• 한국품질경영학회:학술대회논문집
• /
• 한국품질경영학회 2007년도 춘계학술대회
• /
• pp.187-195
• /
• 2007

최근 우리나라에서 도요타를 벤치마킹하여 TPS를 도입하는 회사가 늘어나고 있다. 다품종 소량생산의 Lean 생산방식을 적용하기 위해서는 셋업시간의 단축 뿐만 아니라 이에 따른 셋업 품질능력이 향상되어야 한다. 따라서, 공정을 셋업하는 작업자들에게 이러한 Complex Target & Control Chart를 적용한다면, 통계적인 지식 없이도 공정의 불량을 예방 할 수 있으리라 확신한다. 이러한 관리도를 사용하여 공정능력을 향상한다면, 일본과 같은 높은 수준의 공정능력을 확보 할 수 있을 것이다. 단, 본 관리도는 현장 작업자를 위한 불량예방을 위한 품질관리 도구이며, 공정변동을 관리하기 위해서는 엔지니어 측면에서 관리도의 활용도 병행되어야 한다.

• 한국의류학회지
• /
• 제26권1호
• /
• pp.50-61
• /
• 2002

The manufacturer first identifies a target market before developing a sizing chart. A target market is specific for age or figure type. The purpose of this study is to evaluate the suitability of sizing system of women's apparel brand in Korea. For this purpose, the characteristics of the manufacture's sizing chart for jacket and skirt/pants were analyzed. For each brand, the target age of the brand and the age of consumers who preferred that bland were compared. The size charts collected from 27 women's apparel brands were analyzed and compared with Korean industrial standard sifting chart. The results of this study reviled that the body proportion in many manufacturer's sizing chart does not correspond to the body types in Korean industrial standard sizing chart. This trend was apparent for the short figure sizes made for women 155cm in height. There is a difference between the target age in brand concept and the age of consumer preferring to purchase that brand apparel. The age of fitting models usually does not correspond the customer's age. It was concluded that the age of target customer does not go well with the age of brand concept nor the fitting model age caused fit problem of the women's ready-made clothes.

• 산업경영시스템학회지
• /
• 제39권2호
• /
• pp.37-45
• /
• 2016

Control chart is representative tools of statistical process control (SPC). It is a graph that plotting the characteristic values from the process. It has two steps (or Phase). First step is a procedure for finding a process parameters. It is called Phase I. This step is to find the process parameters by using data obtained from in-controlled process. It is a step that the standard value was not determined. Another step is monitoring process by already known process parameters from Phase I. It is called Phase II. These control chart is the process quality characteristic value for management, which is plotted dot whether the existence within the control limit or not. But, this is not given information about the economic loss that occurs when a product characteristic value does not match the target value. In order to meet the customer needs, company not only consider stability of the process variation but also produce the product that is meet the target value. Taguchi's quadratic loss function is include information about economic loss that occurred by the mismatch the target value. However, Taguchi's quadratic loss function is very simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. Also, it can be well explained by only on condition that the normal process. Spiring proposed an alternative loss function that called reflected normal loss function (RNLF). In this paper, we design a new control chart for overcome these disadvantage by using the Spiring's RNLF. And we demonstrate effectiveness of new control chart by comparing its average run length (ARL) with ${\bar{x}}-R$ control chart and expected loss control chart (ELCC).

• 한국안광학회지
• /
• 제14권1호
• /
• pp.69-80
• /
• 2009

목적: 본 연구는 영국에서 개발된 컴퓨터 모니터용 검안프로그램 Test Chart 2000 Pro의 타당도(validity)를 평가하기 위해 수행되었다. 방법: Test Chart 2000 Pro와 한국표준검안법의 공통된 10종류 검안항목에 대하여, 각 항목별로 동일한 피실험자군을 대상으로 2가지 검안법을 함께 실시하고, 측정결과의 일치도를 비교분석하였다. 결과: 10종류의 비교실험 중 Snellen Chart, Cross-cyl Target, Duochrome Test, Fan and Block Test, Random Dot Stereograms에서는 한국표준검안법과 Test Chart 2000 Pro양측의 결과가 통계적으로 유의미한 일치를 보였으나, LogMar Chart, Single Letter Chart, Phoria Test, Fixation Disparity Test, Worth 4 Dot Test에서는 두 검안 방법의 결과에서 차이가 나타났다. 결론: 한천석 시력표와 포롭터로 이루어진 한국표준검안법을 기준으로 했을 때 Test Chart 2000 Pro의 타당도는 높지 않으며, 측정의 정확도 측면에서 개선이 요구된다.

• 산업경영시스템학회지
• /
• 제36권2호
• /
• pp.56-62
• /
• 2013

Control chart is representative tool of Statistical Process Control (SPC). But, it is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In order to manage the process, we should consider not only stability of the variation also produce products with a high degree of matching the target value that is most ideal quality characteristics. There is a need for process control in consideration of economic loss. In this paper, we design a new control chart using the quadratic loss function of Taguchi. And we demonstrate effectiveness of new control chart by compare its ARL with ${\overline{x}}-R$ control chart.

• 벤처창업연구
• /
• 제7권2호
• /
• pp.151-156
• /
• 2012

본 논문에서 우리는 동시에 볼 수 있는 수정된 3개의 관리도를 제안하였다. 첫번째 곤리도는 샘플 데이터로만 그려진 관리도이다. 두번째 관리도는 처음 관리도에 상하한 규격을 포함한 관리도이다. 세번째 관리도는 목표값이 포함되고 오랜 기간 동안의 데이터로 계산된 알려진 평균과 표준편차로 계산된 상 하한 관리선이 포함된 관리도이다. 3개의 관리도를 동시에 보면 즉시 공정의 문제점을 알아낼 수 있는 정점이 있다. 이 논문에서 제안된 방법이 현장에서 활용되어 도움을 주길 희망한다.

• 산업경영시스템학회지
• /
• 제39권3호
• /
• pp.10-17
• /
• 2016

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally ${\bar{x}}-R$ control chart or ${\bar{x}}-s$ control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

• 품질경영학회지
• /
• 제38권3호
• /
• pp.313-321
• /
• 2010

The coefficient of variation represents the ratio of the standard deviation to the mean, and it is a useful statistic for comparing the degree of variation from one data series to another, even if the means are drastically different from each other. Recently, the CV control chart is developed for monitoring processes in such situations. However, the CV control chart has low performance in detecting small shift. Due to the development of equipment and technique, currently, small shift of process occurs more frequently than large shift. In this paper, we proposes the CV-CUSUM control chart using CUSUM scheme which is cumulative sum of the deviations between each data point and a target value to detect a small shift in the process. We also found that the FIR(fast initial response) CUSUM control chart is especially valuable at start-up or after a CV-CUSUM control chart has signaled out-of-control.

• 대한안전경영과학회지
• /
• 제9권2호
• /
• pp.215-233
• /
• 2007

Even though the ad hoc Shewhart methods remain controversial due to various mathematical flaws, there is little disagreement among researchers and practitioners when a set of process data has a skewness distribution. In the context and language of process control, the error related to the process data shows that time to signal increases when a control parameter shifts to a skewness direction. In real-world industrial settings, however, quality practitioners often need to consider a skewness distribution. To address this situation, we developed an enhanced design method to utilize advantages of the traditional attribute control chart and to overcome its associated shortcomings. The proposed design method minimizes bias, i.e., an average time to signal for the shift of process from the target value (ATS) curve, as well as it applies a variable sampling interval (VSI) method to an attribute control chart for detecting a process shift efficiently. The results of the factorial experiment obtained by various parameter circumstances show that the VSI c control chart using nearly unbiased ATS design provides the smallest decreasing rate in ATS among other charts for all experimental cases.

• 산업경영시스템학회지
• /
• 제20권42호
• /
• pp.73-85
• /
• 1997

In the product liability age the demand on quality is extremely high and inspection and test are automated. The process capability indices $C_p, {\;}C_{pk}$ and p control chart widely used to provide unitless measure of process performance and process control. Traditional process capability indices $C_p, {\;}C_{pk}$ do not represent the process variation from target value. The convention p chart for control of fraction nonconforming becomes inadequate when the fraction nonconforming becomes very small such as PPM level production system. This paper proposes process performance measure considering quadratic loss function and cumulative counts control chart for control of PPM level production system.