• Journal of the Korea Safety Management & Science
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• v.23 no.3
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• pp.27-33
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• 2021

The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

• Korean Journal of Occupational Health Nursing
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• v.30 no.4
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• pp.145-155
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• 2021

Purpose: The purpose of this study was to examine the effects of customer violence experiences, protection systems, and monitoring systems on the subjective health status of salespersons and electronic machine repairers. Methods: A total of 934 persons were sampled nationwide, including 582 salespersons and 352 electronic machine repairers, from March 2~30, 2020 and asked to fill out a self-reported questionnaire. Results: The findings show that electronic machine repairers were more exposed to customer violence and had a weaker protection system than salespersons. They also experienced severe control from management through a monitoring system. The regression analysis revealed that verbal violence had a negative impact on the subjective health status of electronic machine repairers (p=.021). A worker protection system had significant effects on the improved subjective health status of salespersons (p=.009). Depression and fatigue had negative impacts on the subjective health status of both salespersons (depression: p<.001, fatigue: p<.001) and electronic machine repairers (depression: p<.001, fatigue: p=.002). Conclusion: These findings put a greater emphasis on the need for worker protection systems to prevent workplace violence and a health promotion program to manage depression and fatigue in workplaces.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.263-266
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• 2019

In this paper, we suggest an activity and health monitoring system to observe the status of the dogs in real time. We also propose a k-days algorithm which helps monitoring pet health status using classified activity data from a machine learning approach. One of the best machine learning algorithm is used for the classification activity of dogs. Dog health status is acquired by comparing current activity calculation with passed k-days activities average. It is considered as a good, warning and bad health status for differences between current and k-days summarized moving average (SMA) > 30, SMA between 30 and 50, and SMA < 50, respectively.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.169-178
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• 2018

The ice machine is the machine for making ice. As most of the companies that manufactures and sells the ice machine are small and medium-sized companies, they have been they have been experiencing the trouble for the after-sales service after selling the machine. The difficulties of the after-sales service are mostly caused by unnecessary customer service requests of the purchaser, which eventually leads to the unnecessary expenditure of the seller and the purchaser. However, financially, the poor ice machine manufacturers want to reduce this cost as much as possible. Furthermore, even if they want to sell their products overseas, they are hesitating because of the after-sales service. For this reason, the companies making the ice machine need a system which checks the status of the ice machine and takes the proper actions without the visiting service. Therefore, this paper introduces the remote control and operational status monitoring systems which can monitor the status of the ice machine in the remote area and control it as needed. Through the developed system, the company manufacturing the ice machine and the manager of the ice machine can understand the current status of the ice machine and respond against the ice machine's trouble, immediately. In addition, it can be expected to have great effects on cost reduction because the maintenance and management after selling can be efficiently performed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.60-63
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• 1997

Recently, factory automation and shop floor control system need a web based remote monitoring technology to control effectively machine tool. This paper describes a web based remote monitoring system which is concerned with open architecture controller for machine tool. The environment of this system consists of a lot of elements such as web server, database, machine tool, pc based controller, client computers and script programs, also which is interconnected by network including intranet or internet. Designed script programs, also which is interconnected by network including intranet or internet. Designed script program service current status and faults information of machine to remote users who want to monitor machine tool. Additionally those have various functions to service we board for q&a, downloading data and information of after-service managers.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.1-18
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• 2017

Recently, identification of the extremely stressed condition of children is an essential skill for real-time recognition of a dangerous situation because incidents of children have been dramatically increased. In this paper, therefore, we present a model based on machine learning techniques for stress status identification of a child by using bio-signals such as voice and heart rate that are major factors for presenting a child's emotion. In addition, a smart band for collecting such bio-signals and a mobile application for monitoring child's stress status are also suggested. Specifically, the proposed method utilizes stress patterns of children that are obtained in advance for the purpose of training stress status identification model. Then, the model is used to predict the current stress status for a child and is designed based on conventional machine learning algorithms. The experiment results conducted by using a real-world dataset showed that the possibility of automated detection of a child's stress status with a satisfactory level of accuracy. Furthermore, the research results are expected to be used for preventing child's dangerous situations.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.1 s.190
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• pp.7-13
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• 2007

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.235-238
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• 2000

This article presents an adaptive decision tree algorithm for dynamically reasoning machine failure cause out of real-time, large-scale machine status database. On the basis of experiment using semiconductor etching machine, it has been verified that our model outperforms previously proposed decision tree models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.708-713
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• 1997

A remote data communication system for monitoring of NC machine fault diagnosis and status is developed. This system communicates with host PC by using dial-up communication method on PSTN. The developed system consists of (1)remote communication module among NC's and host PC using PSTN, (2) 8 channels analog data sensing module, (3) digital I/O module for control of NC machine, (4) communication module between NC machine and remote data communication system using RS-232c, and (5) Software man-machine interface. This system may be applied for remote sensing of the status in Fms. To show the veridity of the developed system, several examples are illustrated.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.23-27
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• 2018

Korea has a high proportion of self-employment. Many of them start the food business since it does not require high-techs and it is possible to start the business relatively easily compared to many others in business categories. However, the closure rate of the business is also high due to excessive competition and market saturation. Cafés and restaurants are examples of food business where the business analysis is highly important. However, for most of the people who want to start their own business, it is difficult to conduct systematic business analysis such as trade area analysis or to find information for business analysis. Therefore, in this paper, we predicted business status with simple information using Microsoft Azure Machine Learning Studio program. Experimental results showed higher performance than the number of attributes, and it is expected that this artificial intelligence model will be helpful to those who are self-employed because it can easily predict the business status. The results showed that the overall accuracy was over 60 % and the performance was high compared to the number of attributes. If this model is used, those who prepare for self-employment who are not experts in the business analysis will be able to predict the business status of stores in Seoul with simple attributes.