• Journal of Korean Society for Quality Management
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• v.40 no.2
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• pp.186-198
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• 2012

Since Duncan(1956) first proposed an economic design of $\bar{X}$-control charts, most of the succeeding works on economic design of control charts assumed the exponential failure model like Duncan. Hu(1984), however, assumed a more versatile Weibull failure model to develop an economic design of $\bar{X}$-control charts and Banerjee and Rahim(1988) further improved Hu's design by changing the assumption of fixed-length sampling intervals to variable-length ones. In this article we follow the approach of Banerjee and Rahim(1988) but include a pair of warning limits inside the control limits in order to search for a failure without stopping the process when the sample mean falls between warning and control limits. The computational results indicate that the proposed model gives a lower cost than Banerjee and Rahim's model unless the early failure probability of a Weibull distribution is relatively large. The reduction in cost is shown to become larger as the cost of production loss outweighs the cost of searches for a failure.

• Proceedings of the Fisheries Business Administration Society of Korea Conference
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• 2007.12a
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• pp.167-184
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• 2007

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut-down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t-test is used to identify the differences in financial variables between the distressed group and the non-distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990$\sim$1993), period 2(1994$\sim$1997), period 3(1998$\sim$2002). The final model built from whole sample appled each three sub-samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub-sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• The Journal of Fisheries Business Administration
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• v.39 no.2
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• pp.61-79
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• 2008

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut - down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t - test is used to identify the differences in financial variables between the distressed group and the non - distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990 - 1993), period 2(1994 - 1997), period 3(1998 - 2002). The final model built from whole sample appled each three sub - samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub - sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• International Journal of Reliability and Applications
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• v.4 no.2
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• pp.51-56
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• 2003

A k-out-of-n system with n identical and independent components is considered in which the components takes two types of function: 0 (open-circuit) or 1 (closed) on command (e.g. electromagnetic relays and solid state switches). Components are subject to two types of failure on command: failure to close or failure to open. In our k-out-of-n system, failure of (n-k)＋1 or more components to close causes to the close failure of the system, or failure of k or more components to open causes the open failure of the system. The long-run average cost rate is obtained. We find the optimal k minimizing the long run average cost rate for given n. A numerical example is presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.261-268
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• 2017

The development of ICT technology centered on mobile smart platforms have been emerging as a shared economic platform based on collaborative consumption. In this study, we analyze what factors affect success and failure in commercialized shared economic platforms from 2008 to 2016, and present what policy factors are needed to activate shared economic platform. To do this, we analyze successful cases of shared economic platforms and failed cases, derive key variables that affect success and failure, and conduct inductive analysis based on ID 3 algorithm based on them. Through this, we present the policy factors for the commercial success of the shared economic platform by deriving the rules for the success and failure of the shared economic platform.

• Journal of Welding and Joining
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• v.28 no.6
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• pp.45-50
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• 2010

Most of joining processes for machine and steel structure are performed by butt and fillet welding. The mechanical properties and fatigue strength of their welding zone can be effected largely by the differential of generated heat and changes of grain size according to thickness of material and number of passes in welding process. In this study, it was investigated about characteristics of fatigue failure according to thickness of material and number of passes in cruciform fillet weld zone as the basic study for safe and economic design of welding structures. Fracture modes in cruciform fillet weld zone are classified into toe failure and root failure according to non-penetrated depth. It can be accomplished economic design of welding structures considering fatigue strength when the penetrated depth in fillet weld zone is controled properly.

• Economic and Environmental Geology
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• v.33 no.2
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• pp.117-128
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• 2000

Regional evaluations of slope stability by the failure criterion and by environmental geological factors were conducted. The failure criterion is the general conditions for plane failure which consider the geometrical conditions between geological discontinuities and topographical slope planes. The factor focused in this condiction is dip and dip direction. Geostatics, named semivariogram was used for establishing structural domains in slope stability evaluation by the failure criterion. The influential range was calculated to 6 km in the case of dip direction of dominant joint set and 7 km in the case of dip of the same dominant joint set. Then applying this failure criterion to the study area produced a slope stability map using the established domains and slopes generated by TIN module of ARC/INFO GIS. This study considered another regional slope stability analysis. 5 failure-driven factors 9the unstable slope map, geology, engineering soil, groundwater, and lineament density) were selected and used as data coverages for regional slope stability evaluation by geoenvironmental factors. These factors were weighted and overlayed in GIS. From the graph of cumulatave area (%) and instability index, finding critical points classified the instability indices. The most unstable slopes are located in the southern area of Mt. Eorae, Dabul-ri, and the eastern area of Junkok-ri in the first area is plane failure. Also, the expected orientations of failure are 59/338 and 86/090 (dip/dip direction).

• IE interfaces
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• v.15 no.1
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• pp.64-72
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• 2002

Broaching machine is widely used for machining inner shaped slots in the work-pieces, and provides vertical motion (usually hydraulically powered) between tool and work-piece. In this study, we modelled the tool life process and investigated economic tool life of broaching machine. Tool life process is divided into wear-process and succeeding failure process. Wear process is defined as machining wear and failure process as 'chipping' occurred by random shock. We modelled wear process as linear regression function for products amounts and assumed failure process as Poisson process. Economic tool life is defined as the number of lots which minimizes average tool related cost per lot and analyzed by using age replacement policy technique. As tool-related cost factors, we consider tool replacement cost, tool maintenance cost and quality costs of products. The results of this study can be applied to analyze life process of general machining tools.

• International Area Studies Review
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• v.21 no.4
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• pp.271-294
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• 2017

Despite a huge amount of foreign assistance and close economic guidance by international donors throughout the past decades, Zambia today still suffer from a high level of aid dependency and the absence of sustainable economic development. In this study, I investigate the factors that resulted in aid (and development) failure in Zambia, focusing on institutional/historical contexts. I propose that in Zambia, government has largely failed to implement (or even produce) effective economic policies that could lead to successful use of foreign assistance for long-term, sustainable development. In particular, I focus on the nature of state and politics in Zambia, and argue that failed politics is one of the main causes of development and aid failure in Zambia and highlight colonial legacies and other contextual/institutional factors to understand the nature of politics and state in Zambia. In particular, this paper proposes that the Zambian case demonstrates that foreign aid and donor influence could worsen the situation directly by simply providing wrong guidance and also by further weakening the state (and institutional) capacity of the recipient country.

• Journal of Korean Society for Quality Management
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• v.43 no.4
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• pp.471-488
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• 2015

Purpose: Double sampling $T^2$ chart is a useful tool for detecting a relatively small shift in process mean when the process is controlled by multiple variables. This paper finds the optimal design of the double sampling $T^2$ chart in both economical and statistical sense under Weibull failure model. Methods: The expected cost function is mathematically derived using recursive equation approach. The optimal designs are found using a genetic algorithm for numerical examples and compared to those of single sampling $T^2$ chart. Sensitivity analysis is performed to see the parameter effects. Results: The proposed design outperforms the optimal design of the single sampling $T^2$ chart in terms of the expected cost per unit time and Type-I error rate for all the numerical examples considered. Conclusion: Double sampling $T^2$ chart can be designed to satisfy both economic and statistical requirements under Weibull failure model and the resulting design is better than the single sampling counterpart.