• IE interfaces
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• v.20 no.2
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• pp.112-120
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• 2007

As the market rapidly changes, the speed of new product development is highlighted as a critical element which determines the success of firms. While firms endeavor to accelerate the development speed, frequent iterations in a development process hinders the effort of acceleration. For this reason, many previous researches tried to find the optimal structure of the development process which minimizes the number of iterations. However, such researches have a limitation in that they can be applied to only a single-project environment. In a multi-project environment, waiting time induced by lack of resources also delays the process as well as the iterations do. In this paper, we propose dynamic sequencing method focusing on both iterations and waiting time for reducing the durations of development projects in a multi-project environment. This method reduces the waiting time by changing the sequence of development tasks according to the states of resources. While the method incurs additional iterations, they are expected to be offset by the reduced waiting time. The results of simulation show that the dynamic sequencing method dramatically improves the efficiency of a development process. Especially, the improvement is more salient as projects are more crowded and the process is more unbalanced. This method gives a new insight in researches on managing multiple development projects.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.344-350
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• 2022

Due to the increase in container cargo volume, the congestion of container terminals is increasing and the waiting time of gate in-out trucks has significantly lengthened at container yards and gates, resulting in severe inefficiency in gate in-out truck operations as well as port operations. To resolve this problem, the Busan Port Authority and terminal operator provide services such VBS, terminal congestion information, and expected operation processing time information. However, the visible effect remains insufficient, as it may differ from actual waiting time.. Thus, as basic data to resolve this problem, this study presents deep learning based average gate in-out truck waiting time prediction models, using container gate in-out information at Busan New Port. As a result of verifying the predictive rate through comparison with the actual average waiting time, it was confirmed that the proposed predictive models showed high predictive rate.

• Korean Management Science Review
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• v.27 no.1
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• pp.17-31
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• 2010

Patients entering an emergency care center in a hospital usually visit medical processes in different orders depending on the urgency level and the medical treatments required. We formulate the patient flows among diverse processes in an emergency care center using the Jackson network, which is one of the queueing networks, in order to evaluate the system performances such as the expected queue length and the expected waiting time. We present a case study based on actual data collected from an emergency care center in a hospital, in order to prove the validity of applying the Jackson network model in practice. After assessing the current system performances, we provide operational strategies to reduce waiting at the bottleneck processes and evaluate the impact of those strategies on the entire system.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.57-64
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• 2012

The waiting time of patients is an important factor related with service quality of a hospital system. An appointment system of patients is not popular, in special, in a private hospital. An appointment system is expected to diversify patients in time and to reduce patient's waiting time. Three appointment rules are suggested and analyzed to compare the waiting time of appointment and walk-in patients using simulation analysis. The results of two way ANOVA show that the time slot of 30 minutes for allocating appointment patients is better than the time slot of 60 minites in view of patient's waiting time. The results of the appointment level 1 also show that the constant pattern rule and the zigzag pattern rule give shorter waiting time for walk-in patient and for appointment patient, respectively.

• Quality Improvement in Health Care
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• v.5 no.2
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• pp.202-215
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• 1998

Purpose : To shorten processing time for variety of medical affairs of the patient at the outpatient clinic of a big hospital is very important to qualify medical care of the patient. Therefore, patient's waiting time for drug delivery after doctor's prescription is often utilized as a strong tool to evaluate patient satisfaction with a medical care provided. We performed this study to investigate factors influencing patient satisfaction related with waiting time for drug delivery. Methods : The data were collected from July 21 to August 12, 1998. A total 535 patients or their families who visited outpatient clinics of Inha University Hospital were subjected to evaluate the drug delivery time and the level of their satisfaction related, which were compared with those objectively evaluated by Quality Improvement Team. The reliability of the scale was tested with Cronbach's alpha, and the data were analyzed using frequency, t-test, ANOVA, correlation analysis and multiple regression. Results : The mean drug delivery time subjectively evaluated by the patient (16.1 13.0 min) was longer than that objectively evaluated (10.9 7.6 min) by 5.2 min. Drug delivery time objectively evaluated was influenced by the prescription contents, total amount or type of drug dispensed, etc, as expected. The time discrepancy between two evaluations was influenced by several causative factors. One of those proved to be a patient's late response to the information from the pharmacy which the drug is ready to deliver. Interestingly, this discrepancy was found to be more prominent especially when waiting place for drug delivery was not less crowded. Other factors, pharmaceutical counseling at the pharmacy, emotional status or behavior of a patient while he waits for the medicine, were also found to influence the time subjectively evaluated. Regarding the degree of patient satisfaction with the drug delivery, majority of patients accepted drug delivery time with less than 10 min. It was also found to be influenced by emotional status of the patient as well as kindness or activity of pharmaceutical counselor. Conclusion : The results show that, besides prescription contents, behavior pattern or emotional status of a patient, environment of the waiting place, and quality of pharmaceutical counseling at the pharmacy, may influence the patient's subjective evaluation of waiting time for drug delivery and his satisfaction related with the service in the big hospital. In order to improve patient satisfaction related with waiting time for drug delivery, it will be cost effective to qualify pharmaceutical counseling and information system at the drug delivery site or waiting place rather than to shorten the real processing time within the pharmacy.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.185-193
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• 2024

With the advent of smartphones, people can access various information through the internet anytime and anywhere. Even in the vehicle environment, users can use the internet. Users interact with web and applications every day and get information. However, as the amount of data to be processed by the program increases, users inevitably receive a message to wait. User waiting is an inconvenient experience, but minimizing user waiting is the best way because there is time required for data processing. However, if the service processing time exceeds the expected time, users experience more severe boredom and pain. Therefore, various methods and researches are being conducted to alleviate the boredom of user waiting. The most commonly used method to alleviate user waiting boredom is loading. In this study, we investigated the effect of skeleton loading, the latest loading technique, on user waiting experience, and how attractive it is as a design technique in terms of UI compared to other loading techniques.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.142-148
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• 1989

In order to determine the level of service which minimizes the total of expected cost of service and the expected cost of waiting for that service, the important considerations are to evaluate the distance traveled to and from a service facility (D) and the expected number of mechanics in queueing system (L). The travel-time models are very useful when the servers must travel to the customer from the service facility. Thus, in this paper we studied on the determination of the optimal service level by the travel-time models. In order to decide the optimal service level, (D) has been introduced as a uniform distribution and (L) has been introduced as M/M/S model of queueing theory.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.11-24
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• 2012

We compared a DBR(drum-buffer-rope) system with a CONWIP(constant work-in-process) system in a production line with constant processing times. Based on the observation that a WIP-controlled line production system such as DBR and CONWIP is equivalent to a m-node tandem queue with finite buffer, we applied a max-plus algebra based solution method for the tandem queue to evaluate the performance of two systems. Numerical examples with 6 workstations were also used to demonstrate the proposed analysis. The mathematical analyses support that CONWIP outperforms DBR in terms of expected waiting time and WIP. Unlike the CONWIP case, sequencing workstations in a DBR affects the performance of the system. Delaying a bottleneck station in a DBR reduces expected waiting time.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.175-181
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• 2002

BIS(Bus arrival Information System) is a system that informs Passengers waiting at bus stops of the bus arrival time of next buses. However, when operating this system, it is not exactly known what type of bus arrival information should be provided. The purpose of this paper is to develop a model of the optimal bus arrival time to be informed for BIS. Analyzing Efficiency in the Seoul's Urban Bus Industry Using Data Envelopment Analysis. Two basic types of bus arrival information can be considered. One is Bus Locations : Where next buses are located and under what situation they are, such as the next bus departed from the previous stop, The other is Expected Arrival Time. Time to the arrivals of next buses. Characteristics of these two types of bus arrival time information provided for passengers waiting at bus stops for BIS are examined. The waiting time of passengers at bus stops is derived as a function of the bus arrival time to be informed. Some basic principles about the optimal bus arrival time to be informed are found. Finally, a case study assuming several simplifications is performed. One of the key findings is that there exists optimal arrival time to be informed other than the average arrival time. The optimal arrival time to be informed should be closer to the average arrival time for small and very large standard deviations and be earlier for certain amounts of standard deviations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.21-29
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• 2015

A steady-state controllable M/G/1 queueing model operating under the {T:Min(T,N)} policy is considered where the {T:Min(T,N)} policy is defined as the next busy period will be initiated either after T time units elapsed from the end of the previous busy period if at least one customer arrives at the system during that time period, or after T time units elapsed without a customer' arrival, the time instant when Nth customer arrives at the system or T time units elapsed with at least one customer arrives at the system whichever comes first. After deriving the necessary system characteristics including the expected number of customers in the system, the expected length of busy period and so on, the total expected cost function per unit time for the system operation is constructed to determine the optimal operating policy. To do so, the cost elements associated with such system characteristics including the customers' waiting cost in the system and the server's removal and activating cost are defined. Then, procedures to determine the optimal values of the decision variables included in the operating policy are provided based on minimizing the total expected cost function per unit time to operate the queueing system under considerations.