• Title/Summary/Keyword: X bar Control Chart

Search Result 64, Processing Time 0.026 seconds

Special control chart for automotive engineers (자동차 기술자를 위한 특수관리도)

  • 서호복
    • Journal of the korean Society of Automotive Engineers
    • /
    • v.4 no.1
    • /
    • pp.1-4
    • /
    • 1982
  • 우리가 흔히 쓰는 관리도에도 X over bar-R관리도, P(또는 Pn)관리도, C(또는 U)관리도가관리 도의 대종을 이루고 있다. 그러나 기계공업 특히 자동차공업분야에서는 기계가공 부품을 일일이 재기가 어렵거나 시간이 걸리므로 고-노고우 게이지(go-no go gauge)를 써서 선별하는 경우가 많다. 또 금형베품의 조립시에는 측정개소가 많기 때문에 어느 한 부분만을 제어서 관리할 수 없으므로 여러곳을 제어서 관리해야 하는데 이때 금형전체를 어떻게 맞출것인가, 혹은 제품의 공차관리를 어떻게 해나갈 것인가 하는 문제가 생긴다. 다음에 이러한 경우에 유용하게 쓰일 수 있는 관리도의 예를 소개하고자 한다.

  • PDF

A Survey on The Economic Design of Control Chart in Small Process Variation (미세공정변동에서 관리도의 경제적 설계를 위한 조사연구)

  • Kim, Jong-Gurl;Um, Sang-Joon;Kim, Hyung-Man
    • Proceedings of the Safety Management and Science Conference
    • /
    • 2013.04a
    • /
    • pp.533-546
    • /
    • 2013
  • 이 논문은 미세공정변동에서 극소불량을 감지하는 관리도의 경제적 설계를 개발하기 위한 조사연구이다. 일반적인 관리도의 설계는 통계적 설계와 경제적 설계로 구분할 수 있다. 공정의 변동 원인에 따라 샘플의 간격(h), 샘플의 크기(n), 관리한계선(k) 등의 설계 모수를 최적접근방법으로 결정을 하는 경제적 설계의 모델을 조사하였다. 관리도의 경제적 설계는 공정의 관리이상상태를 효율적으로 감지하여 관리상태로 정상화 시키는 것에 대한 공정의 개선비용과 기대품질비용을 절약 할 수 있는 최적설계 방안이다. 그리고 Shewhart 관리도의 X-bar 통계량으로 극소불량을 검출 하는것에 한계가 있기 때문에 Zp 통계량과 분포를 설계하여 극소불량을 빠르게 감지할 수 있는 Zp 관리도의 설계를 적용하고, 미세공정변동을 정확하게 감지할 수 있는 CUSUM 관리도를 동시에 적용하였다. 따라서, 미세공정변동과 극소불량을 동시에 관리 할 수 있는 Zp-CUSUM 관리도의 통계적 설계 구조를 체계화 하였으며, 기존의 경제적 설계의 모델을 비교 분석하여 새로운 경제적 설계에 대한 모델을 제안하고자 한다.

  • PDF

Application of Westgard Multi-Rules for Improving Nuclear Medicine Blood Test Quality Control (핵의학 검체검사 정도관리의 개선을 위한 Westgard Multi-Rules의 적용)

  • Jung, Heung-Soo;Bae, Jin-Soo;Shin, Yong-Hwan;Kim, Ji-Young;Seok, Jae-Dong
    • The Korean Journal of Nuclear Medicine Technology
    • /
    • v.16 no.1
    • /
    • pp.115-118
    • /
    • 2012
  • Purpose: The Levey-Jennings chart controlled measurement values that deviated from the tolerance value (mean ${\pm}2SD$ or ${\pm}3SD$). On the other hand, the upgraded Westgard Multi-Rules are actively recommended as a more efficient, specialized form of hospital certification in relation to Internal Quality Control. To apply Westgard Multi-Rules in quality control, credible quality control substance and target value are required. However, as physical examinations commonly use quality control substances provided within the test kit, there are many difficulties presented in the calculation of target value in relation to frequent changes in concentration value and insufficient credibility of quality control substance. This study attempts to improve the professionalism and credibility of quality control by applying Westgard Multi-Rules and calculating credible target value by using a commercialized quality control substance. Materials and Methods : This study used Immunoassay Plus Control Level 1, 2, 3 of Company B as the quality control substance of Total T3, which is the thyroid test implemented at the relevant hospital. Target value was established as the mean value of 295 cases collected for 1 month, excluding values that deviated from ${\pm}2SD$. The hospital quality control calculation program was used to enter target value. 12s, 22s, 13s, 2 of 32s, R4s, 41s, $10\bar{x}$, 7T of Westgard Multi-Rules were applied in the Total T3 experiment, which was conducted 194 times for 20 days in August. Based on the applied rules, this study classified data into random error and systemic error for analysis. Results: Quality control substances 1, 2, and 3 were each established as 84.2 ng/$dl$, 156.7 ng/$dl$, 242.4 ng/$dl$ for target values of Total T3, with the standard deviation established as 11.22 ng/$dl$, 14.52 ng/$dl$, 14.52 ng/$dl$ respectively. According to error type analysis achieved after applying Westgard Multi-Rules based on established target values, the following results were obtained for Random error, 12s was analyzed 48 times, 13s was analyzed 13 times, R4s was analyzed 6 times, for Systemic error, 22s was analyzed 10 times, 41s was analyzed 11 times, 2 of 32s was analyzed 17 times, $10\bar{x}$ was analyzed 10 times, and 7T was not applied. For uncontrollable Random error types, the entire experimental process was rechecked and greater emphasis was placed on re-testing. For controllable Systemic error types, this study searched the cause of error, recorded the relevant cause in the action form and reported the information to the Internal Quality Control committee if necessary. Conclusions : This study applied Westgard Multi-Rules by using commercialized substance as quality control substance and establishing target values. In result, precise analysis of Random error and Systemic error was achieved through the analysis of 12s, 22s, 13s, 2 of 32s, R4s, 41s, $10\bar{x}$, 7T rules. Furthermore, ideal quality control was achieved through analysis conducted on all data presented within the range of ${\pm}3SD$. In this regard, it can be said that the quality control method formed based on the systematic application of Westgard Multi-Rules is more effective than the Levey-Jennings chart and can maximize error detection.

  • PDF

Study on VoIP Service Quality Management (VoIP 서비스 품질관리에 관한 연구)

  • Chang, Byeong-Yun;Seo, Dong-Won;Park, Byung-Joo
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.11 no.2
    • /
    • pp.245-252
    • /
    • 2011
  • VoIP transmits voices over IP-based networks and it is the abbreviation of Voice over Internet Protocol. Recently, VoIP provides various services in addition to voices. Since VoIP services' provision is extending, VoIP service quality management is becoming an important issue. Therefore, in this paper, we study VoIP service quality management. We examine VoIP technology, service types, and network architecture. Then, we investigate key quality indicators(KQIs)/key performance indicators(KPIs) in terms of customers, not network service providers. Toward this, we also study the concept of general service quality management as well as the concept of telecommunication related service quality management. Moreover, we apply $\bar{x}$ and R charts to show how to use statistical quality control techniques in real telecommunication companies with one KQI.