• Title/Summary/Keyword: Manufacturing Big Data

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A Study on the Perception of Fashion Platforms and Fashion Smart Factories using Big Data Analysis (빅데이터 분석을 이용한 패션 플랫폼과 패션 스마트 팩토리에 대한 인식 연구)

  • Song, Eun-young
    • Fashion & Textile Research Journal
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    • v.23 no.6
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    • pp.799-809
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    • 2021
  • This study aimed to grasp the perceptions and trends in fashion platforms and fashion smart factories using big data analysis. As a research method, big data analysis, fashion platform, and smart factory were identified through literature and prior studies, and text mining analysis and network analysis were performed after collecting text from the web environment between April 2019 and April 2021. After data purification with Textom, the words of fashion platform (1,0591 pieces) and fashion smart factory (9750 pieces) were used for analysis. Key words were derived, the frequency of appearance was calculated, and the results were visualized in word cloud and N-gram. The top 70 words by frequency of appearance were used to generate a matrix, structural equivalence analysis was performed, and the results were displayed using network visualization and dendrograms. The collected data revealed that smart factory had high social issues, but consumer interest and academic research were insufficient, and the amount and frequency of related words on the fashion platform were both high. As a result of structural equalization analysis, it was found that fashion platforms with strong connectivity between clusters are creating new competitiveness with service platforms that add sharing, manufacturing, and curation functions, and fashion smart factories can expect future value to grow together, according to digital technology innovation and platforms. This study can serve as a foundation for future research topics related to fashion platforms and smart factories.

Development of Cloud based Data Collection and Analysis for Manufacturing (클라우드 기반의 생산설비 데이터 수집 및 분석 시스템 개발)

  • Young-Dong Lee
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.216-221
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    • 2022
  • The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.

Recognizing the Necessity for Developing Customer-Oriented New Products for the 4th Industrial Revolution (4차 산업혁명 시대를 대비한 고객 중심의 신제품 개발 필요성 인식 제고)

  • Oh, Won-geun
    • Journal of Information Technology Applications and Management
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    • v.27 no.1
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    • pp.97-109
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    • 2020
  • It is expected that the Fourth Industrial Revolution will have a great impact on the manufacturing industry, especially as it will cause big changes in industry, economy as well as socio-cultural. To cope with this situation, each country is promoting the policy of cultivating its manufacturing. This study derives the effect of the fourth industrial revolution on product lifecycle management for smart manufacturing through expert's cognitive analysis. The knowledge area of product lifecycle management is divided into Project Portfolio Management, Collaborative Product Design, Customer Needs Management, Direct Material Sourcing, Product Data Management, Digital Manufacturing & Engineering, R&D Foundation, New Product Development through academic research. The expert survey was conducted in five different perspectives: Importance, Insufficiency. Then, using the results of the survey and the academic research the implication about Product Lifecycle Management were derived. The significance of this study is that it derives the change areas and factors of the product life cycle management knowledge domain in preparation for the fourth industrial revolution according to the perspective of importance and insufficiency.

Next Generation Smart-City Facility Platform and Digital Chain (차세대 스마트도시 시설물의 플랫폼 정의와 디지털 체인)

  • Yang, Seung-Won;Kim, Jin-Wooung;Kim, Sung-Ah
    • Journal of KIBIM
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    • v.10 no.4
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    • pp.11-21
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    • 2020
  • With increasing interest and research on smart cities, there is also an increasing number of studies on urban facilities that can be built within smart cities. According to these studies, smart cities' urban facilities are likely to become high value-added industries. However, the concept of smart city is not clear because it involves various fields. Therefore, in this study, the definition of Next-Generation(N.G) Smart City Facilities with Digital Twin and Digital Chain is carried out through a multidisciplinary approach. Based on this, Next-Generation Smart City Facilities will be divided into High Value-Added Products and Big Data Platforms. Subsequently, the definition of the Digital Chain containing the data flow of the entire process built through the construction of the Digital Twin proceeds. The definitions derived are applied to the Next-Generation Noise Barrier Tunnel to ensure that data is exchanged at the Digital Twin stage, and to review the proposed configuration of the Digital Chain and Data Flow in this study. The platform definition and Digital Chain of Next-Generation Smart City Facilities proposed in this study suggest that it can affect not only the aspects of data management that are currently in the spotlight, but also the manufacturing industry as a whole.

A Comparative Analysis between Manufacturing and Transactional/Service Processes of Six Sigma Quality Improvement (제조부문과 사무간접/서비스부문의 6시그마 프로세스 개선활동 비교분석)

  • Yoon, Jae-Wook;Kim, Bo-Hyoung
    • Journal of Korean Society for Quality Management
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    • v.36 no.4
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    • pp.37-46
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    • 2008
  • There are big differences in six sigma projects between manufacturing processes and transactional/service processes. This paper analyzed the differences between the two areas by examining 18 six sigma case studies in Korean companies. To characterize six sigma case studies, step-by-step questions and check criteria were developed based on 12 step DMAIC methodology. On the basis of those characterized data, the differences between two areas were analyzed. Significant differences were found in the number of CTQs, validation of measurement systems, methods to determine improvement objectives, the methods to elicit improvement plans and types of control systems. The most significant difference was that statistical tools were widely used in manufacturing processes, but qualitative tools were used in transactional/service processes during improvement phase.

Strategies of smart factory building and Application of small & medium-sized manufacturing enterprises (스마트팩토리 구축전략과 중소.중견 제조기업의 적용 방안)

  • Park, Jong-Shik;Kang, Kyung-sik
    • Journal of the Korea Safety Management & Science
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    • v.19 no.1
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    • pp.227-236
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    • 2017
  • Smart Manufacturing Factory is a paradigm of the future lead to the fourth industrial revolution that led Germany and the United States. Now the automation of the production facility and won a certain degree, and through the process of integrating the entire process, including planning, design, distribution of information and communication technology products in emerging as a core competitiveness of the national economy. In particular, the company accelerated the smart factory building in order to improve the manufacturing industry, cost savings and productivity simply to incorporate internet of things(IoT),Robot, artificial intelligence, big data technology as a factory automation level of sophistication of the system and out to progress to the level that replaces human labor have. In this we should look at the trend of promoting domestic and foreign factories want to present these smart strategies for Korea.

A study on grinding and process design of Constant Velocity (등속조인트의 공정설계 및 연삭에 관한 연구)

  • Kim, Woo-Kang;Ko, Jun-Bin;Byun, Dong Hae
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.9 no.4
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    • pp.8-13
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    • 2010
  • The constant velocity internal grinding is a popular process for studying axle machine design and process in automobile industry. In this study, The program which gives the data of wheel size and truing diameter of ball groove is developed. As a result I obtained the data of grinding conditions makes good surface roughness get a grinding conditions. The grinding characteristics and conditions of constant velocity joint were investigated with respect to grinding feed, cutting depth, grinding time. At machine failure, the results were suddenly increased and the detailed surfaces were extremely obtained. Grinding condition was big more affected by grinding depth, grinding speed and grinding time.

A Study on Grinding for Inner Race (내륜 연삭에 관한 연구)

  • Kim, Woo-Kang;Kim, Geon-Hee
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.10 no.6
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    • pp.46-49
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    • 2011
  • The grinding is a popular process for studying constant velocity joint and process in automobile industry. In this study, The study gives the data of wheel type and grinding of inner race is developed. As a result I obtained the data of grinding conditions makes good surface roughness get a grinding conditions. The grinding characteristics and conditions of inner race were investigated with respect to grinding feed, cutting depth, grinding time. The results were suddenly increased and the detailed surfaces were extremely obtained. Grinding condition was big more affected by grinding time, grinding speed and grinding depth.

IoT-Based Device Utilization Technology for Big Data Collection in Foundry (주물공장의 빅데이터 수집을 위한 IoT 기반 디바이스 활용 기술)

  • Kim, Moon-Jo;Kim, DongEung
    • Journal of Korea Foundry Society
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    • v.41 no.6
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    • pp.550-557
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    • 2021
  • With the advent of the fourth industrial revolution, the interest in the internet of things (IoT) in manufacturing is growing, even at foundries. There are several types of process data that can be automatically collected at a foundry, but considerable amounts of process data are still managed based on handwriting for reasons such as the limited functions of outdated production facilities and process design based on operator know-how. In particular, despite recognizing the importance of converting process data into big data, many companies have difficulty adopting these steps willingly due to the burden of system construction costs. In this study, the field applicability of IoT-based devices was examined by manufacturing devices and applying them directly to the site of a centrifugal foundry. For the centrifugal casting process, the temperature and humidity of the working site, the molten metal temperature, and mold rotation speed were selected as process parameters to be collected. The sensors were selected in consideration of the detailed product specifications and cost required for each process parameter, and the circuit was configured using a NodeMCU board capable of wireless communication for IoT-based devices. After designing the circuit, PCB boards were prepared for each parameter, and each device was installed on site considering the working environment. After the on-site installation process, it was confirmed that the level of satisfaction with the safety of the workers and the efficiency of process management increased. Also, it is expected that it will be possible to link process data and quality data in the future, if process parameters are continuously collected. The IoT-based device designed in this study has adequate reliability at a low cast, meaning that the application of this technique can be considered as a cornerstone of data collecting at foundries.

A Case Study of e-Business Implementation in Part Manufacturing Industry(B2B in PCB Industry) (부품 제조 산업에서의 e-Business 구축 사례(PCB 산업의 B2B))

  • Bae, Joon-Soo;Bae, Eun-Hae;Cheong, Min-Chang;Shin, In-Ki;Park, Young-Chul
    • IE interfaces
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    • v.13 no.3
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    • pp.503-511
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    • 2000
  • The main theme of this research is a case of e-Business implementation in part manufacturing industry, especially in a PCB manufacturing company. The characteristics of part manufacturing industry are as follows. First, an ERP system runs as a legacy system that is ready to be combined with e-Business system. Secondly, the number of customers is very small. The customers are not many individuals but only a few big electronic enterprises that are strategically affiliated with the part manufacturing company. This means that the e-Business of the part manufacturing industry needs to focus on sharing pertinent information throughout the transactions with the customers, not on data-warehousing or data-mining customers' potential needs or requests. In this paper, we extracted e-Business opportunity domains from a PCB manufacturing company, a typical part manufacturing industry. We are intended to enhance information sharing between customers and the company, and provide functions of transactions necessary in the whole value chain from order to shipment. Implementing the e-Business system on the Web can increase the visibility of customers, and further, the company can be transformed into an extended enterprise where the relationship with the customers becomes very close and interleaved. Also, the Cyber Office functionality of the e-Business system can support the salespersons effectively, so that they can spend more time on customer satisfaction. Such efforts, in the future, can be a basis for active adaptation to the industry transformations such as forming e-community and participating in the marketplace.

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