• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.74-79
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• 2001

In this two-part paper, a virtual machine tool (VMT) is presented. In part 1, the analytical foundation of a virtual machining system, envisioned as the foundation for a comprehensive simulation environment capable of predicting the outcome of cutting processes, is developed. The VMT system purposes to experience the pseudo-real machining before real cutting with a CNC machine tool, 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 products. The attributes can be characterized with the machined surface error, dimensional accuracy, roughness, integrity and so forth. The main components of the VMT are cutting process, application, thermal behavior and feed drive modules. In part 1, the cutting process module is presented. The proposed models were verified experimentally and gave significantly better prediction results than any other method. The thermal behavior and feed drive modules are developed in part 2 paper. The developed models are integrated as a comprehensive software environment in part 2 paper.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.11
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• pp.47-56
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• 2019

A deep neural network (DNN) model was proposed to predict the upset in the inertia friction welding process using a database comprising results from a series of FEM analyses. For the database, the upset length, upset beginning time, and upset completion time were extracted from the results of the FEM analyses obtained with various of axial pressure and initial rotational speed. A total of 35 training sets were constructed to train the proposed DNN with 4 hidden layers and 512 neurons in each layer, which can relate the input parameters to the welding results. The mean of the summation of squared error between the predicted results and the true results can be constrained to within 1.0e-4 after the training. Further, the network model was tested with another 10 sets of welding input parameters and results for comparison with FEM. The test showed that the relative error of DNN was within 2.8% for the prediction of upset. The results of DNN application revealed that the model could effectively provide welding results with respect to the exactness and cost for each combination of the welding input parameters.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.24-29
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• 2002

In any rapid prototyping process, the layer by layer building process introduces an area error between the staircase and the surface line specified by the computer-aided design model. This affects the dimensional accuracy as well as the surface finish for different part build orientations. This paper describes a methodology for computing the area error for any orientation of the part built by the fused deposition modelling system. This technique can be applied to determine the best build orientation of the part, based on the minimum area error. This technique is verified by comparing the results with the experimental measurements of the area error of the parts built at different orientations.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.2
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• pp.73-80
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• 2001

The objective of this research is to develop a measurement error model for sculptured surface in On-Machine Measurement(OMM) process based on a closed-loop configuration. The geometric error model of each axis of a vertical CNC machining center is derived using a 4$\times$4 homogeneous transformation matrix. The ideal locations of a touch-type probe for the sculptured surface measurement are calculated from the parametric surface representation and X-, Y- directional geometric errors of the machine. Also the actual coordinates of the probe are calculated by considering the pre-travel variation of a probe and Z-directional geometric errors. Then, the step-by-sep measurement error analysis method is suggested based on a closed-loop configuration of the machining center including workpiece and probe errors. The simulation study shows the simplicity and effectiveness of the proposed error modeling strategy.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.46-55
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• 1996

As industrial standard data, the STL format which approximates three dimensional CAD model to triangular facets, is used for RP(Rapid Prototyping) system in recent days. Because most RP system take the only form of two dimensional line segments as an input stream inspite of its imperfectness while converting into STL format, a CAD model is converted into a standard industrial format which is composed of many triangular facets. The error verifying process is composed of four main steps, and these are 1) Remove facets with two or more vertices equal to each other. 2) Fix overlapping error such as more than three facets adjacent to anedge. 3) Fill holes in the mesh by using Delaunay triangulation method. 4) Correct the wrong direction and normal vectors. This paper is concerned with serching the mentioned errors in advance and modifying them.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.172-181
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• 1999

The objective of this research is to develop a measurement error model for sculptured surfaces in On-Machine Measurement (OMM) process based on a closed-loop configuration. The geometric error model of each axis of a vertical CNC Machining center is derived using a 4${\times}$4 homogeneous transformation matrix. The ideal locations of a touch-type probe for the scupltured surface measurement are calculated from the parametric surface representation and X-, Y- directional geometric errors of the machine. Also, the actual coordinates of the probe are calculated by considering the pre-travel variation of a probe and Z-directional geometric errors. Then, the step-by-step measurement error analysis method is suggested based on a closed-loop configuration of the machining center including workpiece and probe errors. The simulation study shows the simplicity and effectiveness of the proposed error modeling strategy.

• Journal of Distribution Science
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• v.12 no.2
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• pp.59-71
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• 2014

Purpose - In recent years, many firms have attempted various approaches to cope with the continual increase of aviation transportation. The previous research into freight charge forecasting models has focused on regression analyses using a few influence factors to calculate the future price. However, these approaches have limitations that make them difficult to apply into practice: They cannot respond promptly to small price changes and their predictive power is relatively low. Therefore, the current study proposes a freight charge-forecasting model using time series data instead a regression approach. The main purposes of this study can thus be summarized as follows. First, a proper model for freight charge using the autoregressive integrated moving average (ARIMA) model, which is mainly used for time series forecast, is presented. Second, a modified ARIMA model for freight charge prediction and the standard process of determining freight charge based on the model is presented. Third, a straightforward freight charge prediction model for practitioners to apply and utilize is presented. Research design, data, and methodology - To develop a new freight charge model, this study proposes the ARIMAC(p,q) model, which applies time difference constantly to address the correlation coefficient (autocorrelation function and partial autocorrelation function) problem as it appears in the ARIMA(p,q) model and materialize an error-adjusted ARIMAC(p,q). Cargo Account Settlement Systems (CASS) data from the International Air Transport Association (IATA) are used to predict the air freight charge. In the modeling, freight charge data for 72 months (from January 2006 to December 2011) are used for the training set, and a prediction interval of 23 months (from January 2012 to November 2013) is used for the validation set. The freight charge from November 2012 to November 2013 is predicted for three routes - Los Angeles, Miami, and Vienna - and the accuracy of the prediction interval is analyzed using mean absolute percentage error (MAPE). Results - The result of the proposed model shows better accuracy of prediction because the MAPE of the error-adjusted ARIMAC model is 10% and the MAPE of ARIMAC is 11.2% for the L.A. route. For the Miami route, the proposed model also shows slightly better accuracy in that the MAPE of the error-adjusted ARIMAC model is 3.5%, while that of ARIMAC is 3.7%. However, for the Vienna route, the accuracy of ARIMAC is better because the MAPE of ARIMAC is 14.5% and the MAPE of the error-adjusted ARIMAC model is 15.7%. Conclusions - The accuracy of the error-adjusted ARIMAC model appears better when a route's freight charge variance is large, and the accuracy of ARIMA is better when the freight charge variance is small or has a trend of ascent or descent. From the results, it can be concluded that the ARIMAC model, which uses moving averages, has less predictive power for small price changes, while the error-adjusted ARIMAC model, which uses error correction, has the advantage of being able to respond to price changes quickly.

• Journal of the Ergonomics Society of Korea
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• v.23 no.4
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• pp.9-21
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• 2004

As menu structure of household appliance is complicated, user's cognitive workload frequently occurs errors. In existing studies, errors didn't present that interpretation for cognitive factors and alternatives, but are only considered as statistical frequency. Therefore, error classification and analysis in tasks is inevitable in usability evaluation. This study classified human error throughout information process model and navigation behavior. Human error is defined as incorrect decision and behavior reducing performance. And navigation is defined as unrelated behavior with target item searching. We searched and analyzed human errors and its causes as a case study, using mobile phone which could control appliances in near future. In this study, semantic problems in menu structure were elicited by SAT. Scenarios were constructed by those. Error analysis tests were performed twice to search and analyze errors. In 1st prototype test, we searched errors occurred in process of each scenario. Menu structure was revised to be based on results of error analysis. Henceforth, 2nd Prototype test was performed to compare with 1st. Error analysis method could detect not only mistakes, problems occurred by semantic structure, but also slips by physical structure. These results can be applied to analyze cognitive causes of human errors and to solve their problems in menu structure of electronic products.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.478-484
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• 1990

An automatic tuning method of a PID controller which is used for single input single output processes is proposed. In the proposed tuning method, the frequency response data model is adopted along with the performance index which is an integral of time weighted square error between reference model and process frequency response data model for tuning. This method is easier to retune when either the process dynamics is changed or the reference model is changed. Finally, an example is provided to show the usefulness of the method.