• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.298-304
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• 2009

This paper describes an algorithm that improves 3D reconstruction result using a multi-sensor fusion disparity map. We can project LRF (Laser Range Finder) 3D points onto image pixel coordinatesusing extrinsic calibration matrixes of a camera-LRF (${\Phi}$, ${\Delta}$) and a camera calibration matrix (K). The LRF disparity map can be generated by interpolating projected LRF points. In the stereo reconstruction, we can compensate invalid points caused by repeated pattern and textureless region using the LRF disparity map. The result disparity map of compensation process is the multi-sensor fusion disparity map. We can refine the multi-sensor 3D reconstruction based on stereo vision and LRF using the multi-sensor fusion disparity map. The refinement algorithm of multi-sensor based 3D reconstruction is specified in four subsections dealing with virtual LRF stereo image generation, LRF disparity map generation, multi-sensor fusion disparity map generation, and 3D reconstruction process. It has been tested by synchronized stereo image pair and LRF 3D scan data.

• Fashion & Textile Research Journal
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• v.14 no.4
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• pp.597-606
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• 2012

To increase the productivity and product quality of customized baseball jerseys, this study developed a multi-variable system for a production process that efficiently controls diverse production management factors. The working time was measured through the establishment of a standard process where skilled workers and Chinese factory workers manufactured 5 sets of the same basic design jerseys. Based on the measured working time (1,136 seconds/per unit), the multi-variable process control system was developed, where hourly production management is possible according to the involved workers and equipment types. Each process was assigned accoding to the production management factors for a total of 28 standard processes. The processes were developed based on consideration of work characteristics according to the order of needlework of open-type set baseball jerseys with sleeves(the basic design of baseball jerseys)to result in a customized production system structure that could be set up with multi-variables. As a result, a total 12 types of systems were developed in consideration of the personnel involved and the number of equipments. The optimal production management system (with the highest efficiency compared to the number of workers)was A-2, B-1, C-1. D-2, E-2, F-1, and G-1. This system had extremely high efficiency and showed 99% assignment efficiency for the 7-person team. Though not optimal, possible process assignment for each working personnel is proposed as a reserve process in case work modification is inevitable due to malfunctions and the absence of equipments.

• Journal of Korean Society for Quality Management
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• v.45 no.2
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• pp.191-207
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• 2017

Purpose: To develop an interactive version of the conventional process capability-based approach, called 'Interactive Process Capability-Based Approach (IPCA)' in multi-response surface optimization to obtain a satisfactory compromise which incorporates a decision maker(DM)'s preference information precisely. Methods: The proposed IPCA consists of 4 steps. Step 1 is to obtain the estimated process capability indices and initialize the parameters. Step 2 is to maximize the overall process capability index. Step 3 is to evaluate the optimization results. If all the responses are satisfactory, the procedure stops with the most preferred compromise solution. Otherwise, it moves to Step 4. Step 4 is to adjust the preference parameters. The adjustment can be made in two modes: relaxation and tightening. The relaxation is to make the importance of one of the satisfactory responses lower, which is implemented by decreasing its weight. The tightening is to make the importance of one of the unsatisfactory responses higher, which is implemented by increasing its weight. Then, the procedure goes back to Step 2. If there is no response to be adjusted, it stops with the unsatisfactory compromise solution. Results: The proposed IPCA was illustrated through a multi-response surface problem, colloidal gas aphrons problem. The illustration shows that it can generate a satisfactory compromise through an interactive procedure which enables the DM to provide his or her preference information conveniently. Conclusion: The proposed IPCA has two major advantages. One is to obtain a satisfactory compromise which is faithful to the DM preference structure. The other is to make the DM's participation in the interactive procedure easier by using the process capability index in judging satisfaction/unsatisfaction. The process capability index is very familiar with quality practitioners as well as indicates the process performance levels numerically.

• Design & Manufacturing
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• v.17 no.4
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• pp.72-78
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• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.305-318
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• 1999

In this paper we derive the higher order expansions of the first four cumulants of multi-dimensional Maximum Likelihood Estimator (MLE) under the general parametric model up to and including terms of order O({{{{ {n }^{-1 } }}}}) Also we obtain the explicit form of the expansion of the normalizing trans formation of multi-dimensional MLE and show that the suggested normalizing process is much better than the normal approximation based on central limit theorem through example.

• Nonlinear Functional Analysis and Applications
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• v.27 no.4
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• pp.731-742
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• 2022

In this paper, we present a new mixed type iterative process for approximating the common fixed points of single-valued nonexpansive mapping and multi-valued nonexpansive mapping in a CAT(0) space. We demonstrate strong and weak convergence theorems for the new iterative process in CAT(0) spaces, as well as numerical results to support our theorem.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.53-56
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• 2002

We have developed a Monte Carlo (MC) simulator for electron beam lithography in multi-layer resists and multi-layer substrates in order to fabricate and develop high-speed PHEMT devices for millimeter- wave applications. For the deposited energy calculation to multi-layer resists by electron beam in MC simulation, we modeled newly for multi-layer resists and heterogeneous multi-layer substrates. Using this model, we simulated T-gate or r-gate fabrication process in PHEMT device and showed our results with SEM observations.

• 한국가스학회:학술대회논문집
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• 1997.09a
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• pp.115-120
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• 1997

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.70-75
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• 1993

Chatter vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life machine life and the productivity of machining process. The In-process monitoring & control of chatter vibration is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer,Accelerometer and AE(Acoustic Emission) sensor for the credible detection of chatter vibration. And a new approach using a neural network to process the features of multi-sensor for the recognition of chatter vibration in turning operation is proposed. With the back propagation training process, the neural network memorize and classify the feature difference of multi-sensor signals.

• Korean Journal of Materials Research
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• v.26 no.8
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• pp.427-429
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• 2016

A multi-step deposition process for the gap-filling of submicrometer trenches using dimethyldimethoxysilane (DMDMOS), $(CH_3)_2Si(OCH_3)_2$, and $C_xH_yO_z$ by plasma enhanced chemical vapor deposition (PECVD) is presented. The multi-step process consisted of pre-treatment, deposition, and post-treatment in each deposition step. We obtained low-k films with superior gap-filling properties on the trench patterns without voids or delamination. The newly developed technique for the gap-filling of submicrometer features will have a great impact on inter metal dielectric (IMD) and shallow trench isolation (STI) processes for the next generation of microelectronic devices. Moreover, this bottom up gap-fill mode is expected to be universally for other chemical vapor deposition systems.