• Journal of Korean Society for Quality Management
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• v.30 no.2
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• pp.152-159
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• 2002

An acceptance sampling plan for products manufactured from a production process with variable fraction defective is developed. We consider a situation where defective products have short lifetimes and non-defective ones never fail during the technological life of the products. An acceptance criterion which guarantee the out going quality of accepted products is derived using the prior information on the quality of products. Numerical examples are provided.

• Journal of the Korea Safety Management & Science
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• v.9 no.4
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• pp.137-142
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• 2007

This paper is to introduce attribute acceptance sampling plan based on statistical inference of binomial proportions such as PPM or PPB. In addition, this paper presents three variable sampling acceptance sampling plans based on $C_{pm},\;C_{pmk}$, and Taguchi's loss function. Producers are able to consider as not only external vendors but also internal customers.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.793-802
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• 1997

A sampling plan is presented for situations where sampling inspection is based on the quality characteristic of interest and items in rejected lots are screened based on a correlated variable. A cost model is constructed which involves the costs of misclassification errors, sampling and screening inspections. A method of finding optimal values of sample size, acceptance number and cutoff value on the correlated variable is presented, and numerical studies are given.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.3
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• pp.205-212
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• 2004

This paper proposes the variables repetitive group sampling plan where the quality characteristic following normal distribution has upper or lower specification limit. The problem is formulated as a non-linear programming problem where the objective function to minimize is the average sample number and the constraints are related to lot acceptance probabilities at acceptable quality level (AQL) and limiting quality level (LQL) under the operating characteristic curve. Sampling plan tables are constructed for the selection of parameters indexed by AQL and LQL in the cases of known standard deviation and unknown standard deviation. It is shown that the proposed sampling plan significantly reduces the average sample number as compared with the single or the double sampling plan.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.231-238
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• 2016

Traditional acceptance sampling plans have focused on the proportion of nonconforming items as an attribute criterion for quality. In today's modern quality management under high quality production environments, the reduction of the deviation from a target value in a quality characteristic has become the most important purpose. In consequence, various inspection plans for the purpose of reducing the deviation from the target value in the quality characteristic have been investigated. In this case, a concept of the quality loss evaluated by the deviation from the target value has been accepted as the variable evaluation criterion of quality. Further, some quality measures based on the quality loss have been devised; e.g. the process loss and the process capability index. Then, as one of inspection plans based on the quality loss, the rigorous design procedure for the variable sampling plan having desired operating characteristics (VS-OC plan) indexed by the quality loss has been proposed by Yen and Chang in 2009. By the way, since the estimator of the quality loss obeys the non-central chi-square distribution, the rigorous design procedure for the VS-OC plan indexed by the quality loss is complicated. In particular, the rigorous design procedure for the VS-OC plan requires a large number of the repetitive and complicated numerical calculation about the non-central chi-square distribution. On the other hand, an approximate design procedure for the VS-OC plan has been proposed before the proposal of the above rigorous design procedure. The approximate design procedure for the VS-OC plan has been constructed by combining Patnaik approximation relating the non-central chi-square distribution to the central chi-square distribution and Wilson-Hilferty approximation relating the central chi-square distribution to the standard normal distribution. Then, the approximate design procedure has been devised as a convenient procedure without complicated and repetitive numerical calculations. In this study, through some comparisons between the rigorous and approximate design procedures, the applicability of the approximate design procedure has been confirmed.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.131-138
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• 2009

The variable sampling inspection scheme with screening for the purpose of assuring the upper limit of maximum expected surplus loss after inspection has been proposed. In this inspection scheme, it has been assumed that a product lot consists of products manufactured through a single production line and lot quality characteristics follow a normal distribution. In the previous literature with respect to inspection schemes, it has been commonly assumed that lot quality characteristics obey a single normal distribution under the condition that all products are manufactured in the same condition. On the other hand, the production line is designed in order that the workload of respective processes becomes uniform from the viewpoint of line balancing. One of the solutions for the bottleneck process is to arrange the workshops in parallel. The lot quality characteristics from such a production line with the process consisting of some parallel workshops might not follow strictly the single normal distribution. Therefore, we expand an applicable scope of the above mentioned variable sampling inspection scheme with screening in this article. Concretely, we consider the variable sampling inspection with screening for the purpose of assuring the upper limit of average outgoing surplus quality loss in the production lots when the lot quality follows the mixed normal distribution.

• Industry Promotion Research
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• v.8 no.1
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• pp.111-117
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• 2023

Sampling inspection methods for quality control have been proposed a lot in the industry. However, the sampling inspection method for reliability, which is a quality over time, has been relatively less presented, and there are not many literatures that are clearly summarized. Therefore, this paper focuses on the reliability conformity test to verify that the reliability evaluation scale value of the target is satisfied during the reliability test. To this end, first, we look at the conditions that both consumers and producers can satisfy in terms of the OC curve and find out what sampling methods satisfy the desired level of producer risk and consumer risk. Next, two methods of the reliability sampling methods such as attribute and variable reliability sampling methods are examined. Specifically, the attribute reliability sampling method is a form of sampling plan where n samples are tested for a certain period of T hours and the lot is accepted if the number of failures is less than or equal to a certain number c. On the other hand, the variable reliability sampling method is a form of sampling plan where the lot is accepted if the reliability evaluation scale such as MTBF satisfies a certain standard. Both sampling plans may also use inspection tables.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.123-134
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• 2007

This paper focuses on the in-house reliability assurance plan for the bulk materials of each company. The reliability assurance needs in essence a long time and high cost for testing the materials. In order to reduce the time and cost, accelerated life test is adopted. The bulk sampling technique was used for acceptance. Design parameters might be total sample size(segments and increments}, stress level and so on. We focus on deciding the sample size by minimizing the asymptotic variance of test statistics as well as satisfying the consumer's risk. In bulk sampling, we also induce the sample size by adapting the normal life time distribution model when the variable of the lognormal life time distribution is transformed and adapted to the model. In addition, the sample size for both the segments and increments can be induced by minimizing the asymptotic variance of test statistics of the segments and increments with consumer's risk met. We can assure the reliability of the mean life and B100p life time of the bulk materials by using the calculated minimum sample size.

• International Journal of Reliability and Applications
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• v.17 no.1
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• pp.85-105
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• 2016

In this paper accelerated life testing is incorporated in quality control technique of acceptance sampling plan to induce early failures in high reliability products.Stress under accelerated condition can be applied in constant-stress, step-stress and progressive-stress or combination of such loadings. A ramp-stress results when stress is increased linearly (from zero) with time. In this paper optimum failure-censored ramp-stress accelerated life test sampling plan for log-logistic distribution has been formulated with cost considerations. The log-logistic distribution has been found appropriate for insulating materials. The optimal plans consist in finding optimum sample size, sample proportion allocated to each stress, and stress rate factor such that producer's and consumer's interests are safeguarded. Variance optimality criterion is used when expected cost per lot is not taken into consideration, and bilevel programming approach is used in cost optimization problems. The methods developed have been illustrated using some numerical examples, and sensitivity analyses carried out in the context of ramp-stress ALTSP based on variable SSP for proportion nonconforming.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.3
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• pp.359-366
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• 1993

The purpose of this study was to classify college women according to the general life style, to examine the differences in the characteristics of time consumption, and clothing purchasing behavior, and ultimately to verify the importance of the time variable in life style analysis. 449 subjects were gathered through convenience sampling method and, frequency, precentage, average, $x^2$-test, t-test, ANOVA, Duncan's multiple range test, Factor Analysis, Cluster Analysis were conducted for data analysis. Results of the study were as follows : 1. College women were classified into five subgroups by cluster analysis : fashion-pursuit group, home-intended group, outer-intended group, conservative-economy group, and passive-inactive group. 2. In case of time consumption patterns, significant differences were found according to the different groups in patronage of library and extra off-campus educational programs, participation in household duties, consumption patterns of leisure time and participation in clubs. 3. In case of clothing purchasing behavior, significant differences were found according to the different groups in clothing purchasing motives, information sources, purchasing plan, the number of visited stores, and the confirmation of labels.