The purpose of this research was to develop an integrated interface for the usability test of systems or products in the design process. It is capable of automatically creating GOMS models which can predict human task performances. It can generate GOMS models to be interacted with the prototype interfaces. It can also effectively manage various design information and various usability test results to be implemented into the new product and/or system design. Thus we can perform usability test for products or system prototypes more effectively and also reduce time and effort required for this test. For usability tests, we established an integrated interface based on GOMS model by the LabVIEW program. We constructed the system that the linkage to GOMS model is available. Using this integrated interface, the menu structure of mobile phone can be constructed easily. User can design a depth and a breath that he want. The size of button and the label of the button is changable. The path to the goal can be defined by the user. Using a designed menu structure, the experiment could be performed. The results of GOMS model and the actual time are presented. Besides, values of operators of GOMS model can be defined as the value that user wants. Using the integrated interface that we developed, the optimal menu structure deducted. The menu structure that user wants can be established easily. The optimal layout and button size can be decided by comparison of numerous menu structures. User can choose the method of usability test among GOMS model and empirical data. Using this integrated interface, the time and costs can be saved and the optimal menu structure can be found easily.

Principal Component Analysis (PCA) reduces the dimensionality of the process by creating a new set of variables, Principal components (PCs), which attempt to reflect the true underlying process dimension. However, for highly nonlinear processes, this form of monitoring may not be efficient since the process dimensionality can't be represented by a small number of PCs. Examples include the process of semiconductors, pharmaceuticals and chemicals. Nonlinear correlated process variables can be reduced to a set of nonlinear principal components, through the application of Kernel Principal Component Analysis (KPCA). Support Vector Data Description (SVDD) which has roots in a supervised learning theory is a training algorithm based on structural risk minimization. Its control limit does not depend on the distribution, but adapts to the real data. So, in this paper proposes a non-linear process monitoring technique based on supervised learning methods and KPCA. Through simulated examples, it has been shown that the proposed monitoring chart is more effective than $T^2$ chart for nonlinear processes.

This study considers paging schemes that can page some cells or only one cell within the location area to reduce paging cost by using PAs (Paging Agents) and compares their performances by using a new analytic method. There are three ways of paging schemes using PAs; BSPA (Base Staton Paging Agent), 2SPA (2-Step Paging Agent), LAPA (Location Area Paging Agent). This study proposes exact performance of BSPA and 2SPA using a new analytic method based on Markov chain modeling to find the most efficient paging scheme. Numerical results for various circumstances are presented by using proposed analytic method to select a proper paging scheme in mobile communication networks.

In this paper, we study the methodology for the measurement and integration of market risk and credit risk using Copula. We apply the methodology of Rosenberg, and Schuermann(2006) to the assets of pension system. Firstly we estimate dynamics of risk factors and their effects on investment returns, then use the estimated result to simulate future movement of risk factors and distribution of investment returns. Finally we measure integrated risk using integrated return distribution by Copula and simulated future investment return distributions. We found the integrated risk changing with the correlation of risks and investment weights of risks and confirmed the diversification effect of risks. This result is consistent when we use normal Copula and normal marginals, t-Copula and t(3) marginals, and normal Copula and non-parametric marginals. And in the case of non-parametric maginals, larger integrated risk is calculated. It means that use of non-parametric marginals is more conservative.

We develop a nonlinear integer programming model which minimizes the total cost with the optimal number of operators to hire and their optimal allocation to the tasks under the diverse constraints such as the weekly, daily, and hourly maximum allowable abandonment rates for the time-varying inbound call volume. We present a case study based on actual data at a call center, in order to prove the validity of applying the optimization method proposed. By the one-sample two-tailed t-test, we confirm that the expected abandonment rates resulting from the optimization method are identical with the ones from the discrete-event simulation within specified confidence intervals.

The traveling purchaser problem (TPP) is a generalization of the well-known traveling salesman problem (TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. In the last decade, TPP has received some attention of the researchers in the operational research area. However, all of the past researches for TPP are restricted on a single purchaser (vehicle). It could be the limitation to solve the real world problem. The purpose of this paper is to suggest the capacitated multiple TPP (CMTPP). It could be used in inbound logistics optimization in supply chain management area and many others. Since TPP is known as NP-hard, we also developed the heuristic algorithm to solve the CMTPP.

As more individuals and organizations participate in the complex design process of manufacturing industry, collaborative product development and management of the global supply chain have become more popular. Although the product quality concerns once focused on the manufacturing process, they are now directed at earlier stages of the design cycle where the engineering product is created as a 3D CAD model. In this paper, we describe the current state of product data quality activities in the manufacturing industry and the yardstick to measure 3D CAD data quality. Moreover we introduce a quality assurance method through the result of statistical analysis of 3D CAD models and suggest a six sigma level of CAD data quality by analyzing 76 samples provided from three Korean automotive companies.

Design works consist of essential works and subsidiary works. Essential design works means designing creative ideas and productive ideas, while subsidiary design works means helping essential works those are making data tables and specification sheets, checking CAD data's integrity. Subsidiary design works forms the bulk of the whole design process and affects the time limit of delivery. Therefore we propose the automatic data matching system for CAD data's integrity. Proposed system is automatic system supporting subsidiary design works. The data matching system consists of three parts; 1) automatic generation of data tables 2) supporting module for checking CAD data's integrity between Drawings 3) automatic generation of spec. sheets. Developed system was tested in LCD equipment manufacture company and was found to be useful system.

To mitigate space restriction and to raise productivity, some shipbuilding companies use floating-docks on the sea instead of dry-docks on the land. In that case, a floating-crane that can lift very heavy objects (up to 3,600 tons) is used to handle the blocks which are the basic units in shipbuilding processes, and so, very large blocks (these are called the mega-blocks) can be used to build a ship. But, because these mega-blocks can be made only in the area near the floating-dock and beside the sea, the space is very important resource for the process. Therefore, our problem is to make an efficient spatial schedule for the mega-block assembly yard. First of all, we formulate this situation into a mathematical model and find optimal solution for a small problem using a commercial optimization software. But, the software could not give optimal solutions for practical sized problems in a reasonable time, and so we propose a GA-based heuristic algorithm. Through a numerical experiment, finally, we show that the spatial scheduling algorithm can provide a very good performance.

In this paper, we address an optimization problem for minimizing the inspection and rework cost in an inspection-rework system, which forms a network of nodes including a K-stage inspection system, storage areas for items, a source inspection shop, and a re-inspection shop. We assume that (n, 0) acceptance sampling is performed in the source inspection shop and that only 100(1-r)% of items of rejected lots are re-inspected in the re-inspection shop. Since all the nodes are interrelated, in order to formulate our steady-state objective function, we make a steady-state network flow analysis between nodes, and derive both the steady-state amount of flows between nodes and the steady-state fraction defectives by solving a nonlinear balance equation. Finally we provide some fundamental properties and an enumeration procedure for determining the optimal values of (K, r) which both minimizes our objective function and attains a given target average outgoing quality.