• Title/Summary/Keyword: 샘플링검사

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A Study on the Determination of the Economic Sample Size of the Attribute Acceptance Sampling Plans for Destructive Testing (파괴시험 계수형 샘플링검사 경제적 시료 크기 결정에 관한 연구)

  • 김병재
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.4 no.5
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    • pp.11-14
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    • 1981
  • This study intends to decide the economic sample size based on the cost of sampling Inspection for destructive testing. The marginal percent defective is used as the lot tolerance percent defective (LTPD), and the Newton's iterative method is adopted to calculate the optimum sample size(n), given by the consumer's risk($\beta$ - risk) and the acceptance number(c).

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A Study on the Economical Design of Sampling Inspection Method by Attribute (계수선별형 샘플링검사의 경제성에 관한 연구)

  • 김진수;권혁윤
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.41
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    • pp.147-156
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    • 1997
  • This Study deals with the problem of determining a minimum cost sampling inspection plan for destructive testing by attribute. The linear cost model(LCM) is constructed under the assumption that unit cost, destructive testing cost, producer's risk cost, consumer's risk cost are given. For the solution from the LCM, we assumed the uniform distribution as a prior distribution.

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A Study on the Economical Design of Sampling Inspection Plan by Attribute (계수선별형(計數選別型) 샘플링검사(檢査)의 경제성(經濟性)에 관한 연구(硏究))

  • Lee, Byeong-Geun;Jeon, Jae-Gyeong
    • Journal of Korean Society for Quality Management
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    • v.13 no.2
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    • pp.48-55
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    • 1985
  • This paper intends to decide the optimum OC curves and to find the minimized ${\alpha}$, ${\beta}$-risk based upon the Linear Cost Model (L.C.M.) for the destructive or nondestructive acceptance sampling inspection plan. For the solution from the L.C.M., we assume the uniform distribution as a Prior-distribution and use numerical analysis by computer.

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Variables Sampling Plans for the Weibull Distribution under Progressive Failure Censoring (점진적 정수 중단 하에서의 와이블분포에 대한 계량형 샘플링검사)

  • Lee, Sang-Ho;Jeon, Chi-Hyeok;Balamurali, S.
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.922-926
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    • 2005
  • Progressively censored variables sampling plans are proposed for the lot acceptance of parts whose life follows Weibull distribution with known shape parameter. Progressive type-II censoring gives us not only time to failure but also degradation information. So, one can construct more flexible and more cost effective sampling plans. Design parameters of our sampling plan are determined by using the usual two-point approach.

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Continuous Sampling Plans with Prior Distribution (불량율(不良率)의 사전분포(事前分布)를 고려(考慮)한 연속생산형(連續生産型) 샘플링검사(檢査))

  • Yun, Wan-Cheol;Bae, Do-Seon
    • Journal of Korean Institute of Industrial Engineers
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    • v.5 no.1
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    • pp.53-57
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    • 1979
  • The concept of AOQL in designing Dodge's continuous sampling plans is modified to include probabilistic consideration reflecting the prior knowledge about the process average fraction defectives, and a new design criterion called AOQL, which eliminates some of the drawbacks of the AOQL criterion is proposed. AOQL, approach provides more economical sampling plans in many cases, and can be used even when only limited amount of prior information is available.

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The Study on the Failure Rate Sampling Plan Considering Cost (비용을 고려한 신뢰성 샘플링검사 설계에 관한 연구)

  • 조재립
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.59
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    • pp.97-103
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    • 2000
  • This study considers the design of life test sampling inspection plans by attributes for failure rate level qualification at selected confidence level. The lifetime distribution of products is assumed to be exponential. MIL-STD-690C and KS C 6032 standards provide this procedures. But these procedures have some questions to apply in the field. The cost of test and confidence level($1-{\beta}$ risk) are the problem between supplier and user. So, we suggest that the optimal life test sampling inspection plans using expected cost model considering product cost, capability, environmental test cost, etc.

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Deep Learning-Based Defects Detection Method of Expiration Date Printed In Product Package (딥러닝 기반의 제품 포장에 인쇄된 유통기한 결함 검출 방법)

  • Lee, Jong-woon;Jeong, Seung Su;Yu, Yun Seop
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.463-465
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    • 2021
  • Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.

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Inspection and Sampling for Bulk Materials (집합체의 검사와 샘플링)

  • Choi, Sung-Woon
    • Proceedings of the Safety Management and Science Conference
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    • 2007.11a
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    • pp.305-309
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    • 2007
  • This study introduces acceptance sampling plans and procedures for the inspection of bulk materials. This paper also presents statistical aspects of sampling bulk materials such as general principles and sampling of particulate materials.

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