scholarly journals Data Analytics and Its Advantages for Addressing the Complexity of Healthcare: A Simulated Zika Case Study Example

2019 ◽  
Vol 9 (11) ◽  
pp. 2208 ◽  
Author(s):  
Lily Popova Zhuhadar ◽  
Evelyn Thrasher
Keyword(s):  
Discrete Event Simulation ◽  
Data Analytics ◽  
Business Models ◽  
Discrete Event ◽  
Simulation Models ◽  
Resource Planning ◽  
The United States ◽  
Wait Times ◽  
Event Simulation ◽  
Use Of Data

The need to control rising costs in healthcare has led to an increase in the use of data analytics to develop more efficient healthcare business models. This article discusses a simulation that uses data analytics to minimize the number of physicians and nurses needed in healthcare facilities during a crisis situation. Using a hypothetical emergency scenario, the hospital uses a healthcare analytical system to predict the necessary resources to govern the situation. Based on historical data regarding the flow of patients through the facility, a discrete-event simulation estimates resource scheduling and the resulting impact on both wait times and personnel demand. Furthermore, the value of multiple replications for discrete-event simulation models is discussed and defined, along with factors that enable greater control of multiple design points with this simulated experiment. The results of this study demonstrate the value of simulation modeling in effective resource planning. The addition of only a single doctor significantly reduced predicted wait times for patients during the crisis. Further, the findings support the use of data analytics and predictive modeling to mitigate rising healthcare costs in the United States through efficient planning and resource allocation.

scholarly journals Supporting scale-up of COVID-19 RT-PCR testing processes with discrete event simulation

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255214
Author(s):  
Jad El Hage ◽  
Patti Gravitt ◽  
Jacques Ravel ◽  
Nadia Lahrichi ◽  
Erica Gralla
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Scale Up ◽  
Simulation Models ◽  
The United States ◽  
Molecular Testing ◽  
Rt Pcr ◽  
Event Simulation ◽  
Trade Offs ◽  
The Impact

Testing is critical to mitigating the COVID-19 pandemic, but testing capacity has fallen short of the need in the United States and elsewhere, and long wait times have impeded rapid isolation of cases. Operational challenges such as supply problems and personnel shortages have led to these bottlenecks and inhibited the scale-up of testing to needed levels. This paper uses operational simulations to facilitate rapid scale-up of testing capacity during this public health emergency. Specifically, discrete event simulation models were developed to represent the RT-PCR testing process in a large University of Maryland testing center, which retrofitted high-throughput molecular testing capacity to meet pandemic demands in a partnership with the State of Maryland. The simulation models support analyses that identify process steps which create bottlenecks, and evaluate “what-if” scenarios for process changes that could expand testing capacity. This enables virtual experimentation to understand the trade-offs associated with different interventions that increase testing capacity, allowing the identification of solutions that have high leverage at a feasible and acceptable cost. For example, using a virucidal collection medium which enables safe discarding of swabs at the point of collection removed a time-consuming “deswabbing” step (a primary bottleneck in this laboratory) and nearly doubled the testing capacity. The models are also used to estimate the impact of demand variability on laboratory performance and the minimum equipment and personnel required to meet various target capacities, assisting in scale-up for any laboratories following the same process steps. In sum, the results demonstrate that by using simulation modeling of the operations of SARS-CoV-2 RT-PCR testing, preparedness planners are able to identify high-leverage process changes to increase testing capacity.

Discrete Event Simulation: An Efficient Tool to Assist Shipyard Investment and Production Planning

2004 ◽  
Vol 20 (03) ◽  
pp. 176-182
Author(s):  
Matthias Krause ◽  
Frank Roland ◽  
Dirk Steinhauer ◽  
Maximilian Heinemann
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Object Oriented ◽  
Simulation Models ◽  
Resource Planning ◽  
Simulation Tool ◽  
Production Flow ◽  
Holistic Model ◽  
Event Simulation ◽  
Tool Set

The complexity both of the product ship and the shipbuilding process make planning tasks in long, medium, and short terms difficult and lead to serious uncertainties. Discrete event simulation can be used to test and evaluate different scenarios in investment planning, scheduling, and resource planning. Using a virtual shipyard environment, the cost to find optimum solutions and the risk related to wrong decisions in the real world can be drastically reduced. However, due to the special skills and efforts usually needed to develop simulation models, the practical application of production flow simulation in shipyards is still rather limited. Object-oriented simulation tool sets specially developed for shipbuilding needs provide the chance to drastically reduce these efforts. Object libraries containing general and shipbuilding specific components with defined interfaces shorten the time needed for development of models for similar purposes. Furthermore, the integration of discrete event simulation models for certain shipyard facilities into a holistic model of the entire enterprise is made possible by using a tool set. Because of costs, some shipyards shy away from investing in simulation techniques. Networking activities and joint projects on simulation issues help to overcome those obstacles. German Flensburger Schiffbaugesellschaft already uses a simulation tool set successfully and actively cooperates with universities and other shipyards, while Center of Maritime Technologies has gathered experience in this field during participation in several simulation projects with other shipyards, for example, Jos. L. Meyer and Aker Ostsee. The article revues practical applications of simulation, gives an impression of how object-oriented simulation tool libraries can be structured, and outlines collaboration possibilities for making simulation applications affordable.

scholarly journals Evaluation of Simulation-Based Optimization in Grafting Labor Allocation

2018 ◽  
Vol 34 (3) ◽  
pp. 479-489 ◽  
Author(s):  
Sara Masoud ◽  
Young-Jun Son ◽  
Chieri Kubota ◽  
Russell Tronstad
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
Resource Planning ◽  
Labor Management ◽  
Labor Allocation ◽  
Event Simulation ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Optimal Resource

Abstract.Vegetable grafting is a labor-intensive operation with many management decisions. Labor management and resource planning are critical allocations in grafting nurseries, yet optimization is challenging due to the dynamic nature of workers’ performance in vegetable seedling propagation. To this end, we developed a simulation-based optimization framework for labor management to optimize labor allocation. This approach was evaluated by comparing its result with those suggested by selected domain experts (a plant scientist and a nursery manager). Furthermore, the simulation models were validated with a dataset from a developing tomato grafting company. Simulation-based optimization is demonstrated as an effective approach to find the optimal/near optimal labor allocation for horticultural nurseries, where discrete event simulation is used to represent the dynamics of the grafting work environment and meta-heuristics are used to devise optimal/ near optimal resource allocation strategies. Results reveal that a potential annual savings between $2,510 (0.6%) and $97,388 (20%) can be achieved for a grafting facility of 6 million plants per year. Keywords: Simulation-based optimization, Grafting, Labor allocation, Discrete event simulation.

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 Evaluation of a proposed optimization method for discrete-event simulation models

2012 ◽  
Vol 32 (3) ◽  
pp. 543-560 ◽  
Author(s):  
Alexandre Ferreira de Pinho ◽  
José Arnaldo Barra Montevechi ◽  
Fernando Augusto Silva Marins ◽  
Rafael Florêncio da Silva Costa ◽  
Rafael de Carvalho Miranda ◽  
...  
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
Optimization Method ◽  
Event Simulation

scholarly journals Discrete-Event Simulation of the Establishment of a Bare Beachhead for Long-Term Joint Logistics over the Shore (JLOTS) Operations

2017 ◽  
Vol 5 (2) ◽  
pp. 123-128
Author(s):  
Marqus Burrell ◽  
Jeffrey Demarest ◽  
Sarah LaRue ◽  
Angelo Martinez ◽  
Wilson Meyer
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
The United States ◽  
Operational Conditions ◽  
Freedom Of Movement ◽  
Event Simulation ◽  
Early Entry ◽  
Sea Transportation ◽  
Development Center

The United States military uses Joint Logistics Over-the-Shore (JLOTS) operations to move soldiers, vehicles, and equipment across the globe for military and humanitarian missions. These logistics operations can only be accomplished through cooperation between commanders in all services.  The U.S. Army Engineer Research and Development Center is developing a tool to analyze a set of early entry alternatives to optimize mission effectives and efficiencies in order to facilitate assured mobility and freedom of movement. This program is currently being developed under the name Planning Logistics Analysis Network System (PLANS). PLANS comprehensively covers air, land, and sea transportation infrastructure, regions of avoidance, and more. This research addresses a gap in strategic and operational planning by modeling the establishment of JLOTS operations on bare beach environments. The West Point developed discrete event simulation will determine the amount of time it takes to prepare a beach to sustain JLOTS operations under varying environmental and operational conditions.

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