Analysis of batched service time data using Gaussian and semi-parametric kernel models

Queue is an occurrence where someone has to wait their turn to get service. Queuing processes in hospitals when processing outpatient registration medical records at the hospital often occur especially during peak hours. To overcome this problem, a solution is needed to improve service performance at the hospital. The queuing model used is the Multi Channel-single phase queuing model which has one or more services flowing by a single queue. The variables to be observed are time between arrivals, service time data and number of services assuming a Poisson distribution pattern. The results of this study will show the operator's busy time is 83.33%, the number of queues in a certain period (Lq) is 13 patients, the number of registrants in the system (L) is 14 patients, the waiting time in the queue (Wq) is 24 minutes, and waiting time in the system (W) is 30.06 minutes.

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Queuing analysis using Viswalk for check-in counter: Case study of Lombok Praya International Airport

MATEC Web of Conferences ◽

10.1051/matecconf/201818102006 ◽

2018 ◽

Vol 181 ◽

pp. 02006

Author(s):

Sony Sulaksono Wibowo ◽

Siti Raudhatul Fadilah

Keyword(s):

Service Time ◽

Demand Forecasting ◽

Optimal Number ◽

Queuing System ◽

Time Data ◽

Traffic Demand ◽

Queuing Analysis ◽

International Airport ◽

Airport Terminal

Queuing analysis on check-in counter in airport is required to accommodate the passenger processing facilities, such as check-in service. The purpose of this paper is to evaluate the performance of a queuing system at check-in facilities in 2nd passenger terminal Lombok Praya International Airport in 2016 and 2036. This analysis is done by determining parameters of the queues at every check-in counter through simulations on Viswalk. Before running the simulation, the model of airport terminal must be created first. Queuing simulation starts with the traffic demand forecasting of domestic departure passenger for the next 20 years. To determine the optimal number of check-in counters, an iteration of various number is performed. Check-in services time data were adopted from previous study which became an input of the simulation using two different scenarios. The expected output are the queuing parameter and the distribution of passenger service time at each check-in counter.

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Mengurangi Antrean pada Stasiun Pengisian Bahan Bakar Umum dengan Pendekatan Simulasi Menggunakan ProModel

JIEMS (Journal of Industrial Engineering and Management Systems) ◽

10.30813/jiems.v12i1.1534 ◽

2019 ◽

Vol 12 (1) ◽

Author(s):

Mirna Lusiani ◽

Anie Belita

Keyword(s):

Service Time ◽

Discrete Event ◽

Primary Data ◽

Time Data ◽

Actual System ◽

Large Cities ◽

Event Simulation ◽

Gas Station ◽

Increasing Demand ◽

Number Of Customers

<p>The gas station has become an important facility for the public, especially for people in large cities such as Jakarta. This condition was caused by increasing demand from year to year. The number of facilities has less number than the customer that came, which could cause queueing in the station. This research was made with the purpose to reduce the number of the queue and increase the number of customers serviced at the gas station. This research located on one of the gas stations in Jakarta at 16.00-18.00 from Monday to Friday. The data used for this research is primary data which was observed directly by the researcher. The data used for this research are the number of customers arrived and service time. Data analysis is using discrete-event simulation with ProModel software. The conclusion of this research is the actual system has a relatively high number of queueing customer which also affect the reduced number of customers that was served. Improvement model was created by decreasing the service time by 10% with the average number of queues by 4 customers for Pertalite and 4<br />customers for Premium. Scenario model is also designed as a proposal by using customer migration scenario from Premium to Pertalite by 30%, 60%, and 100%. The proposed system for the first scenario is by decreasing the service time by 20% with the average number of queues by 8 customers for Pertalite and 1 customer for Premium. For the second scenario is by modifying the queueing system and decreasing the service time by 10% with the average number of queues by 8 customers for Pertalite and 7 customers for Premium. For the third scenario is by opening a new server for Pertalite with the average number of queues by 5 customers.</p>

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Peningkatan Pelayanan di Poli Kebidanan dan Kandungan RSUD Saiful Anwar dengan Menggunakan Simulasi Antrian

Jurnal Teknik Industri ◽

10.22219/jtiumm.vol3.no1.85-92 ◽

2010 ◽

Vol 3 (1) ◽

pp. 85

Author(s):

Ilyas Mas'udin

Keyword(s):

System Design ◽

Waiting Time ◽

Service Time ◽

Service System ◽

Initial Condition ◽

Trial And Error ◽

Time Data ◽

Service System Design ◽

Kolmogorov Smirnov ◽

The Mean

This research have aim to reduce waiting time of patient in pregnant division at RSUD Saiful Anwar Malang. First step, collecting the time between arrival data and service time data at each division. These data were tested using Kolmogorov-Smirnov to find a kind of distribution and the parameter of the data. Them making service system design based on the initial condition using ARENA and run to find the mean of waiting time from the beginning design, using trial and error then tried some new altematives design to minimize waiting time.

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A Study on Statistical Methods for Prediction of Service Life of Fire Trucks

Fire Science and Engineering ◽

10.7731/kifse.7d557484 ◽

2021 ◽

Vol 35 (2) ◽

pp. 39-44

Author(s):

Chang-Sub Chun ◽

Seung-Mo Kim

Keyword(s):

Statistical Analysis ◽

Service Time ◽

Functional Approach ◽

Time To Failure ◽

Economic Approach ◽

Original Function ◽

Time Data ◽

Economic Productivity ◽

Professional Institution ◽

Mean Time

The current methods of calculating the economic productivity of fire pumpers reduce the value of the vehicle based on its lifetime use. However, it is reasonable to base the service time of a fire pumper on its original function. In this study, we proposed the use of the functional approach to determine the productivity of fire pumpers as opposed to the use of the economic approach. The Korea Fire Institute is a professional institution that inspected 342 fire pumpers in 2019. In all, 102 pumpers were found to be malfunctioning. The number was modified to 100 cases considering the production date and results of statistical analysis. Next, we determined a mean time to failure (MTTF) of 7.65 years based on the service time data using Weibull distribution; this MTTF is 2.35 years shorter than the current mean service time of the pumpers, so this study selected a reasonable service time of 8 years for a pumper.

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Modeling Within-Person Variance in Reaction Time Data of Older Adults

GeroPsych ◽

10.1024/1662-9647/a000045 ◽

2011 ◽

Vol 24 (4) ◽

pp. 169-176 ◽

Cited By ~ 4

Author(s):

Philippe Rast ◽

Daniel Zimprich

Keyword(s):

Reaction Time ◽

Cognitive Aging ◽

Reaction Times ◽

Reaction Time Task ◽

Reaction Time Data ◽

Scale Model ◽

Time Data ◽

Time Task ◽

The Mean ◽

Second Wave

In order to model within-person (WP) variance in a reaction time task, we applied a mixed location scale model using 335 participants from the second wave of the Zurich Longitudinal Study on Cognitive Aging. The age of the respondents and the performance in another reaction time task were used to explain individual differences in the WP variance. To account for larger variances due to slower reaction times, we also used the average of the predicted individual reaction time (RT) as a predictor for the WP variability. Here, the WP variability was a function of the mean. At the same time, older participants were more variable and those with better performance in another RT task were more consistent in their responses.

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Ambulatory Assessment

European Psychologist ◽

10.1027/1016-9040.14.2.109 ◽

2009 ◽

Vol 14 (2) ◽

pp. 109-119 ◽

Cited By ~ 66

Author(s):

Ulrich W. Ebner-Priemer ◽

Timothy J. Trull

Keyword(s):

Real Time ◽

Clinical Psychology ◽

Real Life ◽

Ambulatory Assessment ◽

Computer Assisted ◽

Affective Valence ◽

Time Data ◽

Physiological Processes ◽

Context Specific ◽

Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

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