• International Journal of Reliability and Applications
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• v.16 no.1
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• pp.15-26
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• 2015

Present study investigates the fuzzy reliability of some systems using intuitionistic fuzzy Weibull lifetime distribution, in which the lifetime parameters are assumed to be fuzzy parameter due to uncertainty and inaccuracy of data. Expressions for fuzzy reliability, fuzzy mean time to failure, fuzzy hazard function and their ${\alpha}$-cut have been discussed when systems follow intuitionistic fuzzy Weibull lifetime distribution. A numerical example is also taken to illustrate the methodology to calculate the fuzzy reliability characteristics of systems.

• Journal of the Korean Society of Safety
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• v.8 no.4
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• pp.82-90
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• 1993

Manual lifting, as a part of Manual Materials Handling Activities, is recognized by authorities in the field of occupational health and safety as a major hazard to industrial workers. The most important problem in applying fuzzy model of manual materials lifting is the decision of membership functions on each approaches. : Biomechanical, Physiological, Psychophysical. The primary objectives of this paper suggests to process deciding the most acceptable membership functions for establishing permissible weights on manual lifting activities using fuzzy sets.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.123-127
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• 2002

In this paper, we propose spatial prediction model for landslide hazard mapping that can account for the fuzziness of boundaries in thematic maps showing the different environmental impacts, depending on the scales and the resolutions of them. The fuzziness or uncertainty of boundary is represented in favourability function based on fuzzy object concept and the effects of them are quantitatively evaluated with the help of cross validation procedures. To illustrate the proposed schemes, a case study from Boeun, Korea was carried out. As a result, the proposed schemes are helpful to account for intrinsic uncertainties in categorical maps and can be effectively adopted in spatial prediction models for other purposes.

• Proceedings of the KSRS Conference
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• v.2
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• pp.717-720
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• 2006

In this study, we predicted locations vulnerable to ground subsidence hazard using fuzzy logic and geographic information system (GIS). Test was carried out at an abandoned underground coal mine in Samcheok City, Korea. Estimation of relative ratings of eight major factors influencing subsidence and determination of effective fuzzy operators are presented. Eight major factors causing ground subsidence were extracted and constructed as a spatial database using the spatial analysis and the probability analysis functions. The eight factors include geology, slope, landuse, depth of mined tunnel, distance from mined tunnel, RMR, permeability, and depth of ground water. A frequency ratio model was applied to calculate relative rating of each factor, and the ratings were integrated using fuzzy membership function and five different fuzzy operators to produce a ground subsidence susceptibility map. The ground subsidence susceptibility map was verified by comparing it with the existing ground subsidences. The obtained susceptibility map well agreed with the actual ground subsidence areas. Especially, ${\gamma}-operator$ and algebraic product operator were the most effective among the tested fuzzy operators.

• Journal of the Korean Society for Railway
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• v.19 no.2
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• pp.145-158
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• 2016

This paper introduces a risk graph which is one method for determining the SIL as a measure of the effectiveness of signaling system. The purpose of this research is to make up for the weakness of the qualitative determination, which has input value ambiguity and a boundary problem in the SIL range. The fuzzy input valuable consists of consequence, exposure, avoidance and demand rate. The fuzzy inference produces forty eight fuzzy rule by adapting the calibrated risk graph in the IEC 61511. The Max-min composition is utilized for the fuzzy inference. The result of the fuzzy inference is the fuzzy value. Therefore, using the de-fuzzification method, the result should be converted to a crisp value that can be utilized for real projects. Ultimately, the safety requirement for hazard is identified by proposing a SIL result with a tolerable hazard rate. For the validation the results of the proposed method, the fuzzy risk graph model is compared with the safety analysis of the signaling system in CENELEC SC 9XA WG A10 report.

• Journal of Information Technology Services
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• v.8 no.4
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• pp.175-185
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• 2009

Objectifying claims filed during the warranty period, analyzing the current circumstances and improving on the problem in question is an activity worth doing that could reduce the likelihood of claims to occur, cut down on the costs, and enhance the corporate image of the manufacturer. Existing analyses of claims are confronted with two problems. First, you can't precisely assess the risks of claims involved by means of the value of claims per 100 products alone. Second, even in a normal state, the existing approach fails to capture the probabilistic conflicts that escape the upper control limit of claims, thus leading to wrong control activities. To solve the first problem, this paper proposed that a time series detection concept where the claim rate is monitored based on the date when problems are processed and a hazard function for expression of the claim rate be utilized. For the second problem, this paper designed a model whereby to define a normal state by making use of PID (Proportion, Integral, Differential) and infer by way of a fuzzy concept. This paper confirmed the validity and applicability of the proposed approach by applying methods suggested in the actual past data of warranty claims of a large-scaled automotive firm, unlike hypothetical simulation data, in order to apply them directly in industrial job sites, as well as making theoretical suggestions for analysis of claims.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.23-33
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• 2017

Given the expansion of globalization and international trade, the number of apparel consumers is growing every year, making it difficult to estimate the amount of handling needed from the logistics industry. To determine which management factors are important and which ones require improvement, fuzzy AHP was used. Using this method, the factors were ranked in the final analysis as follows: The first and most important factor was training employees (0.17), while the second was fire hazard management (0.169); the third-highest factor was inbound and outbound goods (0.142), and the fourth was the warehouse management system. Barcode management was ranked fifth. By these results, we were able to analyze the processes of clothing warehouses, noting that although the factors appear independent, they are actually connected while proceeding with full management control. Moreover, because of the special characteristics of garments, employee management is crucial. Due to the vulnerability of these goods to fire hazards, this factor must be well managed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.101-106
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• 2006

The geoidal undulations are needed for determining the orthometric heights from the Global Positioning System GPS-derived ellipsoidal heights. There are several methods for geoidal undulation determination. The paper presents a method employing a simple architecture Two Layer Multiquadric-Biharmonic Artificial Neural Network (TLMB-ANN) to approximate an area of 4200 square kilometres quasigeoid surface with GPS-levelling data. Hardy’s Multiquadric-Biharmonic functions is used as the hidden layer neurons’ activation function and Levenberg-Marquardt algorithm is used to train the artificial neural network. In numerical examples five surfaces were compared: the gravimetric geometry hybrid quasigeoid, Support Vector Machine (SVM) model, Hybrid Fuzzy Neural Network (HFNN) model, Traditional Three Layer Artificial Neural Network (ANN) with tanh activation function and TLMB-ANN surface approximation. The effectiveness of TLMB-ANN surface approximation depends on the number of control points. If the number of well-distributed control points is sufficiently large, the results are similar with those obtained by gravity and geometry hybrid method. Importantly, TLMB-ANN surface approximation model possesses good extrapolation performance with high precision.