• Title/Summary/Keyword: Expanded Product Data Information

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Quality and Productivity Improvement by Clustering Product Database Information in Semiconductor Testing Floor

  • Lim, Ik-Sung;Koo, Il-Sup;Kim, Tae-Sung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.60
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    • pp.73-81
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    • 2000
  • The testing processes for VLSI finished devices are considerably complex because they require different types of ATE to be linked together. Due to the interaction effect between two or more linked ATEs, it is difficult to trace down the cause of the unexpected longer ATE setup time and random yields, which frequently occur in the VLSI circuit-testing laboratory. The goal of this paper is to develop and demonstrate the methodology designed to eliminate the possible interaction factors that might affect the random yields and/or unexpected longer setup time as well as increase the productivity. The statistical method such as design of experiment or multivariate analysis cannot be applied to the final testing floor here directly due to the environmental constraints. Expanded product data information (PDI) is constructed by combining product data information and ATE control information. An architecture utilizing expanded PDI is designed, which enables the engineer to conduct statistical approach investigation and reduce the setup time, as well as increase yield.

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An Expanded Website Quality Model in Online Shopping Malls for Developing Satisfaction and Loyalty: The Moderating Effect of Gender

  • Sang Min KIM;Tian JIAQI;Yong-Ki LEE
    • Journal of Distribution Science
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    • v.22 no.5
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    • pp.93-104
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    • 2024
  • Purpose: This study used the SORmodel (or cue utilization theory) to examine the impact of expanded quality factorsincluding product quality on customer satisfaction, attitude, and behavioral loyalty. This study examined the moderating effect of gender on the customer satisfaction-attitudinal and behavioral loyalty relationship. Research design, data, and methodology: 364 respondents were collected through an online survey and analyzed using the SmartPLS 4.0 program. Results: The findings show that product quality, along with system quality and service quality, are key determinants of customer satisfaction. In addition, this study shows that the relationship between customer satisfaction and attitudinal loyalty (repurchase and word-of-mouth intention) does not differ depending on gender, but the relationship between customer satisfaction and behavioral loyalty (share-of-visit and share-of-wallet) is stronger for women than for men. Conclusions: This research integrates concepts from environmental psychology and marketing focusing on website quality (information, system, service, and product), as well as satisfaction, attitudinal and behavioral loyalty. Online shopping mall practitioners must systematically analyze and assess the quality of online shopping, a pivotal factor driving customer satisfaction, attitude, and behavioral loyalty. Acknowledging the influence of gender on consumers' online purchasing behavior can aid online retailers in devising tailored e-commerce marketing strategies aimed at attracting and retaining customers.

Endpoint Detection Using Both By-product and Etchant Gas in Plasma Etching Process (플라즈마 식각공정 시 By-product와 Etchant gas를 이용한 식각 종료점 검출)

  • Kim, Dong-Il;Park, Young-Kook;Han, Seung-Soo
    • Journal of IKEEE
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    • v.19 no.4
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    • pp.541-547
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    • 2015
  • In current semiconductor manufacturing, as the feature size of integrated circuit (IC) devices continuously shrinks, detecting endpoint in plasma etching process is more difficult than before. For endpoint detection, various kinds of sensors are installed in semiconductor manufacturing equipments, and sensor data are gathered with predefined sampling rate. Generally, detecting endpoint is performed using OES data of by-product. In this study, OES data of both by-product and etchant gas are used to improve reliability of endpoint detection. For the OES data pre-processing, a combination of Signal to Noise Ratio (SNR) and Principal Component Analysis (PCA),are used. Polynomial Regression and Expanded Hidden Markov model (eHMM) technique are applied to pre-processed OES data to detect endpoint.

Fashion consumers' information search and sharing in new media age (뉴 미디어 시대 패션소비자의 정보 탐색과 공유)

  • Shin, HyunJu;Lee, Kyu-Hye
    • The Research Journal of the Costume Culture
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    • v.26 no.2
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    • pp.251-263
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    • 2018
  • As mobile shopping has increased in the new media age, fashion consumers' decision making and product consumption processes have changed. The volume of consumer-driven information has expanded since media and social networking sites have enabled consumers to share information they obtain. The purpose of this study was to determine the factors affecting information searching strategies and information sharing about fashion products. An online survey collected data from 466 respondents, relating to the influence of product price level and consumer SNS commitment level on information search and information sharing. Experimental design of three product price level and two consumer SNS commitment level was used. Analysis of the data identified factors in fashion information searching as ongoing searching, prepurchase web portal information search, and prepurchase marketing information search. For low-price fashion products, prepurchase product-detail influenced intention to share information. For mid-priced products, ongoing search significantly affected intention to share information. Both ongoing search and prepurchase marketing information search showed significant effects for high-price products. Consumers who are more committed to SNS engaged in significantly more searching in all aspects of information search factors. Significant interaction effect was detected for consumer SNS commitment level and product price level. When consumers with low consumer SNS commitment search for information on lower-priced fashion products, they are less likely do a prepurchase web portal information search.

A study on the integrated data modeling for the plant design management system and the plant design system using relational database (관계형 데이터베이스를 이용한 PDMS/PDS의 통합 데이터 모델링에 관한 연구)

  • 양영태;김재균
    • Journal of Ocean Engineering and Technology
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    • v.11 no.3
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    • pp.200-211
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    • 1997
  • Most recently, offshore Engineering & Construction field is concerned about integration management technology such as CIM(Computer Integrated Manufacturing), PDM(Product Data Management) and Enterprise Information Engineering in order to cope with the rapid change of engineering and manufacturer specification as per owner's requirement during construction stage of the project. System integration and integrated data modeling with relational database in integration management technology improve the quality of product and reduce the period of the construction project by reason of owing design information jointly. This paper represents the design methodology of system integration using Business Process Reengineering by the case study. The case study is about the offshore plant material information process from front end engineering design to detail engineering for the construction and the basis of monitoring system by integrating and sharing the design information between the 2D intelligent P&ID and 3D plant modeling using relational database. As a result of the integrated data modeling and system integration, it is possible to maintain the consistency of design process in point of view of the material balancing and reduce the design assumption/duration. Near future, this system will be expanded and connected with the MRP(Material Requirement Planing) and the POR (Purchase Order Requisition) system.

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A Case Study on Product Production Process Optimization using Big Data Analysis: Focusing on the Quality Management of LCD Production (빅데이터 분석 적용을 통한 공정 최적화 사례연구: LCD 공정 품질분석을 중심으로)

  • Park, Jong Tae;Lee, Sang Kon
    • Journal of Information Technology Services
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    • v.21 no.2
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    • pp.97-107
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    • 2022
  • Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

A Software Architecture Life Cycle Model Based on the Program Management Perspective : The Expanded Spiral Model (프로그램 관리 관점에 기반을 둔 소프트웨어 아키텍처 생애주기 모델 : 확장된 나선형 모델)

  • Koh, Seokha
    • Journal of Information Technology Applications and Management
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    • v.20 no.2
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    • pp.69-87
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    • 2013
  • The expanded spiral model in this paper consists of five processes of architecture design, architectural construction, architectural maintenance, operation, and architectural management. The former four processes are executed alternatively, while the latter architectural management process is executed continuously interacting with the other processes during the whole life cycle of the system. The expanded spiral model provides a conceptual framework to sort discussions of architectural degeneration into those of product-oriented processes and those of management processes, making it possible to incorporate the models and body of knowledge about project and program management especially those of Project Management Institute, into discussions of architectural degeneration. A good architecture decomposes the software-intensive system into components mutually interacting in a well-formed structure. The architecture design process and the architectural construction process together create the object system with well-designed architecture. The architectural maintenance process prevents the implemented architecture deviate from the designed architecture. The architectural management process monitors the changes of requirements including architecturally significant requirements, supports the other processes to be executed reflecting various perspectives of stake-holders, and creates and documents the reasons of architectural decisions, which is considered as a key element of the architecture.

A Study on the Customer Relationship Management Method Using Real-Time IoT Data (실시간 IoT 데이터를 활용한 고객 관계 관리 방안에 관한 연구)

  • Bae, Ji Won;Baek, Dong Hyun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.2
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    • pp.69-77
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    • 2019
  • As information technology advances, the penetration of smart devices connected to the Internet, such as smart phone and tablet PC, has rapidly expanded, and as sensor prices have fallen the Internet of Things has begun to be introduced in the industry. Today's industry is rapidly changing and evolving, requiring companies to respond to the new paradigm of business. In this situation, companies need to actively manage and maintain customer relationships in order to acquire loyal customers who bring them a high return. The purpose of this study is to suggest a method to manage customer relationship using real time IoT data including IoT product usage data, customer characteristics and transaction data. This study proposes a method of segmenting customers through RFM analysis and transition index analysis. In addition, a real-time monitoring through control charts is used to identify abnormalities in product use and suggest ways of differentiating marketing for each group. In the study, 44 samples were classified as 9 churn customers, 10 potential customers, and 25 active customers. This study suggested ways to induce active customers by providing after-sales benefit for product reuse to a group of churn customers and to promote the advantages or necessity of using the product by setting the goal of increasing the frequency of use to a group of potential customers. Finally, since the active customer group is a loyal customer, this study proposed an one-on-one marketing to improve product satisfaction.

Evaluation Factors of PDM Systems (PDM 시스템의 평가에 관한 연구)

  • 강석호;김영호;황영헌;김대환
    • The Journal of Society for e-Business Studies
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    • v.1 no.1
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    • pp.209-226
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    • 1996
  • System Intergration (SI) has resently been conceived as one df the most important tools for enforciong and reinforcing the competitiveness of an enterprise. A major concern of SI lies in sharing many types of information, such as engineering, production, finance, marketing, and so on. Product Data Management (PDM) systems are mainly concerned with product- related information, and also support a large portion of the Commerce At Light Speed (CALS) straitegy. PDM systems receive a great amount df attention form industry, A variety of PDM solutions have been introduced for the last few years, and its market has expanded very fast with an annual growth of 30%. However, in general, it is not an easy task to choose a right PDM solution for a particular company. A major purpose of this paper is to provide essential factors in evaluating PDM systems. While developing the factors. we consider the expected future trend of PDM technologies and three types of PDM-based intergration (frontward, rearward, and sideward integrations). We Propose to carry out the evaluation process in two fold. An overall evaluation is performed first to narrow down many alternatives into a few candidate systems, and then a detailed technical evaluation step follows to determine the final solution. A number of influencing factors are categorized and described in each of these steps.

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SNS 보완을 위한 DBR 스케줄러 설계 및 개발에 관한 연구

  • 전태준;황인원
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2000.11a
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    • pp.333-351
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    • 2000
  • In this paper, for DBR scheduler development I have designed prototype by using methodology and gave you some research about system integration to apply DBR sch onto the plan establishment phase of SNS system. DBR manage the constraints and the working speed of each product resource t frequently and today its role is tend to be much expanded by inserting mode information system such as MRPⅡ, ERP and SCM. So in this paper I have analyzed designed the business and inner processor for DBR scheduler development then on t of the analyzed data I have developed the simulator And moreover I will suggest method to insert it into SNS system modules. For system development I have used Delphi 4.0, Microsoft Access(DBMS) and QuickR for making report such as ordering, working directions, progress chart and inventor

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