• 제목/요약/키워드: Data Product

검색결과 6,550건 처리시간 0.033초

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

  • Lim, Ik-Sung;Koo, Il-Sup;Kim, Tae-Sung
    • 산업경영시스템학회지
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    • 제23권60호
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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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The Relationships between Product Quality Cues and Perceived Values based on Gender Differences at a Food Select Shop

  • Yim, Myung-Seong
    • 산경연구논집
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    • 제11권10호
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    • pp.59-73
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    • 2020
  • Purpose: The ultimate purpose of this work is to investigate gender differences in the relationships between product quality cues and perceived values at a food select shop. Specifically, this study examines the effects of internal and external cues, which are indicators of product quality, on emotional and social values based on gender differences. Research design, data and methodology: In this study, a questionnaire technique was used to collect the data necessary to test the proposed model. 183 data were collected through this technique. PLS SEM (Partial Least Squares Structured Equation Model) was used to test the research model. Results: First, there is no gender difference between intrinsic cue and emotional value. When using male and female data, there was no significant causal relationship between intrinsic cues and emotional values. Second, we found no gender difference between intrinsic cue and social value. When analyzed with female data, there was no significant causal relationship between intrinsic cue and social value. On the other hand, in the case of men, it was found that a weak causal relationship exists. Third, this study found gender difference between extrinsic cue and emotional value. In the case of men, it was found that a weak causal relationship exists, whereas in the case of women, a strong causal relationship exists between extrinsic cue and emotional value. Fourth, we found gender difference between extrinsic cue and social value. In the case of men, there was no causal relationship, whereas in the case of women, there was a strong causal relationship between extrinsic cue and social value. Finally, we found that there are moderating roles of gender in the relationship between external cues and perceived quality. Conclusions: As a result of analysis, it is necessary to focus on extrinsic clues of product in order to increase the perceived emotional and social values of women. On the other hand, in order to improve the perceived emotional and social values of men, it is necessary to pay attention to both intrinsic and extrinsic cues of product. Therefore, it is necessary to consider what clues and values are important to core customers.

Product Variety Modeling Based on Formal Concept Analysis

  • Kim, Tai-Oun
    • Industrial Engineering and Management Systems
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    • 제9권1호
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    • pp.1-9
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    • 2010
  • Increasing product variety based on product family and product platform provides a company with a competitive advantage over its competitors. As products become more complex, short-life cycled and customized, the design efforts require more knowledge-intensive, collaborative and coordinating efforts for information sharing. By sharing knowledge, information, component and process across different families of products, the product realization process will be more efficient, cost-effective and quick-responsive. Formal Concept Analysis (FCA) is used for analyzing data and forming semantic structures that are formal abstractions of concepts of human thoughts. A Web Ontology Language (OWL) is designed for applications that need to process the content of information instead of simply presenting information to humans. OWL also captures the evolution of different components of the product family. The purpose of this paper is to develop product variety modeling to increase the usefulness of common platform. In constructing and analyzing product ontology, FCA is adopted for conceptual knowledge processing. For the selected product family, product variety Ontology is constructed and implemented using prot$\'{e}$g$\'{e}$-2000.

의류제품에 대한 소비자만족 형성과정 -소비자관여, 제품성과, 소비감정을 중심으로- (Consumer Satisfaction Formation Process of Clothing -Based on Consumer Involvement, Product Performance, and Consumption Emotion-)

  • 김지영;박재옥
    • 한국의류학회지
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    • 제26권5호
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    • pp.663-674
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    • 2002
  • The objectives of this study were 1) to ascertain whether there was a difference in product performance (expressive or instrumental), which consumer recognized after using, related to consumer involvement toward clothing, 2) to clarify the effect of product performance on consumption emotion(positive or negative), 3) to investigate the effect of consumption emotion on satisfaction, and 4) to find out whether product performance had a direct effect on satisfaction toward product. The study was conducted in three steps. Through the two steps, measurement instruments were developed. At the last step, judgement sampling method were utilized to collect the data and subjects were 614 university students. Confirmatory factor analysis and structural equation model analysis were used to analyze the data. The results were as follows: 1) Consumer involvement had an effect on product performances but it was related to the expressive product performance more than to the instrumental product performance. 2) Product performance had positive influence on positive consumption emotion, while it had negative influence on negative consumption emotion. The results revealed that there were significant relationships between product performance and consumption emotion. 3) Positive consumption emotion had a positive effect on consumer satisfaction, on the other hand negative consumption emotion had a negative effect on consumer satisfaction. 4) Although the direct effects of product performances on satisfaction were larger than the indirect effects, product performance was greatly influential in consumption emotion and consumption emotion was strongly related to consumer satisfaction. Therefore, consumption emotion is an important determinant variable in the process of consumer satisfaction.

빅 데이터를 활용한 애완동물 상품 추천 시스템 구현 (Implementation of a pet product recommendation system using big data)

  • 김삼택
    • 한국융합학회논문지
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    • 제11권11호
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    • pp.19-24
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    • 2020
  • 최근, 애완동물의 급격한 증가로 애완동물의 건강상태 체크와 다양하게 수집된 데이터를 활용하여 사료 추천 등 통합적인 애완동물관련 개인화 상품 추천 서비스가 요구된다. 본 논문은 빅 데이터 기술을 활용하여 애완동물관련 데이터 수집, 전처리, 분석, 관리등 다양한 개인화서비스를 할 수 있는 상품 추천시스템을 구현한다. 먼저, 애완동물이 착용하고 있는 센서 정보와 고객의 구매 패턴, SNS 정보를 수집해 데이터베이스에 저장하고 통계적 분석을 활용하여 사료제작, 애완동물 건강관리 등 맞춤형 개인화 추천 서비스가 가능한 플랫폼을 구현한다. 본 플랫폼은 유사도가 분석될 상품과 상품정보에 대한 유사도 상품 정보를 출력하고 최종적으로 추천 분석한 결과를 출력하여 고객에게 정보를 제공 할 수 있다.

워드 임베딩을 이용한 아마존 패션 상품 리뷰의 사용자 감성 분석 (User Sentiment Analysis on Amazon Fashion Product Review Using Word Embedding)

  • 이동엽;조재춘;임희석
    • 한국융합학회논문지
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    • 제8권4호
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    • pp.1-8
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    • 2017
  • 현대 사회에서 패션 시장의 규모는 해외와 국내 모두 지속적으로 증가하고 있다. 전자상거래를 통해 상품을 구입하는 경우 다른 소비자들이 작성한 상품에 대한 평가 데이터는 소비자가 상품의 구입 여부를 결정하는데에 영향을 미친다. 기업의 입장에서도 상품에 대한 소비자의 평가 데이터를 분석하여 소비자의 피드백을 반영한다면 기업의 성과에 긍정적인 영향을 미칠 수 있다. 이에 본 논문에서는 아마존 패션 상품의 리뷰 데이터를 학습하여 형성된 워드임베딩 공간을 이용하여 사용자의 감성을 분석하는 모델을 구축하는 방법을 제안한다. 실험은 아마존 리뷰 데이터 570만건을 학습하여 형성된 워드임베딩 공간을 이용하여 긍정, 부정 리뷰 데이터의 개수에 따라 총 3개의 SVM 분류기 모델을 학습하는 방식으로 진행하였다. 실험 결과 긍정 리뷰 데이터 5만건, 부정 리뷰데이터 5만건을 이용하여 SVM 분류기를 학습하였을 때 88.0%로 가장 높은 정확도(accuracy)를 나타냈다.

선박 및 해양 구조물에 있어서 유지보수용 데이터 교환을 위한 준표준 분석과 사례 구현 (Pseudo-standard and Its Implementation for the Maintenance Data of Ship and Offshore Structures)

  • 손금준;이장현;이정렬;한은정
    • 한국CDE학회논문집
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    • 제18권4호
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    • pp.267-274
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    • 2013
  • This study focuses on the data schema and data content, which includes maintenance data, data structures and illustration data relevant with the maintenance process of ship and offshore structures. Product lifecycle management (PLM) is expected to encompass all the product data generated for the operation and maintenance information as well as the design and production. This paper introduces a data exchange schema in PLM of ship and offshore, serving as the basis for the role of standards required by the middle-of-life PLM. Also this paper identifies a typology of standards relevant to PLM that addresses the schema of evolving standards and identifies a XML schema supporting the exchange of data related with maintenance operations. Technical document based on standards in accordance with S1000D and Shipdex is explained. A case study illustrating the use of standard data exchange and technical document is presented.

클릭스트림 데이터를 활용한 전자상거래에서 상품추천이 고객 행동에 미치는 영향 분석

  • 이홍주
    • 한국경영정보학회:학술대회논문집
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    • 한국경영정보학회 2008년도 춘계학술대회
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    • pp.135-140
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    • 2008
  • Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.

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홀로그래픽 저장장치를 위한 수정된 로그-유사도비를 이용한 LDPC-LDPC 곱부호 (LDPC-LDPC Product Code Using Modified Log-likelihood Ratio for Holographic Storage System)

  • 정성권;이재진
    • 전자공학회논문지
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    • 제54권6호
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    • pp.17-21
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    • 2017
  • 홀로그래픽 데이터 저장장치는 높은 데이터 전송률과 저장용량이 매우 크기 때문에 차세대 저장장치 후보 중 하나이다. 하지만 홀로그래픽 데이터 저장장치의 오류요인으로는 인접 페이지간 간섭 및 2차원 인접 심볼간 간섭이 있다. 또한 물리적 영향에 의해 발생되는 연집오류가 있다. 본 논문에서는 이러한 연집오류를 정정하고 성능을 향상시키기 위해 수정된 로그-우도비값과 부가적 정보를 반복적으로 사용하는 방식을 제안한다. 제안하는 LDPC 곱부호는 일반적인 LDPC 부호와 비교하여 BER이 $10^{-5}$일 때, 약 0.5dB 성능 향상을 보였다.

Data Segmentation for a Better Prediction of Quality in a Multi-stage Process

  • Kim, Eung-Gu;Lee, Hye-Seon;Jun, Chi-Hyuek
    • Journal of the Korean Data and Information Science Society
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    • 제19권2호
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    • pp.609-620
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    • 2008
  • There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

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