scholarly journals Modeling and Analysis of the Rotor Blade Refurbishment Process at the Corpus Christi Army Depot

2015 ◽  
Vol 3 (2) ◽  
pp. 124-130
Author(s):  
Nathanial Green ◽  
David Jaye ◽  
Stephen Kerns ◽  
Gene Lesinski
Keyword(s):  
Rotor Blade ◽  
Performance Metrics ◽  
Discrete Event ◽  
Rotor Blades ◽  
Modeling And Analysis ◽  
Corpus Christi ◽  
Event Simulation ◽  
The Impact ◽  
Budget Reductions ◽  
Rotary Wing

Much of the Army’s equipment is coming to the end of its planned life cycle.  At the same time, the Department of Defense and the Army are facing severe budget reductions for the foreseeable future.  As a result, the planned modernization and acquisition of new equipment will be delayed.  The Army is now forced to keep and maintain current equipment as opposed to retiring old systems and buying new ones.  With the increased investment in the current systems, the organizations and depots that maintain and refurbish the Army’s equipment are becoming increasingly valuable assets.  Corpus Christi Army Depot (CCAD) is the Army’s only facility for repair and overhaul of rotary wing aircraft.  CCAD receives approximately 10 rotor blades per day for the Black Hawk helicopter.  Each blade is routed through a detailed inspection and rework process consisting of approximately 67 sequential operations which take approximately 45 days per blade.  Recently CCAD has expanded and reorganized the rotor blade refurbishment facility which provides an opportunity to re-examine processes, adjust positioning of work stations, and improve efficiency.  In this research we develop a discrete-event simulation model of the CCAD rotor blade refurbishment process in order to identify inefficiencies and examine “what if” scenarios to improve key performance metrics.  The key performance metrics used to analyze model input include throughput, work in progress, mean queue time, mean queue size, and workstation utilization.  The baseline model revealed that there were two crucial bottlenecks that severely limited the throughput and overall performance of the refurbishment process.  Adjusting the capacities of these workstations was very effective in reducing the number of blades in WIP and reducing the impact of the queues in front of these stations, but failed to increase the throughput to the desired amount.  Additionally, we found that the loss of one whirl tower’s production would not be a significant factor for CCAD’s performance in terms of throughput since operating with only one whirl tower did not significantly impact metrics of interest for the process.

scholarly journals Simulation Modeling and Analysis of a Door Industry

2021 ◽  
Vol 12 (1) ◽  
pp. 43-57
Author(s):  
Konstantinos Chronis ◽  
Alexandros Xanthopoulos ◽  
Dimitrios E. Koulouriotis
Keyword(s):  
Simulation Model ◽  
Performance Metrics ◽  
Discrete Event ◽  
Labor Cost ◽  
Total Production ◽  
Labor Costs ◽  
Daily Production ◽  
Modeling And Analysis ◽  
Event Simulation ◽  
Planning Decision

Ιn this paper, the authors study the production line of a door industry. The first stage of this research consists of the detailed documentation with flow charts and systematization of all production processes, all product types, as well as all stages of production and equipment. The standard production times were calculated for each workstation, together with the relevant workforce requirements. In the second stage of this research, a discrete event simulation model of the factory was developed to assist in the production planning decision-making. The simulation model was verified using actual production data relating to 19 customer orders for a total of 1,281 doors. Four simulation experiments were executed, where the effect of alternative shifts on the manufacturing line's efficiency was investigated. The performance metrics of total production, mean daily production, and mean labor cost per product were considered. This experimental trial resulted in the identification of the shift configuration that achieves increased productivity while maintaining relatively low labor costs.

scholarly journals High-Fidelity Finite Element Modeling and Analysis of Adaptive Gas Turbine Stator-Rotor Flow Interaction at Off-Design Conditions

2020 ◽  
Vol 36 (5) ◽  
pp. 595-606 ◽  
Author(s):  
Nikita Kozak ◽  
Fei Xu ◽  
Manoj R. Rajanna ◽  
Luis Bravo ◽  
Muthuvel Murugan ◽  
...  
Keyword(s):  
Finite Element ◽  
Gas Turbine ◽  
Rotor Blade ◽  
Large Scale ◽  
Turbine Blades ◽  
Engine Performance ◽  
Rotor Blades ◽  
Efficiency Gain ◽  
Modeling And Analysis ◽  
The Impact

ABSTRACTThe objective of this work is to computationally investigate the impact of an incidence-tolerant rotor blade concept on gas turbine engine performance under off-design conditions. When a gas turbine operates at an off-design condition such as hover flight or takeoff, large-scale flow separation can occur around turbine blades, which causes performance degradation, excessive noise, and critical loss of operability. To alleviate this shortcoming, a novel concept which articulates the rotating turbine blades simultaneous with the stator vanes is explored. We use a finite-element-based moving-domain computational fluid dynamics (CFD) framework to model a single high-pressure turbine stage. The rotor speeds investigated range from 100% down to 50% of the designed condition of 44,700 rpm. This study explores the limits of rotor blade articulation angles and determines the maximal performance benefits in terms of turbine output power and adiabatic efficiency. The results show articulating rotor blades can achieve an efficiency gain of 10% at off-design conditions thereby providing critical leap-ahead design capabilities for the U.S. Army Future Vertical Lift (FVL) program.

scholarly journals Simulation modeling and analysis of primary health center operations

SIMULATION ◽  
2021 ◽  
pp. 003754972110309
Author(s):  
Mohd Shoaib ◽  
Varun Ramamohan
Keyword(s):  
Resource Utilization ◽  
Waiting Times ◽  
Discrete Event ◽  
Simulation Models ◽  
Modeling And Analysis ◽  
Healthcare Facilities ◽  
Event Simulation ◽  
Analytical Approximations ◽  
Primary Health ◽  
Generic Modeling

We present discrete-event simulation models of the operations of primary health centers (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modeling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilization values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilization. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilization of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilization of a server in a queueing system with characteristics similar to the PHC doctor/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyze public health operations in India and can provide researchers in other settings with hierarchical health systems, a template for the development of simulation models of their primary healthcare facilities.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

scholarly journals Assessing asset monitoring levels for maintenance operations

2015 ◽  
Vol 26 (5) ◽  
pp. 632-659 ◽  
Author(s):  
Abdullah A Alabdulkarim ◽  
Peter Ball ◽  
Ashutosh Tiwari
Keyword(s):  
Asset Management ◽  
Business Models ◽  
Discrete Event ◽  
Dynamic Modelling ◽  
Simulation Models ◽  
Content Type ◽  
Event Simulation ◽  
Product Service ◽  
Asset Monitoring ◽  
The Impact

Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

scholarly journals The contribution of reduced COVID-19 test time in controlling the spread of the disease: A simulation-based approach

2022 ◽  
Vol 12 (2) ◽  
Author(s):  
Youness Frichi ◽  
Abderrahmane Ben Kacem ◽  
Fouad Jawab ◽  
Said Boutahari ◽  
Oualid Kamach ◽  
...  
Keyword(s):  
Discrete Event ◽  
Mass Scale ◽  
Test Time ◽  
Test Duration ◽  
Accurate Identification ◽  
Event Simulation ◽  
Simulation Results ◽  
Precautionary Measures ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus COVID-19 has known a large spread over the globe threatening human health. Recommendations from WHO and specialists insist on testing on a mass scale. However, health systems do not have enough resources. The current process requires the isolation of testees in the hospitals’ isolation rooms for several hours until the test results are revealed, limiting hospitals’ capacities to test large numbers of cases. The aim of this paper was to estimate the impact of reducing the COVID-19 test time on controlling the pandemic spread, through increasing hospitals’ capacities to test on a mass scale. First, a discrete-event simulation was used to model and simulate the COVID-19 testing process in Morocco. Second, a mathematical model was developed to demonstrate the effect of accurate identification of infected cases on controlling the disease’s spread. Simulation results showed that hospitals’ testing capacities could be increased six times if the test duration fell from 10 hours to 10 minutes. The reduction of test time would increase testing capacities, which help to identify all the infected cases. In contrast, the simulation results indicated that if the infected population is not accurately identified and no precautionary measures are taken, the virus will continue to spread until it reaches the total population. Reducing test time is a vital component of the response to the COVID-19 pandemic. It is essential for the effective implementation of policies to contain the virus.

Improving outpatient phlebotomy service efficiency and patient experience using discrete-event simulation

2016 ◽  
Vol 29 (7) ◽  
pp. 733-743 ◽  
Author(s):  
Kenneth Yip ◽  
Suk-King Pang ◽  
Kui-Tim Chan ◽  
Chi-Kuen Chan ◽  
Tsz-Leung Lee
Keyword(s):  
Discrete Event Simulation ◽  
Scenario Analysis ◽  
Performance Metrics ◽  
Discrete Event ◽  
Evidence Based ◽  
Content Type ◽  
Event Simulation ◽  
Service Efficiency ◽  
Related Service ◽  
The Relationship

Purpose – The purpose of this paper is to present a simulation modeling application to reconfigure the outpatient phlebotomy service of an acute regional and teaching hospital in Hong Kong, with an aim to improve service efficiency, shorten patient queuing time and enhance workforce utilization. Design/methodology/approach – The system was modeled as an inhomogeneous Poisson process and a discrete-event simulation model was developed to simulate the current setting, and to evaluate how various performance metrics would change if switched from a decentralized to a centralized model. Variations were then made to the model to test different workforce arrangements for the centralized service, so that managers could decide on the service’s final configuration via an evidence-based and data-driven approach. Findings – This paper provides empirical insights about the relationship between staffing arrangement and system performance via a detailed scenario analysis. One particular staffing scenario was chosen by manages as it was considered to strike the best balance between performance and workforce scheduled. The resulting centralized phlebotomy service was successfully commissioned. Practical implications – This paper demonstrates how analytics could be used for operational planning at the hospital level. The authors show that a transparent and evidence-based scenario analysis, made available through analytics and simulation, greatly facilitates management and clinical stakeholders to arrive at the ideal service configuration. Originality/value – The authors provide a robust method in evaluating the relationship between workforce investment, queuing reduction and workforce utilization, which is crucial for managers when deciding the delivery model for any outpatient-related service.

Abstract 2524: Increasing the Proportion of Patients Treated with Stroke Thrombolysis: Reducing In-hospital Delays has Substantially More Impact than Extension of the Time Window

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Martin A James ◽  
Thomas Monks ◽  
Ken Stein ◽  
Martin Pitt
Keyword(s):  
Time Window ◽  
Discrete Event ◽  
Fold Increase ◽  
Service Improvement ◽  
Disability Benefit ◽  
Prospective Data ◽  
Stroke Service ◽  
Event Simulation ◽  
Simulation Based ◽  
The Impact

Background Pooled analyses show the benefit of IV alteplase for ischemic stroke up to 4·5 hours after onset, and expert guidelines have been updated to reflect this. However, the benefit from thrombolysis is critically time-dependent, and the additional benefit from extending the time window may be jeopardised by in-hospital delays. Methods We developed a discrete-event simulation based on prospective data from 1142 acute stroke patients arriving at our large district hospital over a two-year period to April 2011, modelling the time spent in the ED for triage and assessment, brain imaging and, if applicable, thrombolysis. Outputs from the model included arrival to treatment times (ATT), percentage of strokes thrombolysed, and the number of thrombolysed patients with a 90 day modified Rankin Scale (mRS) of 0-1. We sought to model the current stroke pathway (treatment <3 hours of onset), and compare it with developmental scenarios exploring the impact of extending treatment from 3 to 4.5 hours, of ED staff alerting the stroke service at triage, of ambulance pre-alert to the stroke service, and combinations of these measures. Results The model illustrates that extending the treatment window modestly increases the percentage of acute strokes thrombolysed, from 5% to 6% (95% CI 5.8-6.1%), and increases the number of thrombolysed patients with mRS 0-1 by 7 per year (95% CI 5.9-8.0). Both the triage alert and ambulance pre-alert scenarios increase thrombolysis rates to 15% (95% CI 14.9% to 15.7%); but the ambulance pre-alert reduces ATT by a mean of 27 mins (95% CI 26.3-28.4) compared to the triage alert scenario. The ambulance pre-alert scenario increases the number of thrombolysed patients with mRS 0-1 by 35/year (95% CI 32.9-37.7) compared to 22 (95% CI 20.4-23.5) in the triage alert scenario. Combining the treatment extension with either alerting measure does not increase the thrombolysis rate further (15%, 95% CI 14.7-15.1%). Sensitivity analysis illustrates that the pre-alert system is the least vulnerable to a drop in compliance rates. Conclusions Our simulation model shows that the greatest disability benefit accrues from measures to substantially reduce in-hospital delays to alteplase treatment - a potential three-fold increase in the proportion of patients treated. Compared to extending the time window for alteplase from 3 to 4.5 hours, eradicating in-hospital delays to treatment offers a five-fold greater disability benefit, and this should be the pre-eminent focus of service improvement for all emergency receiving hospitals.

Reducing Handoffs and Improving Patient Flow in the ED

2021 ◽  
Author(s):  
Vishnunarayan Girishan Prabhu ◽  
Kevin Taaffe ◽  
Ronald Pirrallo ◽  
William Jackson ◽  
Michael Ramsay
Keyword(s):  
Performance Metrics ◽  
Patient Flow ◽  
Discrete Event ◽  
Common Source ◽  
Agent Based ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Healthcare Settings ◽  
Shift Schedules ◽  
Hybrid Agent

Abstract Over 145 million people visit US Emergency Departments annually. The diverse nature and overwhelming volume of patient visits make the ED one of the most complicated healthcare settings. In particular, handoffs, the transfer of patient care from one physician to another during shift transition are a common source of errors resulting from workflow interruptions and high cognitive workload. This research focuses on developing a hybrid agent-based discrete event simulation model to identify physician shifts that minimize handoffs without affecting other performance metrics. By providing overlapping shift schedules as well as implementing policies that restrict physicians from signing up a new patient during the last hour of the shift, we observed that handoffs and patient time in the emergency department could be reduced by as much as 42% and 17%, respectively.

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