103786}, DOI={10.1016/j.apergo.2022.103786}, abstractNote={The CHOISSE multi-stage framework for evaluating the effects of electronic checklist applications (e-checklists) on surgical team members' perception of their roles, performance, communication, and understanding of checklists is introduced via a pilot study. A prospective interventional cohort study design was piloted to assess the effectiveness of the framework and the sociotechnical effects of the e-checklist. A Delphi process was used to design the stages of the framework based on literature and expert consensus. The CHOISSE framework was applied to guide the implementation and evaluation of e-checklists on team culture for ten pilot teams across the US over a 24-week period. The pilot results revealed more engagement by surgeons than non-surgeons, and significant increases in surgeons' perception of communication and engagement during surgery with a small sample. Mixed methods analysis of the data and lessons learned were used to identify iterative improvements to the CHOISSE framework and to inform future studies.}, journal={APPLIED ERGONOMICS}, publisher={Elsevier BV}, author={Perera, Gimantha N. and Hey, Lloyd A. and Chen, Karen B. and Morello, Madeline J. and McConnell, Brandon M. and Ivy, Julie S.}, year={2022}, month={Sep} }
 @article{rogers_mcconnell_hodgson_kay_king_parlier_thoney-barletta_2021, title={A Military Logistics Network Planning System}, url={https://doi.org/10.31224/osf.io/wnvpf}, DOI={10.31224/osf.io/wnvpf}, abstractNote={This paper presents a proof of concept for a Military Logistics Network Planning System (MLNPS) to be used during mission planning to quickly identify a robust logistical footprint that can adequately sustain units deployed in an expeditionary environment. The logistical network is modeled using an efficient form of goal-seeking deterministic discrete event simulation to process supply requisitions through the logistical network. The queuing information obtained from the simulation informs capacity adjustments to the network to maximize efficiency. This process of simulation and network tuning continues interactively until an adequate and robust logistical footprint is found. During the planning stages, the MLNPS can be used to identify and mitigate logistical problems instead of waiting to react to backlogs when the military's operations would have already been affected. Designed to run as an app on the Army's enterprise resource planning (ERP) system (Global Combat Support System-Army), the MLNPS can also be used during operations to inform commanders of expected operational impacts on logistics. Contingency operation scenarios are used to demonstrate the MLNPS' capabilities.}, author={Rogers, Matthew B and McConnell, Brandon M and Hodgson, Thom J and Kay, Michael G and King, Russell E and Parlier, Greg and Thoney-Barletta, Kristin}, year={2021}, month={Nov} }
 @article{mcconnell_hodgson_kay_king_liu_parlier_thoney-barletta_wilson_2021, title={Assessing uncertainty and risk in an expeditionary military logistics network}, url={https://doi.org/10.31224/osf.io/ynx5k}, DOI={10.31224/osf.io/ynx5k}, abstractNote={Uncertainty is rampant in military expeditionary operations spanning high-intensity combat to humanitarian operations. These missions require rapid planning and decision-support tools to address the logistical challenges involved in providing support in often austere environments. The US Army’s adoption of an enterprise resource planning system provides an opportunity to develop automated decision-support tools and other analytical models designed to take advantage of newly available logistical data. This research presents a tool that runs in near-real time to assess risk while conducting capacity planning and performance analysis designed for inclusion in a suite of applications dubbed the Military Logistics Network Planning System, which previously only evaluated the mean sample path. Logistical data from combat operations during Operation Iraqi Freedom drive supply requisition forecasts for a contingency scenario in a similar geographic environment. A nonstationary queueing network model is linked with a heuristic logistics scheduling methodology to provide a stochastic framework to account for uncertainty and assess risk.}, author={McConnell, Brandon M and Hodgson, Thom J and Kay, Michael G and King, Russell E and Liu, Yunan and Parlier, Greg and Thoney-Barletta, Kristin and Wilson, James R}, year={2021}, month={Nov} }
 @article{slocum_jones_fletcher_hodgson_taheri_wilson_mcconnell_2021, title={Improving Chemotherapy Infusion Operations through the Simulation of Scheduling Heuristics: a case study}, url={https://doi.org/10.31224/osf.io/sg6qp}, DOI={10.31224/osf.io/sg6qp}, abstractNote={Over the last decade, chemotherapy treatments have dramatically shifted to outpatient services such that nearly 90% of all infusions are now administered outpatient. This shift has challenged oncology clinics to make chemotherapy treatment as widely available as possible while attempting to treat all patients within a fixed period of time. Historical data from a Veterans Affairs chemotherapy clinic in the United States and staff input informed a discrete event simulation model of the clinic. The case study examines the impact of altering the current schedule, where all patients arrive at 8:00 AM, to a schedule that assigns patients to two or three different appointment times based on the expected length of their chemotherapy infusion. The results identify multiple scheduling policies that could be easily implemented with the best solutions reducing both average patient waiting time and average nurse overtime requirements.}, author={Slocum, Ryan F and Jones, Herbert Lee and Fletcher, Matthew T and Hodgson, Thom J and Taheri, Javad and Wilson, James R and McConnell, Brandon M}, year={2021}, month={Nov} }
 @article{kearby_winz_mcconnell_hodgson_kay_king_2021, title={Modeling and transportation planning for US noncombatant evacuation operations in South Korea}, url={https://doi.org/10.31224/osf.io/fxvqg}, DOI={10.31224/osf.io/fxvqg}, abstractNote={Purpose: The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions. Design/methodology/approach: It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO. Findings: This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment. Originality/value: The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.}, author={Kearby, John A and Winz, Ryan D and McConnell, Brandon M and Hodgson, Thom J and Kay, Michael G and King, Russell E}, year={2021}, month={Nov} }
 @article{mcdermott_winz_hodgson_kay_king_mcconnell_2021, title={Performance tradeoffs for spare parts supply chains with additive manufacturing capability servicing intermittent demand}, volume={ahead-of-print}, url={https://doi.org/10.1108/JDAL-08-2020-0016}, DOI={10.1108/JDAL-08-2020-0016}, abstractNote={PurposeThe study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.Design/methodology/approachThis work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.FindingsThis research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.Research limitations/implicationsThis research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.Originality/valueThis research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.}, number={ahead-of-print}, journal={Journal of Defense Analytics and Logistics}, publisher={Emerald}, author={McDermott, Kyle C. and Winz, Ryan D. and Hodgson, Thom J. and Kay, Michael G. and King, Russell E. and McConnell, Brandon M.}, year={2021}, month={Dec}, pages={179–213} }
 @article{mcdermott_winz_hodgson_kay_king_mcconnell_2021, title={Performance tradeoffs for spare parts supply chains with additive manufacturing capability servicing intermittent demand}, url={https://doi.org/10.31224/osf.io/bdq23}, DOI={10.31224/osf.io/bdq23}, abstractNote={Purpose - Investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns. Design/Methodology/Approach - This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network. Findings - This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance. Research limitations/implications - This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity, and post-processing requirements. Originality/value - This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.}, author={McDermott, Kyle C and Winz, Ryan D and Hodgson, Thom J and Kay, Michael G and King, Russell E and McConnell, Brandon M}, year={2021}, month={Nov} }
 @article{slocum_jones_fletcher_mcconnell_hodgson_taheri_wilson_2020, title={Improving chemotherapy infusion operations through the simulation of scheduling heuristics: a case study}, volume={2}, ISSN={2047-6965 2047-6973}, url={http://dx.doi.org/10.1080/20476965.2019.1709908}, DOI={10.1080/20476965.2019.1709908}, abstractNote={ABSTRACT Over the last decade, chemotherapy treatments have dramatically shifted to outpatient services such that nearly 90% of all infusions are now administered outpatient. This shift has challenged oncology clinics to make chemotherapy treatment as widely available as possible while attempting to treat all patients within a fixed period of time. Historical data from a Veterans Affairs chemotherapy clinic in the United States and staff input informed a discrete event simulation model of the clinic. The case study examines the impact of altering the current schedule, where all patients arrive at 8:00 AM, to a schedule that assigns patients to two or three different appointment times based on the expected length of their chemotherapy infusion. The results identify multiple scheduling policies that could be easily implemented with the best solutions reducing both average patient waiting time and average nurse overtime requirements.}, journal={Health Systems}, publisher={Informa UK Limited}, author={Slocum, Ryan F. and Jones, Herbert L. and Fletcher, Matthew T. and McConnell, Brandon M. and Hodgson, Thom J. and Taheri, Javad and Wilson, James R.}, year={2020}, month={Feb}, pages={1–16} }
 @article{kearby_winz_hodgson_kay_king_mcconnell_2020, title={Modeling and transportation planning for US noncombatant evacuation operations in South Korea}, volume={4}, ISSN={2399-6439 2399-6439}, url={http://dx.doi.org/10.1108/JDAL-05-2019-0010}, DOI={10.1108/JDAL-05-2019-0010}, abstractNote={
Purpose
The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions.


Design/methodology/approach
It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO.


Findings
This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment.


Originality/value
The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.
}, number={1}, journal={Journal of Defense Analytics and Logistics}, publisher={Emerald}, author={Kearby, John A. and Winz, Ryan D. and Hodgson, Thom J. and Kay, Michael G. and King, Russell E. and McConnell, Brandon M.}, year={2020}, month={Feb}, pages={41–69} }
 @article{mcconnell_hodgson_kay_king_liu_parlier_thoney-barletta_wilson_2019, title={Assessing uncertainty and risk in an expeditionary military logistics network}, volume={7}, ISSN={1548-5129 1557-380X}, url={http://dx.doi.org/10.1177/1548512919860595}, DOI={10.1177/1548512919860595}, abstractNote={Uncertainty is rampant in military expeditionary operations spanning high-intensity combat to humanitarian operations. These missions require rapid planning and decision-support tools to address the logistical challenges involved in providing support in often austere environments. The US Army’s adoption of an enterprise resource planning system provides an opportunity to develop automated decision-support tools and other analytical models designed to take advantage of newly available logistical data. This research presents a tool that runs in near-real time to assess risk while conducting capacity planning and performance analysis designed for inclusion in a suite of applications dubbed the Military Logistics Network Planning System, which previously only evaluated the mean sample path. Logistical data from combat operations during Operation Iraqi Freedom drive supply requisition forecasts for a contingency scenario in a similar geographic environment. A nonstationary queueing network model is linked with a heuristic logistics scheduling methodology to provide a stochastic framework to account for uncertainty and assess risk.}, number={2}, journal={The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology}, publisher={SAGE Publications}, author={McConnell, Brandon M and Hodgson, Thom J and Kay, Michael G and King, Russell E and Liu, Yunan and Parlier, Greg H and Thoney-Barletta, Kristin and Wilson, James R}, year={2019}, month={Jul}, pages={154851291986059} }
 @article{schwartz_mcconnell_parlier_2019, title={How Data Analytics Will Improve Logistics Planning}, volume={51}, url={https://www.army.mil/article/223842/how_data_analytics_will_improve_logistics_planning}, number={3}, journal={Army Sustainment}, author={Schwartz, B. and McConnell, B.M. and Parlier, G.H.Jul–Sep}, year={2019}, pages={54–57} }
 @article{rogers_mcconnell_hodgson_kay_king_parlier_thoney barletta_2018, title={A Military Logistics Network Planning System}, volume={23}, url={http://www.lib.ncsu.edu/resolver/1840.20/36268}, DOI={10.5711/1082598323405}, number={4}, journal={Military Operations Research}, author={Rogers, Matthew B. and McConnell, Brandon M. and Hodgson, Thom J. and Kay, Michael G. and King, Russell E. and Parlier, Greg and Thoney Barletta, Kristen}, year={2018}, pages={5–24} }
 @inproceedings{moore_mcconnell_wilson_2018, title={Simulation-based Evaluation On Integrating Additive Manufacturing Capability In A Deployed Military Environment}, url={http://www.lib.ncsu.edu/resolver/1840.20/36302}, DOI={10.1109/wsc.2018.8632474}, abstractNote={This article develops a data-driven forecast of repair parts for the M109A6 Paladin self-propelled 155 mm howitzer, and this forecast drives a discrete-event simulation to assess requirements for Additive Manufacturing (AM) to be a feasible part of the U.S. Army’s expeditionary supply chain. Actual part demand from the initial invasion of Iraq in 2003 during Operation Iraqi Freedom (OIF) feeds a sample-path-based forecasting method to obtain part demand for each scenario. A simulation of a conceptualized deployed Army 3D-printing facility integrated into the supply chain evaluates the performance and feasibility of the different operational policies. Results indicate current technology could support one battery (or smaller unit) for parts below 100 cubic inches while keeping performance comparable with OIF. These results are incorporated in realistic recommendations for how the Army can potentially improve its supply chain practices with this progressive technology.}, note={annote: Moore, T. A., McConnell, B. M., & Wilson, J. R. (2018). Simulation-based Evaluation On Integrating Additive Manufacturing Capability In A Deployed Military Environment. Proceedings of the 2018 Winter Simulation Conference, 3721–3729.}, booktitle={Proceedings of the 2018 Winter Simulation Conference}, publisher={IEEE}, author={Moore, T.A. and McConnell, B.M. and Wilson, J.R.}, year={2018}, pages={3721–3729} }
 @inproceedings{seminelli_wilson_mcconnell_2017, title={Implementing discrete event simulation to improve optometry clinic operations}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85014203113&partnerID=MN8TOARS}, DOI={10.1109/WSC.2016.7822258}, abstractNote={As the tempo of military operations slows, Army Medical Facilities are faced with a need to improve the efficiency of their clinics to provide timely service to the growing population of Soldiers who are spending more time at home station. Discrete event simulation was used to examine six scheduling and staffing policies for the Womack Army Medical Center's Optometry Clinic with a goal of increasing the daily patient throughput of the clinic with consideration to patient waiting times. The best policy increased clinic throughput by eight patients a day, generating an additional $314,000 in Relative Value Units (RVUs) annually, while only increasing patient wait times by 26%. As a minimum, increasing the walk-in provider's scheduled patient load by two enables the provider to optimally treat both scheduled and walk-in patients, with a $94,000 annual RVU increase. Implementation of these results will improve clinic performance, revenue, and increase Soldiers' access to care.}, booktitle={Proceedings - Winter Simulation Conference}, author={Seminelli, M.D. and Wilson, J.W. and McConnell, Brandon M.}, year={2017}, pages={2157–2168} }