• Title/Summary/Keyword: data industry

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A Decision Tree Approach for Identifying Defective Products in the Manufacturing Process

  • Choi, Sungsu;Battulga, Lkhagvadorj;Nasridinov, Aziz;Yoo, Kwan-Hee
    • International Journal of Contents
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    • v.13 no.2
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    • pp.57-65
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    • 2017
  • Recently, due to the significance of Industry 4.0, the manufacturing industry is developing globally. Conventionally, the manufacturing industry generates a large volume of data that is often related to process, line and products. In this paper, we analyzed causes of defective products in the manufacturing process using the decision tree technique, that is a well-known technique used in data mining. We used data collected from the domestic manufacturing industry that includes Manufacturing Execution System (MES), Point of Production (POP), equipment data accumulated directly in equipment, in-process/external air-conditioning sensors and static electricity. We propose to implement a model using C4.5 decision tree algorithm. Specifically, the proposed decision tree model is modeled based on components of a specific part. We propose to identify the state of products, where the defect occurred and compare it with the generated decision tree model to determine the cause of the defect.

The Arrival of the Industry 4.0 and the Importance of Corporate Big Data Utilization

  • AN, Haeri
    • East Asian Journal of Business Economics (EAJBE)
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    • v.10 no.2
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    • pp.105-113
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    • 2022
  • Purpose - An increase in automation has been as a result of digital technologies. The data will be instrumental in the determination of the services that are more necessary so that more resources can be allocated for them. The purpose of the current research is to investigate how big data utilization will help increase the profitability in the industry 4.0 era. Research design, Data, and methodology - The present research has conducted the comprehensive literature content analysis. Quantitative approaches allow respondents to decide, but qualitative methods allow them to offer more information. In the next step, respondents are given data collection equipment, and information is collected. Result - The According to qualitative literature analysis, there are five ways in which big data utilization will help increase the profitability in the industry 4.0 era. The five solutions are (1) Better Customer Insight, (2) Increased Market Intelligence, (3) Smarter Recommendations and Audience Targeting, (4) Data-driven innovation, (5) Improved Business Operations. Conclusion - Modern companies have been seeking a competitive advantage so that they can have the edge over other companies in the same industries providing the same services and products. Big data is that technology that businesses have always wanted for an extended period of time to revolutionize their operations, making their businesses more profitable.

A Study on the Real-time Data Interface Technology based on SCM for Shipbuilding and Marine Equipment Production (조선해양기자재 제작을 위한 SCM 기반 실시간 데이터 인터페이스 기술에 관한 연구)

  • Myeong-Ki Han;Young-Hun Kim;Jun-Su Park;Won-Ho Lee
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.1
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    • pp.143-149
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    • 2024
  • The production and procurement of shipbuilding and offshore equipment is an important competitive factor in the shipbuilding and offshore industry. Recently, ICT-based digital technology has been rapidly applied to the manufacturing industry following the Fourth Industrial Revolution. Under the digital transformation, real-time data interface technology based on SCM (Supply Chain Management) is emerging as an important tool to improve the efficiency of the equipment manufacturing process. In this study, the characteristics and advantages and disadvantages of interface technologies of web-based data interface technologies were compared and analyzed. The performance was compared between theoretical evaluation based on technical features and practical application cases. As a result, it was confirmed that GraphQL is useful for selective data processing, but there is a problem with optimization, and REST API has a problem with receiving data due to a fixed data structure. Therefore, this study aims to suggest ways to utilize and optimize these data interface technologies.

A Profit Calculating Analysis and a Proposal of Estimation System of Historical Cost Data in the Electrical Construction Works (실적공사비에서 전기공사의 적정이윤율 분석에 관한 연구)

  • Seo, S.S.;Jang, Y.G.;Kim, K.G.;Hyun, S.Y.;Wang, Y.P.;An, J.H.;Park, M.Y.;Sohn, H.K.
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.2129_2131
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    • 2009
  • Since Jan. 2004, the Ministry of Construction and Transportation has partly introduced estimation system of historical cost data in order to reflect result cost of construction market to cost estimation for public construction. It is expected that the purpose of the introduction would be evaluated considering the long-term development of domestic construction industry. In article 3, paragraph 4 of the planning criteria of estimated cost of financial regulation related to government contract rule, the profit estimated by historical cost data indicates sales profit and it is calculated by multiplying the sum of direct cost, indirect cost and general overhead by rate of profit. Finally, it is said that rate of profit cannot exceeds 10%. However, there are a lot of constructions for electronic equipment in the electronic construction and the proportion of government furnished material is very high, not like engineering works or constructions. Therefore, as the proportion of material cost over direct cost is relatively lower, if current rate of profit (10%) is applied, there would be a wide difference of cost in the items of profit under the estimation system of historical cost data. This paper was conducted to examine estimation methods of the items of profit under the estimation system of historical cost data and suggest reasonable applications.

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Dilemma of Data Driven Technology Regulation : Applying Principal-agent Model on Tracking and Profiling Cases in Korea (데이터 기반 기술규제의 딜레마 : 국내 트래킹·프로파일링 사례에 대한 주인-대리인 모델의 적용)

  • Lee, Youhyun;Jung, Ilyoung
    • Journal of Digital Convergence
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    • v.18 no.6
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    • pp.17-32
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    • 2020
  • This study analyzes the regulatory issues of stakeholders, the firm, the government, and the individual, in the data industry using the principal-agent theory. While the importance of data driven economy is increasing rapidly, policy regulations and restrictions to use data impede the growth of data industry. We applied descriptive case analysis methodology using principal-agent theory. From our analysis, we found several meaningful results. First, key policy actors in data industry are data firms and the government among stakeholders. Second, two major concerns are that firms frequently invade personal privacy and the global companies obtain monopolistic power in data industry. This paper finally suggests policy and strategy in response to regulatory issues. The government should activate the domestic agent system for the supervision of global companies and increase data protection. Companies need to address discriminatory regulatory environments and expand legal data usage standards. Finally, individuals must embody an active behavior of consent.

Development of Creating Continuous and Common Cutting NC Data Program (소부재 연속/공용 절단 데이터 생성 프로그램 개발)

  • Hyun, Sung-Yeol;Oh, Sung-Kwon;Huh, Ok-Jae;Shim, Hyun-Sang
    • Special Issue of the Society of Naval Architects of Korea
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    • 2011.09a
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    • pp.101-105
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    • 2011
  • In most shipbuilding company, cutting procedure is proceed by cutting machine which run by CNC(Computer Numerical Code) data. In our cutting process, all CNC data is created by our nesting post processor system automatically. Among them, in case that cutting piece in the remnant plate, our system creates only one piece CNC data. Because remnant plate is not typical shape, and ship designers don't know remnant plate shape and quantity. In can happen some merit and good point if we modify 1:1 piece NC data by shorten cutting path, reducing cutting time or re-arrangement piece. For modifying cutting data, outside workers have to call to ship designer or have to go to NC control room where control the CNC system and cutting machine. It makes stop work process, and it waste time. In this paper, we introduce a program that can modify and replace 1:1 NC data with continuous or common NC data automatically.

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Survival Strategies for Data Business in the Post-COVID Era (포스트 코로나 시대 데이터 비즈니스 생존전략)

  • Lee, Raehyung
    • Journal of Technology Innovation
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    • v.28 no.4
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    • pp.165-175
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    • 2020
  • In this viewpoint paper, we overlook the potential of the data industry and the strategies needed in order to survive in this new socio-economic order brought by COVID-19. The social distancing culture is leading to the expansion and centralization of data. The government established the development plan of the data industry ecosystem and the capital flow is following this stream, so this is an opportunity for those in the data business. To survive and grow in the data industry ecosystem, we need to identify quality characteristics that have a comparative advantage over competitors based on high data quality and need to determine the target business segmentation to avoid wasting resources and make efficient investments.

Analysis on Types of Golf Tourism After COVID-19 by using Big Data

  • Hyun Seok Kim;Munyeong Yun;Gi-Hwan Ryu
    • International Journal of Advanced Culture Technology
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    • v.12 no.1
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    • pp.270-275
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    • 2024
  • Introduction. In this study, purpose is to analize the types of golf tourism, inbound or outbound, by using big data and see how movement of industry is being changed and what changes have been made during and after Covid-19 in golf industry. Method Using Textom, a big data analysis tool, "golf tourism" and "Covid-19" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 1 st January, 2023 to 31st December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "golf tourism" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, top 36 keywords with the highest relevance and search frequency were selected and applied to this study. The top 36 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. Results By using big data analysis, it was found out option of oversea golf tourism is affecting on inbound golf travel. "Golf", "Tourism", "Vietnam", "Thailand" showed high frequencies, which proves that oversea golf tour is now the re-coming trends.

A Data Envelopment Analysis Model for Evaluation of Efficiency of Deep-Sea Fishing Industry (원양어업의 효율성 평가를 위한 자료포락 분석 모형)

  • Kim, Jae-Hee;Choi, Kang-Deuk;Kim, Soo-Kwan
    • The Journal of Fisheries Business Administration
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    • v.39 no.3
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    • pp.49-65
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    • 2008
  • In Korea, deep-sea fishing industry is faced with pressure of being thrown out of business, because of the upcoming unfavorable business conditions such as the fishing regulation of coastal countries, Korea-US Free Trade Agreement(KORUS FTA), and the other socio-economic changes. Hence, we present an evaluation of future business competitive for the deep-sea fishing industry so that the government can develop a concession plan for the deep-sea fishing industry by utilizing the results of this study. In efficiency analysis of deep-sea fishing industry, the decision maker may have two problems: (1) how to deal with multiple inputs and outputs of deep-sea fishing industry and (2) how to assign the weights on different inputs and outputs, In this paper, we proposed to use Data Envelopment Analysis (DEA) to estimate efficiency of deep-sea fishing industry with multiple inputs and outputs. In the DEA, The direct impact of KORUS FTA, fishing regulation of coastal countries, fishing charges, and competitive fishing conditions were used as input parameters while the profitability and secured fishing quarters, as outputs. The results of DEA-BCC model indicate that 6 out of 12 DUMs have better efficiency under variable return to scale assumption.

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The Impact of Cruise Lines' Program on Tourism Industry in Incheon

  • KIM, Kyungmi;PARK, Hyunjun
    • The Journal of Economics, Marketing and Management
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    • v.8 no.1
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    • pp.20-28
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    • 2020
  • Purpose: This research explores possibilities for unique tourism programs in the Port of Incheon that would bring tourism benefits from the cruise line industry to Incheon. This research also tries to find practical strategies and principles for the cruise line industry by reviewing the current itinerary in the cruise line industry. Research design, data, and methodology: Because this study is exploratory research, it first reviews trends in global tourism, ocean tourism, and the cruise line industry. Then, this study compares the current status of cruise line industry in South Korea with those in Japan. Lastly, existing cruise itineraries are reviewed for practical strategies and principles. Results: Based on reviewing the example of a cruise ship itinerary from the cruise ship company, possible cruise line programs at stopover places are suggested for the Port of Incheon and if the program is planted, it will boost Incheon's economy and tourism industry. Conclusion: Basic data about tourism in coastal regions and data analyses are lacking. Therefore, this study not only recommends further research in itinerary development or evaluation of cruise stopover programs, but also future research should explore the impact of the cruise industry from many different perspectives.