• Journal of the Korean Institute of Gas
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• v.9 no.3 s.28
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• pp.15-20
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• 2005

Recently, Environmental and Safety Management is approaching in order to reduce the loss cost of accidents in effect, efficiency, excellency. In the side that is a large production enemy of the industrialization times, Most companies are focused on decreasing the loss that can let their companies grow healthily than a productivity improvement. The this study analyzed a matter asked f3r basic requirements and continuous development of ISO14001, OHSAS18001, PSM, Responsible Care operating in petro-chemical industries basically, and developed a LCMCI(the Loss Control Management system for Continuous Improvement of the Petro-chemical Industries) fer continuous development of petro-chemical companies in order to be able to continuously manage a loss.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.2
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• pp.56-62
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• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.37-45
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• 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).

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.191-204
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• 2003

The target costing technique, mathematically discussed by Sauers, only uses the $C_p index along with Taguchi loss function and $\bar{X}$-P control charts to setup goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p value to $\bar{X}$-P control charts to obtain goal control limits. Studies have shown that the point estimator of the $C_p index, $C_p, could vary from time to time due to the sampling error. The suggested approach is to use confidence intervals, especially the lower confidence intervals, to replace the point estimator. Therefore, an improvement on target costing technique is presented by applying the lower confidence interval of the $C_p index and using both Taguchi and Spiring's loss functions together with $\bar{X}$-P charts to make this technique more robust in practice. An example is also provided to illustrate how the improved target costing technique works.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.43-53
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• 2008

This study is carried out for the fire safety of the factory building, the fire risk reduction measure in compliance with an example approached in fire risk reduction systematically, contribute to reduce the fire risk. The analytical fire risk process of discovering, identifying, estimating and evaluating risk and control measure as risk reduction measures are core concept, applies loss prevention with loss control techniques. The painting process in the workplace where the fire hazard and death accident accompanies coexists. Loss prevention problem of creation prevention of dangerous atmosphere at workplace is health and human services problem of normal circumstances, must be inspected with problem of combustible gases at the time of fire explosion. Static electricity measure accomplished the risk control process thoroughly as the fire risk reduction process model with the ignition sources measure which is presented. Fire risk from within organizing will be able to classify with each field by detailedly but risk treatment process will be able to apply basically all the same concept. Consequently about risk management example from before, this study is proposed risk management techniques that standardized rightly in the actual condition of organization with one plan, with discovery of fire risk, the feedback process in compliance with a fire risk reduction and the review which control the result is joint responsibility of engineer, technical expert and manager as part of safety management to practice with the fact must be supervised.

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.77-83
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• 1990

A model for the economic design of an pn control charts with an assignale cause is presented and the loss-cost function for control schemes using these charts is derived. By minimizing this function with respect to the three control variables, namely, the sample size, the sampling interval and acceptance number, the economically optimal control plan can be optained. The article shows what influence increasing or decreasing condition, according to changeability of the size of these factors, of expected cost can have on the economy when an attribute control chart is used.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.467-482
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• 2021

Purpose: The main theme of this study is to determine the optimal control limit of conditional variance investigation by mathematical approach. According to the determination approach of control limit presented in this study, it is possible with only one parameter to calculate the control limit necessary for budgeting control system or standard costing system, in which the limit could not be set in advance, that's why it has the advantage of high practical application. Methods: This study followed the analytical methodology in terms of the decision model of information economics, Bayesian probability theory and Taguchi's quality loss function concept. Results: The function suggested by this study is as follows; ${\delta}{\leq}\frac{3}{2}(k+1)+\frac{2}{\frac{3}{2}(k+1)+\sqrt{\{\frac{3}{2}(k+1)\}^2}+4$ Conclusion: The results of this study will be able to contribute not only in practice of variance investigation requiring in the standard costing and budgeting system, but also in all fields dealing with variance investigation differences, for example, intangible services quality control that are difficult to specify tolerances (control limit) unlike tangible product, and internal information system audits where materiality standards cannot be specified unlike external accounting audits.

• International Journal of Quality Innovation
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• v.6 no.2
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• pp.31-45
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• 2005

The target costing technique, mathematically discussed by Sauers, only uses the $C_p$ index along with Taguchi loss function and ${\bar{X}}-R$ control charts to set up goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p$ value to ${\bar{X}}-R$ control charts to obtain goal control limits. This study further considers the reflected normal loss function as well as the $C_{pk}$ index along with its lower confidence interval in forming goal control limits. With the use of lower confidence interval to replace the point estimator of the $C_{pk}$ index and reflected normal loss function proposed by Spiring to measure the loss to society, this modified and improved target costing technique would become more robust and applicable in practice. Finally, an example is provided to illustrate how this modified and improved target costing technique works.

• Journal of Agricultural Extension & Community Development
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• v.18 no.3
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• pp.631-664
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• 2011

As agricultural companies encounter number of risks in their business, it is very important to control the risks for their stable management. So we examine the agricultural business risks and propose the risk management strategies for the agricultural companies. For these purpose, we analyze the agricultural business risks with which agricultural companies are confronted, and propose the agricultural companies' the risk management strategies. The results of this study are as follows : First, Changing the risk environment of agricultural business, we have to realize the importance of the agricultural risks and risk management in it. Second, When we choose the risk management strategies which are risk retention, risk avoidance, risk control, risk transfer and insurance, etc., we should always consider the frequency of loss and the severity of loss. Third, If we don't control the agricultural risks, we will be in a position to very difficult situation. So, Agricultural companies should lead to stronger effort to manage the risks for their stable business.

• Korean Management Science Review
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• v.12 no.1
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• pp.111-124
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• 1995

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.