• Title/Summary/Keyword: smart factory

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Smart Factory Promotion and Operation Analysis in the 4th Industrial Revolution Environment

  • Lee, Seong-Hoon;Lee, Dong-Woo
    • International journal of advanced smart convergence
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    • v.11 no.3
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    • pp.42-48
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    • 2022
  • Currently, the world is facing severe inflation due to Corona and the war in Ukraine, and it is causing a lot of difficulties for us. Companies are facing a lot of restrictions on their economic activities compared to the past due to supply chain problems and foreign exchange rates. In this situation, many countries have been implementing various smart factory promotion projects to secure competitiveness through productivity improvement in the manufacturing industry. In this study, the contents of smart factory promotion in major countries were reviewed, and problems raised about the implementation of smart factory in Korea, which are being implemented based on this, were described. It is most reasonable to judge the success of a smart factory by the achievement of the performance indicators presented at the time of the project. Therefore, based on the performance index of the business, which is a key factor in determining the success or failure of a smart factory, we investigated whether the company's smart factory promotion can be carried out successfully through examples

The Effect of UTAUT, Dynamic Capabilities, Utilization of Smart Factory on the Intention to Continue Using: Technology Perception Moderating Effect

  • Jin-Kwon KIM;Kyung-Soo LEE
    • The Journal of Economics, Marketing and Management
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    • v.11 no.6
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    • pp.43-55
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    • 2023
  • Purpose: The purpose of this study was to identify the relationship between smart factory utilization and continued use intention between UTAUT, dynamic capabilities of smart factory construction companies and present the company's strategic direction. Research design, data, and methodology: In this study, a structured research model was derived to confirm the relationship between UTAUT, dynamic capabilities, smart factory utilization and continued use intention and the difference according to Technology perception. For analysis a total of 223 valid questionnaires from e-commerce users were used. Confirmatory factor analysis, correlation analysis, and structural equations were conducted to verify. Results: Both UTAUT, dynamic capabilities had a significant effect on smart factory utilization as well as continued use intention. It was found that the relationship between UTAUT, dynamic capabilities, smart factory utilization, and continued use intention. differed depending on the technology perception. Conclusions: Organizational members utilize the smart factory in anticipation of effects such as work performance and various improvements. Smart factory data will be used continuously when it is useful for business processes and operations. It is necessary to establish strategies and provide training to improve the technical level and capabilities of organizational members. Through this, a strategy is needed that can be continuously used by utilizing the information obtained through smart factory to improve work efficiency, productivity and efficiency increase is needed

Application of Smart Factory Model in Vietnamese Enterprises: Challenges and Solutions

  • Quoc Cuong Nguyen;Hoang Tuan Nguyen;Jaesang Cha
    • International journal of advanced smart convergence
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    • v.13 no.2
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    • pp.265-275
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    • 2024
  • Smart factory is a remarkable development from traditional manufacturing systems to data-based smart manufacturing systems that can connect and process data continuously, collected from machines, production equipment to production and business processes, capable of supporting workers in making decisions or performing work automatically. Smart factory is the key and center of the fourth industrial revolution, combining improvements in traditional manufacturing activities with digital technology to help factories achieve greater efficiency, contributing to increased revenue and reduce operating costs for businesses. Besides, the importance of smart factories is to make production more quality, efficient, competitive and sustainable. Businesses in Vietnam are in the process of learning and applying smart factory models. However, the number of businesses applying the pine factory model is still limited due to many barriers and difficulties. Therefore, in this paper we conduct a survey to assess the needs and current situation of businesses in applying smart factories and propose some specific solutions to develop and promote application of smart factory model in Vietnamese businesses.

The implementation of Network Layer in Smart Factory

  • Park, Chun Kwan;Kang, Jeong-Jin
    • International journal of advanced smart convergence
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    • v.11 no.1
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    • pp.42-47
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    • 2022
  • As smart factory is the factory which produces the products according to the customer's diverse demand and the changing conditions in it, it can be characterized by flexible production, dynamic reconstruction, and optimized production environment. To implement these characteristics, many kind of configuration elements in the smart factory should be connected to and communicated with each other. So the network is responsible for playing this role in the smart factory. As SDN (Software Defined Network) is the technology that can dynamically cope with the explosive increasing data amount and the hourly changing network condition, it is one of network technologies that can be applied to the smart factory. In this paper, we address SDN function and operation, SDN model suitable for the smart factory, and then performs the simulation for measuring this model.

Development of Smart Factory Diagnostic Model Reflecting Manufacturing Characteristics and Customized Application of Small and Medium Enterprises (제조업 특성을 반영한 스마트공장 진단모델 개발 및 중소기업 맞춤형 적용사례)

  • Kim, Hyun-Deuk;Kim, Dong-Min;Lee, Kyung-Geun;Yoon, Je-Whan;Youm, Sekyoung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.3
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    • pp.25-38
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    • 2019
  • This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

Case Study on the Implementation of Facility AI Platform for Small and Medium Enterprises of Korean Root Industry (뿌리업종 중견중소기업의 설비 AI 플랫폼 구축에 관한 사례연구)

  • Lee, Byong Koo;Moon, Tae Soo
    • The Journal of Information Systems
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    • v.32 no.3
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    • pp.205-224
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    • 2023
  • Purpose This study investigates the impact of organizational characteristics on organizational performance through case studies of smart factory implementation in the context of Korean small and medium Enterprises (SMEs). To achieve this goal, this study adopts the smart factory index of KOSMO (Korea Smart Manufacturing Office) established by Korean Ministry of SMEs and Startups. We visited 3 firms implemented smart factory projects. This study presents the results of field study in detail with evaluation criteria on how organizational competences like AI technology adoption and facility automation can be exploited to positively influence organizational performance through smart factory implementation. Design/methodology/approach There are not so many results of empirical studies related to smart factories in Korea. This is because organizational support and user involvement are required for facility AI platform service beyond factory automation after the start of the 4th Industrial Revolution. Korean government's KOSMO (Korean Smart Manufacturing Office) has developed and proposed a level measurement index for smart factory implementation. This study conducts case studies based on the level measurement method proposed by KOSMO in the process of conducting case studies of three companies belonging to the root and mechanic industries in Korea. Findings The findings indicate that organizational competences, such as facility AI platform adoption and user involvement, are antecedents to influence smart factory implementation, while smart factory implementation has significant relationship with organizational performance. This study provides a better understanding of the connection between organizational competences and organizational performance through smart factory case studies. This study suggests that SMEs should focus on enhancing their organizational competences for improving organizational performance through implementing smart factory projects.

A Study on Strategic Utilization of Smart Factory: Effects of Building Purposes and Contents on Continuous Utilization (스마트 팩토리의 전략적 활용 연구: 구축 목적 및 내용이 지속적 활용에 미치는 영향)

  • Oh, Ju-Hwan;Kim, Ji-Dae
    • Korean small business review
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    • v.41 no.4
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    • pp.1-36
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    • 2019
  • The purpose of this study is to identify the relationships among purposes and contents of smart factory building and continuous utilization of smart factory. Specifically, this study identifies two types of purposes of smart factory building as follows: (1) improving productivity, (2) increasing flexibility. In this study, three aspects of smart factory building contents were suggested like this: (1) automation area (facility automation vs. work automation), (2) big data system focus (radical transformation vs. incremental improvement), and (3) value chain integration area (internal value chain integration vs. external value chain integration). In addition, we looked at how firm size moderates the purposes - contents - continuous utilization of smart factory relationship. A questionnaire survey was conducted on 151 manufacturing companies. More specifically, out of 151 companies, 100 are small-and-medium-sized enterprises and 51 large-sized enterprises. All questionnaires were targeted at companies with Smart Factory level above level 2. The analysis results of this study using Smart PLS statistical programs are as follows. First, the purposes of smart factory building including increasing productivity and flexibility had positive impacts on all of the contents of smart factory building. Second, all of smart factory building contents had positive impacts on the continuous use of smart factory except big data system for incremental improvement of manufacturing process. Third, the impacts of smart factory building purposes implementation on smart factory building contents varied depending on whether the purpose is productivity improvement or flexibility. Fourth, it was founded that firm size moderated the relationships of purposes - contents - continuous utilization of smart factory in such a way that large-sized firms tend to empathize the link between flexibility and smart factory building contents for continuous use of smart factory, while small-and-medium-sized-firms emphasizing the link between productivity and smart factory building contents. Most of the previous studies have focused on presenting current smart factory deployment cases. However, it is believed that this research has made a theoretical contribution in this field in that it established and verified a research model for the smart factory building strategy. Based on the findings from a working-level perspective, corporate practitioners also need to have a different approach to smart factory building, which should be emphasized depending on whether their purpose of building smart factory is to increase productivity or flexibility. In particular, since the results of this study identify the moderating effect of firm size, it is deemed necessary for firms to implement a smart factory building strategy suitable for their firm size.

The Built of Smart Factory Using Sensors and Virtual Process Design (센서와 가상 공정설계를 활용한 스마트 팩토리 구축)

  • So, Byeong-Eob;Shin, Sung-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.6
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    • pp.1071-1080
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    • 2017
  • Recently, the terms of the 4th Industrial Revolution and the Smart Factory are often heard through news and media. But most of the companies that are parties are not interested. Because there is no specific guidance on how to build Smart Factory and information about Smart Factory. The built of the Smart Factory should be carried out in accordance with the size of the company considering the purpose of the introduction. In the existing study, they analyzed successful cases of building Smart Factory in Korea As a result, in the case of large-size firms, it is an effective strategy that expanding from a model factory to whole factory for successful Smart Factory building. In addition, in the case of medium and small-size firms, it is an effective strategy that upgrading from low-level step to high-level step for successful Smart Factory building. In this study, selecting medium and small-size firms, and bottleneck section and processes requiring improvement are identified through 3D virtual process design, and then install sensors. Finally, after analyzing the data collected through the sensor, we will improve the process and build Smart Factory with improved productivity.

Standardization Strategy of Smart Factory for Improving SME's Global Competitiveness (중소기업의 글로벌 경쟁력 제고를 위한 스마트공장 표준화 전략)

  • Chung, Sunyang;Jeon, Joong Yang;Hwang, Jeong-Jae
    • Journal of Korea Technology Innovation Society
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    • v.19 no.3
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    • pp.545-571
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    • 2016
  • The development of ICT brings a big change in manufacturing industries, and new information technology such as IoT, AR, and big data was applied on manufacturing process. As a result, the concept of smart factory has been introduced as a new manufacturing paradigm. In fact advanced countries like USA, Germany, and Japan have actively introduced smart factory in their manufacturing industries such as electronic, automobile, machinery, to improve production efficiency and quality. The manufacturing environment has been changed into flexible system, so that smart factory will be leading future manufacturing industries. Thes changes have more severe influence on Korean manufacturing industries. Mny industrial companies, have a strong interest in smart factory and they, particularly big enterprises, have been adopting smart factory to increase their manufacturing efficiencies. However, Korean small and medium-sized enterprises (SMEs) have many financial and technological difficulties so that the diffusion of smart factory in Korean SMEs has not been satisfiable up to present. However, smart factory is very important for enhancing their competitiveness in global market. Therefore, this study aims at identifying the standardization strategy of smart factory in so-called Korean 'roots industry' by presuming that the standardization will activate the diffusion of smart factory among Korean SMEs. For this purpose, first, this study examines the competitiveness of SMEs, especially in 'roots industry' and identifies the necessity of diffusion of smart factory among those SMEs. Second, based on the active review on the existing literature, this study identifies four factor groups that would influence the adoption or diffusion of standardized smart factory. They are technological, organizational, industrial and policy factors. Third, using those four factors, this study made two comprehensive case analyses on the adoption and diffusion of smart factory. These two companies belong to molding sector which is one of the important six sectors in 'root industry'. Finally, based on the theoretical and empirical analyse, this study suggests four strategies for activating the standardization of smart factory; international standardization, government-leading standardization, firm-leading standardization, and non-standardization.

Operational Problem Analysis and Improvement Plan in the Smart Factory Promotion Process

  • Lee, Seong-Hoon;Lee, Dong-Woo
    • International journal of advanced smart convergence
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    • v.11 no.4
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    • pp.273-278
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    • 2022
  • Uncertainty is increasing around the world due to COVID-19 and Ukraine crisis. In this situation, each company is making countless efforts to survive. In Korea, smart factory projects targeting small and medium-sized businesses with difficulties have been continuously promoted. As for the smart factory business that has been promoted so far, the base expansion of the smart factory is also steadily increasing as the number of companies carrying out the project is increasing. It was also found that it contributed to productivity improvement and quality improvement. Despite these positive aspects, difficulties and operational problems are also appearing in the process of promoting smart factories. In this study, we investigated and analyzed operational problems and difficulties in the process of promoting smart factories. In addition, improvement plans for problems were presented according to the contents of this analysis, and improvement plans were presented by classifying them into introduction and supply companies, considering that the smart factory business is formed in the form of a consortium between introduction and supply companies.