Machines and facilities are physically or chemically degenerated by continuous usage. The representative type of the degeneration is the wearing of tools, which results in the process mean shift. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore, a preventive maintenance is necessary at some point . The problem of determining the maintenance period (or wear limit) which minimizes the total cost is called the ‘process mean shift problem’. The total cost includes three items: maintenance cost (or adjustment cost), non-conforming cost due to the non-conforming products, and quality loss cost due to the difference between the process target value and the product characteristic value among the conforming products. In this study, we set the production volume as a decreasing function rather than a constant. Also we treat the process variance as a function to the increasing wear rather than a constant. To the quality loss function, we adopted the Cpm+, which is the left and right asymmetric process capability index based on the process target value. These can more reflect the production site. In this study, we presented a more extensive maintenance model compared to previous studies, by integrating the items mentioned above. The objective equation of this model is the total cost per unit wear. The determining variables are the wear limit and the initial process setting position that minimize the objective equation.

Quality requirements of manufactured products or parts are given in the form of specification limits on the quality characteristics of individual units. If a product is to meet the customer’s fitness for use criteria, it should be produced by a process which is stable or repeatable. In other words, it must be capable of operating with little variability around the target value or nominal value of the product’s quality characteristic. In order to maintain and improve product quality, we need to apply statistical process control techniques such as histogram, check sheet, Pareto chart, cause and effect diagram, or control charts. Among those techniques, the most important one is control charting. The cumulative sum (CUSUM) control charts have been used in statistical process control (SPC) in industries for monitoring process shifts and supporting online measurement. The objective of this research is to apply Taguchi's quality loss function concept to cost based CUSUM control chart design. In this study, a modified quality loss function was developed to reflect quality loss situation where general quadratic loss curve is not appropriate. This research also provided a methodology for the design of CUSUM charts using Taguchi quality loss function concept based on the minimum cost per hour criterion. The new model differs from previous models in that the model assumes that quality loss is incurred even in the incontrol period. This model was compared with other cost based CUSUM models by Wu and Goel, According to numerical sensitivity analysis, the proposed model results in longer average run length in in-control period compared to the other two models.

Insect cuticle tanning (pigmentation and sclerotization) is a complex and vital process, which includes hydroxylation of initial amino acid, tyrosine, to DOPA and decarboxylation of DOPA to dopamine. In the pigmentation process, dopamine further undergoes two N-acylation reactions to yield N-acetyldopamine (NADA) and N-β-alanyldopamine (NBAD). In the former reaction, arylalkylamine N-acetyltransferase (AANAT1) converts dopamine to NADA, and in the later reaction, aspartate 1-decarboxylase (ADC) provides β-alanine, which is conjugated with dopamine catalyzed by NBAD synthase (Ebony) for production of NBAD. In this study, we performed functional genomics of TmAANAT1, TmADC and Tmebony to determine whether they are required for cuticle pigmentation in Tenebrio molitor adults. Loss of function of these genes by RNAi caused the significantly darker body color than that of control animals. Note that, although all phenotypes exhibited dark cuticle pigmentation, RNAi of either TmADC or Tmebony only altered brownish outer region of the cuticle to dark/black. In contrast, RNAi of TmAANAT1 had no effect on the brown hue of the outer cuticle layer, but less or no pigmented inner region of the cuticle became significantly darker than those of control adults. These results suggest that, like that seen in TcAANAT1- or TcADC-deficient Tribolium castaneum adults, NADA produced by a reaction by TmAANAT1 contributes the lighter inner cuticle layer(s), whereas NBAD appears to do the highly pigmented outer cuticle layer(s) of the cuticle of T. molitor adults. This work was supported by NRFs (NRF-2015R1A6A3A04060323 and NRF-2018R1A2B6005106).

Taguchi regarded the concept of quality as ‘total loss to society due to fluctuations in quality characteristics from the time of supplied to the customer.’ The loss function is a representative tool that can quantitatively convert the loss that occurs due to the deviation of the quality characteristic value from the target value. This has been utilized in various studies with the advantage that it can change the social loss caused by fluctuation of quality characteristics to economic cost. The loss function has also been used extensively in the study of producer specification limits. However, in previous studies, only the second order loss function of Taguchi is used. Therefore, various types of losses that can occur in the process can’t be considered. In this study, we divide the types of losses that can occur in the process considering the first and second loss functions and the Spiring’s reflected normal loss function, and perform total inspection before delivering the customer to determine the optimal producer specification limit that minimizes the total cost. Also, we will divide the quality policy for the products beyond the specification limits into two. In addition, we will show the illustration of expected loss cost change of each model according to the change of major condition such as customer specifications and maximum loss cost.

In the industrial fields, the process capability index has been using to evaluate the variation of quality in the process. The traditional process capability indices such as Cp, Cpk, Cpm, and C┼pm have been applied in the industrial fields. These traditional process capability indices are mainly applied in the univariate analysis. However, the main streams in the recent industry are the multivariate manufacturing process and the multiple quality characteristics are corrected each other. Therefore, the multivariate statistical method should be used in the process capability analysis. The multivariate process indices need to be enhanced with more useful information and extensive application in the recent industrial fields. Hence, the purpose of the study is to develop a more effective multivariate process index (MCpI ) using the multivariate inverted normal loss function. The multivariate inverted normal loss function has the flexibility for the any type of the symmetrical and asymmetrical loss functions as well as the economic information. Especially, the proposed modeling method for the multivariate inverted normal loss function (MINLF) and the expected loss from MINLF in this paper can be applied to the any type of the symmetrical and asymmetrical loss functions. And this modeling method can be easily expanded from a bivariate case to a multivariate case.

Machines are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. Under the process mean shift, production cost, failure cost and quality loss function cost are increasing continuously. Therefore a periodic preventive resetting the process is necessary. We suppose that the wear level is observable. In this case, process mean shift problem has similar characteristics to the maintenance policy model. In the previous studies, process mean shift problem has been studied in several fields such as ‘Tool wear limit’, ‘Canning Process’ and ‘Quality Loss Function’ separately or partially integrated form. This paper proposes an integrated cost model which involves production cost by the material, failure cost by the nonconforming items, quality loss function cost by the deviation between the quality characteristics from the target value and resetting the process cost. We expand this process mean shift problem a little more by dealing the process variance as a function, not a constant value. We suggested a multiplier function model to the process variance according to the analysis result with practical data. We adopted two-side specification to our model. The initial process mean is generally set somewhat above the lower specification. The objective function is total integrated costs per unit wear and independent variables are wear limit and initial setting process mean. The optimum is derived from numerical analysis because the integral form of the objective function is not possible. A numerical example is presented.

Process quality control, which prevents problems and risks that may occur in products and processes, has been recognized as an important issue, and SPC techniques have been used for this purpose. Process Capability Index (PCI) is useful Statistical Process Control (SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. Cp and Cpk are traditional PCIs. These traditional Cp and Cpk were used only as a measure of process capability, taking into account the quality variance or the bias of the process mean. These are not given information about the characteristic value does not match the target value of the process and this has the disadvantage that it is difficult to assess the economic losses that may arise in the enterprise. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. Cpm is considers both the process variation and the process deviation from target value. And Cpm + is considers economic loss for the process deviation from target value. In this paper we developed an improved Expected Loss Capability Index using Reflected Normal Loss Function of Spring. This has the advantage that it is easy to realistically reflect the loss when the specification is asymmetric around the target value. And check the correlation between existing traditional process capability index (Cpk) and new one. Finally, we propose the criteria for classification about developed process capability index.

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 PhaseⅠ. 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 PhaseⅠ. 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 x-R control chart and expected loss control chart (ELCC).

In the manufacturing industry fields, thousands of quality characteristics are measured in a day because the systems of process have been automated through the development of computer and improvement of techniques. Also, the process has been monitored in database in real time. Particularly, the data in the design step of the process have contributed to the product that customers have required through getting useful information from the data and reflecting them to the design of product. In this study, first, characteristics and variables affecting to them in the data of the design step of the process were analyzed by decision tree to find out the relation between explanatory and target variables. Second, the tolerance of continuous variables influencing on the target variable primarily was shown by the application of algorithm of decision tree, C4.5. Finally, the target variable, loss, was calculated by a loss function of Taguchi and analyzed. In this paper, the general method that the value of continuous explanatory variables has been used intactly not to be transformed to the discrete value and new method that the value of continuous explanatory variables was divided into 3 categories were compared. As a result, first, the tolerance obtained from the new method was more effective in decreasing the target variable, loss, than general method. In addition, the tolerance levels for the continuous explanatory variables to be chosen of the major variables were calculated. In further research, a systematic method using decision tree of data mining needs to be developed in order to categorize continuous variables under various scenarios of loss function.

Control chart is a graph of plotting dot in the process characteristic values. It is a statistical technique that can be known whether or not the in-control state in this step. In many companies have use as a statistical process control(SPC) tool. Control chart is the management process quality characteristic value, which is plotted dot is whether the existence within the control limits. But, this 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 that sence, expected loss control chart(EL control chart) is very effective process control tool. Because it is a process control chart in consideration to economic loss. The EL control chart is using the quadratic loss function of Taguchi. However, Taguchi’s quadratic loss function is simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. In this paper, we design a new control chart using the reflected normal loss function(RNLF). And we demonstrate its effectiveness by using the control chart performance comparison of EL control chart.

  The facility location in designing a supply chain network is an important decision problem that gives form, structure, and shape to the entire supply chain system. Location problems involve determining the location, number, and size of the facilities to

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for muliple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index MCpm using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other,

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for multiple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index MCpm using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other.

We purpose a decision model to select the optimal facilities for the Decision Making problems with multiple characteristics(nominal-is-best characteristics, larger-is -better characteristics, smaller- is -better characteristics). Using this model, concept of the loss function is used in this comprehensive method of for select the optimal preferred facilities. To solve the issue on the optimal preferred facilities for multiple characteristics, this study propose the loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms.

The purpose of this study is to develop a method to assess the expected damage and loss of vehicle by flood disaster. To this end, we designed the inventory (exposure) DB to define spatial location and distribution by vehicle type, and presented the construction procedure of inventory DB. Vehicle asset value required for quantifying loss was taken into account depreciation in the replacement cost of each representative vehicles. The vehicle vulnerability curve is used to analyze the percent damage due to flood depth. It is classified the vehicle into three types based on the vehicle height, developed the vulnerability curve from the opinion of the expert group. The method proposed in this study is part of f lood loss assessment model. It will be used for flood risk assessment and economic analysis of flood mitigation projects.

최근 다양한 기상변화에 의한 재해발생 위험도는 점차 높아지고 있다. 특히 대기, 하천, 해양 등 지구전역에 걸쳐 발생하고 있는 환경오염과 화학물질의 사용량 증가는 온난화와 같은 환경변화를 초래하고, 이는 곧 지구 물 순환 체계의 변화로 이어지게 된다. 2010년, 2011년의 서울을 비롯한 중부지역의 집중호우 이후 매년 발생하고 있는 홍수피해는 이러한 기상변화를 잘 대변하고 있다. 본 연구에서는 국내 홍수피해지역에 대한 경제적 피해추정을 위해 많이 사용하는 다차원홍수피해산정법(MD-FDA: Multi-Dimensional Flood Damage Analysis)에서 벗어나 실제 침수피해지역에 대한 설문조사를 통해 손실함수를 개발하고자 하였다. 대상지역은 2011년 7월에 발생한 집중호우로 인해 동두천시를 관통하고 있는 신천의 범람으로 인한 도심지 침수지역을 대상으로 실시하였다.