• 한국항해항만학회지
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• 제41권5호
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• pp.303-318
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• 2017

In the shipping industry, it is well known that around 80 % or more of all marine accidents are caused fully or at least in part by human error. In this regard, the International Maritime Organization (IMO) stated that the study of human factors would be important for improving maritime safety. Consequently, the IMO adopted the Casualty Investigation Code, including guidelines to assist investigators in the implementation of the Code, to prevent similar accidents occurring again in the future. In this paper, a process of the human factors investigation is proposed to provide investigators with a guide for determining the occurrence sequence of marine accidents, to identify and classify human error-inducing underlying factors, and to develop safety actions that can manage the risk of marine accidents. Also, an application of these investigation procedures to a collision accident is provided as a case study This is done to verify the applicability of the proposed human factors investigation procedures. The proposed human factors investigation process provides a systematic approach and consists of 3 steps: 'Step 1: collect data & determine occurrence sequence' using the SHEL model and the cognitive process model; 'Step 2: identify and classify underlying human factors' using the Maritime-Human Factor Analysis and Classification System (M-HFACS) model; and 'Step 3: develop safety actions,' using the causal chains. The case study shows that the proposed human factors investigation process is capable of identifying the underlying factors and indeveloping safety actions to prevent similar accidents from occurring.

• 한국공작기계학회논문집
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• 제16권5호
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• pp.48-54
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• 2007

Surface of rapid prototype has inevitably stair-stepping error, which is attributed to the continuous building process of 2 dimensional area. In this study, rounded edge model was established to estimate the roughness of inclined surface which has stair-stepping error. To investigate the roughness of rapid prototypes, specimens that have various surface inclinations were manufactured by various types of RP machines. As the surface inclination increased, the roughness of the specimens manufactured by SL, FDM, or LOM process decreased, which coincides with the simulation results. However, surface roughness of 3DP specimen was almost independent of the inclination. Furthermore, as the angle of surface increased, roughness of poly-jet specimen also increased, which is attributed to the frictional behavior between writing head and scanned area.

• Structural Engineering and Mechanics
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• 제81권1호
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• pp.103-115
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• 2022

The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

• 품질경영학회지
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• 제17권2호
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• pp.158-167
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• 1989

In this paper, a model is presented which incoporates the possibility of quality control at each of the production stages. We consider the TYPE I error and the TYPE II error in inspection procedures. In addition to alternative quality control configurations, the model integrates the carrying costs of in-process and finished inventory, quality of production process, reprocessing including fixed and variable cost. Our policy determines the value of optimal lot-size and reprocessing batch size in reducing the total costs. A numerical example illustrates the model framework and highlights the role of the decision variables.

• 대한안전경영과학회지
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• 제19권3호
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• pp.49-58
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• 2017

This paper suggests a specific model that could efficiently improve the interaction and the interface between MES(Manufacturing Execution System) server and POP(Point of Production) terminal through electronic document server and electronic pen, bluetooth receiver and form paper in disassembly and process inspection works. The proposed model shows that the new method by electronic document automation system can more efficiently perform to reduce processing time for maintenance work, compared with the current approach by handwritten processing system. It is noted in case of the method by electronic document automation system that the effects of proposed model are as follows; (a) While the processing time per equipment for maintenance by the current method was 300 minutes, the processing time by the new method was 50 minutes. (b) While the processing error ratio by the current method was 20%, the error ratio by the new method was 1%.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.852-861
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• 2000

Software reliability growth models are used in testing stages of software development to model the error content and time intervals betwewn software failures. In this paper, using priors for the number of fault with the negative binomial distribution nd the error rate with gamma distribution, Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability. For model selection, we explored the sum of the relative error, Braun statistic and median variation. In Bayesian computation process, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carolo method to compute the posterior distribution. Using simulated data, Bayesian inference and model selection is studied.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(1)
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• pp.349-354
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• 1996

SACOM(Simulation Analyser with Cognitive Operator Model) is being developed at Korea Atomic Energy Research Institute to simulate human operator's cognitive characteristics during the emergency situations of nuclear power plans. An operator model with error mechanisms has been developed and combined into SACOM to simulate human operator's cognitive information process based on the Rasmussen's decision ladder model. The operational logic for five different cognitive activities (Agents), operator's attentional control (Controller), short-term memory (Blackboard), and long-term memory (Knowledge Base) have been developed and implemented on blackboard architecture. A trial simulation with a scenario for emergency operation has been performed to verify the operational logic. It was found that the operator model with error mechanisms is suitable for the simulation of operator's cognitive behavior in emergency situation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.721-724
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• 2000

This paper presents a prediction of tool deflection and resulting machining error fur sculptured surface productions in the ball-end milling process. Due to the different materials and the dimensions of the tool holder and cutter, a cantilever hem model with three uniform sections is proposed fur the tool deflection model. The ability of this model has been verified by a machining experiment. In this study, cutting force and machining error are investigated. This paper provides the prediction of machining error for sculptured surface to improve machining quality for industrial application.

• 한국환경과학회지
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• 제27권7호
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

• International Journal of Precision Engineering and Manufacturing
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• 제4권2호
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• pp.71-76
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• 2003

A virtual machine tool (VMT) is presented in this two-part paper. In Part 1, the analytical foundation for a virtual machining system is developed, which is envisioned as the foundation for a comprehensive simulation environment capable of predicting the outcome of cutting processes. The VHT system undergoes "pseudo-real machining", before actual cutting with a CNC machine tool takes place, to provide the proper cutting conditions for process planners and to compensate or control the machining process in terms of the productivity and attributes of the products. The attributes can be characterized by the machined surface error, dimensional accuracy, roughness, integrity, and so forth. The main components of the VMT are the cutting process, application, thermal behavior, and feed drive modules. In Part 1, the cutting process module is presented. When verified experimentally, the proposed models gave significantly better prediction results than any other methods. In Part 2 of this paper, the thermal behavior and feed drive modules are developed, and the models are integrated into a comprehensive software environment.vironment.