Capacity planning and performance predictions: modelling the European network to determine tomorrow's needs today [air traffic]

2003 ◽  
Author(s):  
A. Marsden
Keyword(s):  
Capacity Planning ◽  
Air Traffic ◽  
European Network ◽  
Performance Predictions ◽  
And Performance

Stress Management and Air Traffic Control Trainees: Development and Evaluation of a New Training Course

2020 ◽  
Vol 64 (1) ◽  
pp. 1155-1159
Author(s):  
Jamie D. Barrett ◽  
Brett Torrence ◽  
Michelle Bryant ◽  
Linda Pierce ◽  
Julia Buck
Keyword(s):  
Stress Management ◽  
Traffic Control ◽  
Management Training ◽  
Federal Aviation Administration ◽  
Air Traffic ◽  
Medical Institute ◽  
Stress Management Training ◽  
Air Traffic Controllers ◽  
Aerospace Medical ◽  
And Performance

The primary mission of the Federal Aviation Administration (FAA) is to maintain the safety of the National Airspace System (NAS). As part of this mission, the FAA is tasked with ensuring that future air traffic controllers are adequately trained to perform the high-risk job of directing air traffic. The FAA Academy curriculum for newly hired controllers involves 3-4 months of intensive lessons and performance assessments. It has been suggested that this training program is quite stressful, and successful trainees tend to be those who can better manage stress. To support ATC trainees, researchers at the Civil Aerospace Medical Institute (CAMI) have conducted operational research to develop and evaluate a stress management training to help trainees manage their stress during training at the FAA Academy.

Capacity Planning for Cluster Tools of Wafer Fabrication Plant

2010 ◽  
Vol 450 ◽  
pp. 365-368
Author(s):  
James C. Chen ◽  
Chia Wen Chen ◽  
Kou Huang Chen ◽  
Chien Hsin Lin
Keyword(s):  
Capacity Planning ◽  
Production Costs ◽  
Wafer Fabrication ◽  
Total Production ◽  
Output Rate ◽  
Cluster Tools ◽  
And Performance ◽  
Using Data ◽  
Capital Intensive

Wafer fabrication is a capital intensive industry. A 12-inch wafer fabrication plant needs a typical investment of US$ 3 billion, and the equipment cost constitutes about two-thirds to three-quarters of the total production costs. Therefore, capacity planning is crucial to the investment and performance of wafer fabrication plants. Several formulae are presented to calculate the required number of machines with sequential, parallel, and batch processing characteristics, respectively. An AutoSched AP simulation model using data from real foundry fabrication plants is used in a case study to evaluate the performance of the proposed formulae. Simulation results indicate that the proposed formulae can quickly and accurately calculate the required number of cluster tools leading to the required monthly output rate.

Understanding aviation operators’ variability in advanced systems

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maria Papanikou ◽  
Utku Kale ◽  
András Nagy ◽  
Konstantinos Stamoulis
Keyword(s):  
Human Performance ◽  
Situational Awareness ◽  
Air Traffic ◽  
Content Type ◽  
Homogeneous Groups ◽  
Professional Groups ◽  
Performance Shaping Factors ◽  
Generational Changes ◽  
And Performance ◽  
Practical Implications

Purpose This study aims to identify variability in aviation operators in order to gain greater understanding of the changes in aviation professional groups. Research has commonly addressed human factors and automation in broad categories according to a group’s function (e.g., pilots, air traffic controllers [ATCOs], engineers). Accordingly, pilots and Air Traffic Controls (ATCOs) have been treated as homogeneous groups with a set of characteristics. Currently, critical themes of human performance in light of systems’ developments place the emphasis on quality training for improved situational awareness (SA), decision-making and cognitive load. Design/methodology/approach As key solutions centre on the increased understanding and preparedness of operators through quality training, the authors deploy an iterative mixed methodology to reveal generational changes of pilots and ATCOs. In total, 46 participants were included in the qualitative instrument and 70 in the quantitative one. Preceding their triangulation, the qualitative data were analysed using NVivo and the quantitative analysis was aided through descriptive statistics. Findings The results show that there is a generational gap between old and new generations of operators. Although positive views on advanced systems are being expressed, concerns about cognitive capabilities in the new systems, training and skills gaps, workload and role implications are presented. Practical implications The practical implications of this study extend to different profiles of operators that collaborate either directly or indirectly and that are critical to aviation safety. Specific implications are targeted on automation complacency, bias and managing information load, and training aspects where quality training can be aided by better understanding the occupational transitions under advanced systems. Originality/value In this paper, the authors aimed to understand the changing nature of the operators’ profession within the advanced technological context, and the perceptions and performance-shaping factors of pilots and ATCOs to define the generational changes.

Applying Discrete Event Simulation (DES) in Healthcare

2015 ◽  
pp. 390-410
Author(s):  
Stavros T. Ponis ◽  
Angelos Delis ◽  
Sotiris P. Gayialis ◽  
Panagiotis Kasimatis ◽  
Joseph Tan
Keyword(s):  
Discrete Event Simulation ◽  
Capacity Planning ◽  
Planning Process ◽  
Discrete Event ◽  
Healthcare Facilities ◽  
Performance Improvements ◽  
Event Simulation ◽  
Health Insurance Provider ◽  
And Performance

This paper highlights the opportunities and challenges of applying Discrete Event Simulation (DES) to support capacity planning of a network of outpatient facilities. Despite an abundance of studies using simulation techniques to examine the operation and performance of outpatient clinics, the problem of capacity allocation and planning of medical services within a network of outpatient healthcare facilities appears to be underexplored. Here, a case study of a health insurance provider that operates a network of six outpatient medical facilities in the US is used to illustrate and explore the synthesizing and adaptive, yet parsimonious nature of using DES methodology for network design and capacity planning. Results of this case study demonstrate that significant performance improvements for the network operator can be achieved with applying DES method to support the network facility capacity planning process.

Early Capacity Testing of an Enterprise Service Bus

2013 ◽  
pp. 288-305
Author(s):  
Ken Ueno ◽  
Michiaki Tatsubori
Keyword(s):  
Performance Evaluation ◽  
Capacity Planning ◽  
Service Oriented Architecture ◽  
Service Providers ◽  
System Development ◽  
Resource Assessment ◽  
Enterprise Service Bus ◽  
Hardware Resource ◽  
And Performance ◽  
Set Up

An enterprise service-oriented architecture is typically done with a messaging infrastructure called an Enterprise Service Bus (ESB). An ESB is a bus which delivers messages from service requesters to service providers. Since it sits between the service requesters and providers, it is not appropriate to use any of the existing capacity planning methodologies for servers, such as modeling, to estimate the capacity of an ESB. There are programs that run on an ESB called mediation modules. Their functionalities vary and depend on how people use the ESB. This creates difficulties for capacity planning and performance evaluation. This article proposes a capacity planning methodology and performance evaluation techniques for ESBs, to be used in the early stages of the system development life cycle. The authors actually run the ESB on a real machine while providing a pseudo-environment around it. In order to simplify setting up the environment we provide ultra-light service requestors and service providers for the ESB under test. They show that the proposed mock environment can be set up with practical hardware resources available at the time of hardware resource assessment. Our experimental results showed that the testing results with our mock environment correspond well with the results in the real environment.

scholarly journals 0218 Biomathematical Modeling Predicts Fatigue Risk in General Surgery Residents

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A84-A85 ◽  
Author(s):  
L P Schwartz ◽  
J K Devine ◽  
S R Hursh ◽  
E Mosher ◽  
S Schumacher ◽  
...  
Keyword(s):  
General Surgery ◽  
National Standards ◽  
Sleep Patterns ◽  
Surgical Resident ◽  
General Surgery Residency ◽  
Performance Predictions ◽  
Shift Schedules ◽  
And Performance ◽  
Surgery Residency Program ◽  
Adjusted Model

Abstract Introduction Fatigue and its effects on performance have long been a concern in medicine. Evidence exists that current duty-hour restrictions for resident trainees have a limited impact on physician wellbeing and patient safety, prompting renewed efforts to address this threat. In this study, sleep patterns of general-surgery residents were used to optimize a biomathematical model of performance for use as a tool for fatigue risk management with residents. Methods General surgery residents based at a multi-hospital, general surgery residency program were approached for participation in this study. Enrolled residents wore actigraph devices for 8 weeks and completed subjective sleep assessments. Sleep data and shift schedules were then input into the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model to assess predicted cognitive performance. Performance was compared to an “effectiveness” level of 77 (equivalent to a blood-alcohol content of 0.05g/dL). Eight hours of sleep debt was considered “below reservoir criteria”. Results Sleep actigraphy data was collected from 22 general surgery residents. Modeling results showed that as shift lengths increased, effectiveness scores generally decreased, and the time spent below criterion (77) increased. Additionally, 11.13% of time on shift was below the effectiveness criterion and 42.7% of shifts included time spent below the reservoir criterion. Adjustments to the sleep prediction were made based on actual sleep, and performance predictions from actual sleep and the adjusted model were significantly correlated (p<.0001). Conclusion Despite adherence to national standards limiting work hours, current surgical resident sleep patterns and shift schedules create concerning levels of fatigue. This study illustrates how biomathematical fatigue models can predict resident physician sleep patterns and performance. Modeling represents a novel and important tool for medical educators seeking to create shift schedules that maintain physician preparedness and minimize fatigue risk. Support N/A

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