• 품질경영학회지
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• 제2권5_2호
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• pp.5-7
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• 1968

• 품질경영학회지
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• 제33권3호
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• pp.126-134
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• 2005

This paper proposes a selectively cumulative sum(S-CUSUM) control chart for detecting shifts in the process mean. The basic idea of the S-CUSUM chart is to accumulate previous samples selectively in order to increase the sensitivity. The S-CUSUM chart employs a threshold limit to determine whether to accumulate previous samples or not. Consecutive samples with control statistics out of the threshold limit are to be accumulated to calculate a standardized control statistic. If the control statistic falls within the threshold limit, only the next sample is to be used. During the whole sampling process, the S-CUSUM chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L -consecutive control statistics fall outside the threshold limit. The number L is a decision variable and is called a 'control length'. A Markov chain approach is employed to describe the S-CUSUM sampling process. Formulae for the steady state probabilities and the Average Run Length(ARL) during an in-control state are derived in closed forms. Some properties useful for designing statistical parameters are also derived and a statistical design procedure for the S-CUSUM chart is proposed. Comparative studies show that the proposed S-CUSUM chart is uniformly superior to the CUSUM chart or the Exponentially Weighted Moving Average(EWMA) chart with respect to the ARL performance.

• 한국축산식품학회지
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• 제34권2호
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• pp.245-251
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• 2014

The aim of this study was to estimate the shelf life of butter and cheese products, with shelf life being a guide used to determine the storage period of food before deterioration. Butter and cheese samples stored at $10^{\circ}C$ and $15^{\circ}C$ had a shelf life of 221 d, while those stored at $25^{\circ}C$ and $35^{\circ}C$ had a shelf life of 109 d. Quality changes, including total cell count, coliform counts, Listeria monocytogenes counts, acid value, moisture content, pH, acidity and overall sensory evaluation, were monitored. In order to pass the overall sensory evaluation, a quality score of 5 points on a 9-point scale was required. For other quality criteria, legal quality limits were established based on the "Process Criteria and Ingredient Standard of Livestock Products" by the Animal, Plant and Fisheries Quarantine and Inspection Agency (Republic of Korea). The nonlegal quality limit was estimated by regression analysis between non-quality criteria (y) and overall sensory evaluation (x). The shelf life was estimated based on the number of days that the product passed the quality limit of the quality criteria. The shelf life of samples stored at $10^{\circ}C$, $15^{\circ}C$, $25^{\circ}C$ and $35^{\circ}C$ was 21.94, 17.18, 6.10 and 0.58 mon, respectively, for butter and 10.81, 9.47, 4.64 and 0.20 mon, respectively, for cheese.

• 한국물환경학회지
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• 제24권6호
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• pp.676-681
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• 2008

The evaluation of the effluent water quality of sewage treatment plant is one of the most important factor in calculating total maximum daily loads (TMDLs). Current method to calculate 95% upper limit of effluent water quality of sewage treatment plant assuming normal distribution of data needs to be implemented in case of non-normal distribution. We have investigated the applicability of percentile ranking method as a non-parametric statistical analysis in case of non-normal distribution of data.

• 품질경영학회지
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• 제25권4호
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• pp.57-70
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• 1997

Consider a production system where all manufactured products are screened through automatic inspection equipment. The products for which the measured value of quality characteristic is larger than the lower screening specification limit (SL) and smaller than the u, pp.r screeing specification limit(SU) are accepted. Those smaller than SL are reworked and those larger than SU are excluded from the process. Assuming that the quality characteristic is normally distributed with known variance, this paper suggests cost models which involve inspection cost, production cost, rework cost, exclusion cost and quality cost, and presents the methods of finding the optimal values of the screening specification limits and the process target. Numerical example is given to demonstrate the a, pp.icability of the cost models suggested in this paper.

• 품질경영학회지
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• 제20권2호
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• pp.11-20
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• 1992

We discuss the feed back control of the on-line QC in the Taguchi method. Taguchi(1982) used the assumptions that the quality characteristics follow an uniform distribution and the Brownian motion to draw the loss function and proposed ${\Delta}/3$ or ${\Delta}$ for the initial control limit. Adams and Woodall(1989) also proposed a different procedure but using the same loss function. We propose, in this paper the new loss function under the assumption of mainly Brownian motion and compare the results with the results of the above.

• 품질경영학회지
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• 제19권2호
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• pp.78-85
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• 1991

In this paper, an inspection and replacement policy in a redundant system is considered. It is assumed that the state of the redundant system is known by inspection. When the system is inspected, it is preventively replaced only if the number of failed units exceeds the predetermined limit. Otherwise, the system is inspected after a inspection interval which depends on the number of failed units. We obtain the optimal number of redundant units, inspection intervals and replacement limit minimizing the expected cost rate.

• Industrial Engineering and Management Systems
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• 제13권2호
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• pp.231-249
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• 2014

This paper discusses a green supply chain with a manufacturer and a collection trader, and it proposes an optimal production planning for remanufacturing of parts in used products with quality classification errors made by the collection trader. When a manufacturer accepts an order for parts from a retailer and procures used products from a collection trader, the collection trader might have some quality classification errors due to the lack of equipment or expert knowledge regarding quality classification. After procurement of used products, the manufacturer inspects if there are any classification errors. If errors are detected, the manufacturer reclassifies the misclassified (overestimated) used products at a cost. Accordingly, the manufacturer decides to remanufacture from the higher-quality used products based on a remanufacturing ratio or produce parts from new materials. This paper develops a mathematical model to find how quality classification errors affect the optimal decisions for a lower limit of procurement quality of used products and a remanufacturing ratio under the lower limit and the expected profit of the manufacturer. Numerical analysis investigates how quality of used products, the reclassification cost and the remanufacturing cost of used products affect the optimal production planning and the expected profit of a manufacturer.

• 대한산업공학회지
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• 제39권4호
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• pp.233-238
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• 2013

This article concerns a profit model in a repair limit replacement problem with imperfect repair. If a system fails, we should decide whether we repair the failed system (repair option) or replace it by new one (replacement option with a lead time). We assume that repair times are random variables and can be estimated before repair with estimation error. If the estimated repair time is less than the specified limit (repair time limit), the failed unit is repaired but the unit after repair is different from the new one (imperfect repair). Otherwise, we order a new unit to replace the failed unit. The long run average profit (expected profit rate) is used as an optimization criterion and the optimal repair time limit maximizes the expected profit rate. Some special cases are derived.

• 산업경영시스템학회지
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• 제41권1호
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• pp.110-117
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• 2018

Machines and facilities are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. By the result of degeneration, non-conforming products and malfunction of machine occur. Therefore a periodic preventive resetting the process is necessary. This type of preventive action is called 'preventive maintenance policy.' Preventive maintenance presupposes that the preventive (resetting the process) cost is smaller than the cost of failure caused by the malfunction of machine. The process mean shift problem is a field of preventive maintenance. This field deals the interrelationship between the quality cost and the process resetting cost before machine breaks down. Quality cost is the sum of the non-conforming item cost and quality loss cost. Quality loss cost is due to the deviation between the quality characteristics from the target value. Under the process mean shift, the quality cost is increasing continuously whereas the process resetting cost is constant value. The objective function is total costs per unit wear, the decision variables are the wear limit (resetting period) and the initial process mean. Comparing the previous studies, we set the process variance as an increasing concave function and set the quality loss function as Cpm+ simultaneously. In the Cpm+, loss function has different cost coefficients according to the direction of the quality characteristics from target value. A numerical example is presented.