• IE interfaces
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• v.23 no.3
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• pp.205-212
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• 2010

The learning curve model is a mathematical form which represents the relationship between the manufacturing experience and its effectiveness. The semiconductor manufacturing is widely known as an appropriate example for the learning effect due to its complicated manufacturing processes. In this paper, I propose a new compound learning curve model for semiconductor products in which the general learning curve model and the growth curve are composed. The dependent variable and the effective independent variables of the model were abstracted from the existing learning curve models and selected according to multiple regression processes. The simulation results using the historical DRAM data show that the proposed compound learning curve model is one of adequate models for describing learning effect of semiconductor products.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.77-84
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• 1992

This paper constructs Croup Technology process-based learning curve model adjusted to a Group Technology environment which accounts for shared learning that occurs when multiple products utilize some of the same process steps. Through this constructed model, the estimated times and productivity of labor calculated by the Group Technology process-based learning curve model are compared with those generated by employing product-based 1 earning curve model. For sensitivity analysis of the model, the impact of learning rate and the ordered production quantity on the ratio differences between Group Technology process-based learning curve model and product-based learning curve model are examined. These results indicate the critical importance of employing Group Technology process-based learning curve model when a process spans multiple products.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.97-103
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• 2011

This paper develops a technology level quantification (TLQ) model by utilizing a learning curve. Original learning curve shows the relationship between cumulative number of units and the required time for the unit. On the other hand, in our developed model, the technology level, such as speed of production and quality of the produced items, is expressed as a function of not cumulative number of units but time, for increasing generality. Furthermore, for expressing each learning that consists of conceptual learning and operational learning, S-curve is utilized in our developed model. By fitting the S-curve and/or decomposing into some activities, our TQL model can be applied to approximate organizational and complicated process. Some variations in time and levels, parameters of our developed model are shown. By using the parameters, the procedure to identify our developed model is proposed. Also, the influential factors for the parameters of our developed model are discussed with classifying the factors into technoware, infoware, humanware, and orgaware. The expected technology level is utilized for expecting the capacity of production system, and the expected capacity can be utilized in predicting various changes in the organization and deciding managerial decision about TT. A case study in manufacturing industry shows the effectiveness of the developed model.

• Proceedings of the ESK Conference
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• 1992.10a
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• pp.113-120
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• 1992

In this paper, a mathematical model of learning curve is proposed to study the finger's reaction time. The model is a logarithmic linear type which represents a learning curve appropriately, and parameters are estimated by the linear. The learning coefficient and percentage of a reaction time can be easily computed in the mathematical model. This quantitative approach provides an important information to be used for the working capability qualification for re-employment as well as for the adaptability estimation of aged workers.

• IE interfaces
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• v.25 no.4
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• pp.441-449
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• 2012

Solar PV(photovoltaic) is paid great attention to as a possible renewable energy source to overcome recent global energy crisis. However to be a viable alternative energy source compared with fossil fuel, its market competitiveness should be attained. Grid parity is one of effective measure of market competitiveness of renewable energy. In this paper, we forecast the grid parity timing of solar PV energy in Korea using two factor learning curve model. Two factors considered in the present model are production capacity and technological improvement. As a result, it is forecasted that the grid parity will be achieved in 2019 in Korea.

• Journal of the Ergonomics Society of Korea
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• v.11 no.2
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• pp.47-56
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• 1992

In this paper, a mathematical model of learning curve is proposed to study the fi- nger's reaction time. The model is a logarithmic linear type which represents a lear- ning curve appropriately, and parameters are estimated by the linear. The learning coefficient and percentage of a reaction time can easily computed in the mathematical model. This quantitative approach provieds an important information to be used fot the working capqbility qualification of re-employment as well as the adaptability estimation of aged workers.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.1
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• pp.165-172
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• 2012

For practical education, many practices using various practical equipments have to be provided to students. In this study, the application of learning curve to represent student's learning process in a practical education using a equipment was studied. Learning curve model was originally developed in production management and based on human performance in human factors aspects. In this study, the application of learning curve model was studied on the eye tracking system, which is used to evaluate the usability of a product in design area. As a case study for its applicability, practical education for eye tracking system was provided to three students and then task completion times were measured for hardware system setup and gaze image recording. Learning curves were estimated for two tasks and then task completion times were predicted using the learning curves. Through ANOVA(analysis of variance) and correlation analysis, the applicability of learning curve to practical education was analysed. As the result, learning curve could be effectively applied to practical eduacation using equipment.

• Journal of the Ergonomics Society of Korea
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• v.27 no.2
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• pp.59-65
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• 2008

Product usability consists of many attributes such as learnability, efficiency, memorability, and so on. In particular, learnability is one of the most important attributes in product usability. Therefore, many people consider the primary criterion for a good user interface to be the degree to which it is easy to learn. Learnability represents the degree of how much can easily learn the usage of a product. It concerns the features of the interactive system that allow novice users to understand how to use it initially and then how to attain a maximal level of performance. In this study, we studied on the application of learning curve to evaluate product learnability. In order to validate the applicability, we carried out simple experiment using mobile phone. We got task completion times through the experiment and predicted the times using learning curve model. And then, we compared prediction times to task completion times. Finally, we identified that learning curve could apply to predict and compare product learnability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.518-527
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• 2014

This study is to estimate the learning curve based on the consequences of reduced voice of customer from each telecommunication service products. We used Exponential Decay Model, which is the most popular among the learning curve models. We attempted to add how VOC changes in accordance with seasonal factors, human resource input, application of software, and the investment. The results of the empirical analysis of each service product as follows: First, as learning curve, customer complaints decreased. Second, human resource input, Network fault make increase or decrease customer complaints(VOC). Third, even though increasing the customer's quality of experience, VOC would not decrease due to service paradox.

• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.20-27
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• 2023

Background: As the number of nuclear facilities nearing their pre-determined design life increases, demand is increasing for technology and infrastructure related to the decommissioning and decontamination (D&D) process. It is necessary to consider the nature of the dismantling environment constantly changing and the worker doing new tasks. A method was studied that can calculate the effect of learning and the change in work time on the work process, according to the learning-forgetting curve model (LFCM). Materials and Methods: The LFCM was analyzed, and input values and scenarios were analyzed for substitution into the D&D process of a nuclear facility. Results and Discussion: The effectiveness and efficiency of the training were analyzed. It was calculated that skilled workers can receive a 16.9% less collective radiation dose than workers with only basic training. Conclusion: Using these research methods and models, it was possible to calculate the change in the efficiency of workers performing new tasks in the D&D process and the corresponding reduction in the work time and collective dose.