This paper introduces some of the developments related to the handling equipment in container terminals and various new conceptual handling systems that have been proposed during the last several decades. The basic ideas behind the previous equipment improvements are analyzed to identify future directions that can be used for devising new handling systems. The handling systems in the container terminals include a quayside handling system, transport system, and yard system. In response to the deployment of mega-sized vessels for container transportation systems, productivity improvement has become one of the most urgent issues in the container terminals. This paper analyzes the previous improvements made for achieving higher productivity in the three subsystems of container handling. Some conceptual handling systems are introduced including the linear motor conveyance system (LMCS), automated storage and retrieval systems (AR/RS), overhead grid rail (GRAIL), SPEEDPORT, SuperDock, the automated container system by ZPMC (ACS-ZPMC), and AUTOCON.

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

This research proposes a Pareto-based multi-objective optimization approach to class-based storage warehouse design, considering a two-block warehouse that operates under the class-based storage policy in a low-level, picker-to-part and narrow aisle warehousing system. A mathematical model is formulated to determine the number of aisles, the length of aisle and the partial length of each pick aisle to allocate to each product class that minimizes the travel distance and maximizes the usable storage space. A solution approach based on multiple objective particle swarm optimization is proposed to find the Pareto front of the problems. Numerical examples are given to show how to apply the proposed algorithm. The results from the examples show that the proposed algorithm can provide design alternatives to conflicting warehouse design decisions.

This research aims to formulate a mathematical model and develop an algorithm for solving a location problem in emergency medical service vehicle parking. To find an optimal parking location which has the least risk score or risk priority number calculated from severity, occurrence, detection, and distance from parking location for emergency patients, data were collected from Pratoom sub-district Disaster Prevention and Mitigation Center from October 2010 to April 2011. The criteria of risk evaluation were modified from Automotive Industry Action Group's criteria. An adaptive simulated annealing algorithm with multiple cooling schedules called multi-agent simulated quenching (MASQ) is proposed for solving the problem in two schemes of algorithms including dual agent and triple agent quenching. The result showed that the solution obtained from both scheme of MASQ was better than the traditional solution. The best locations obtained from MASQ-dual agent quenching scheme was nodes #5 and #133. The risk score was reduced 61% from 6,022 to 2,371 points.

While systems engineering has been widely applied to complex system development, some evidences are reported about major budget and schedule overruns in systems engineering applied. On the other hand, many organizations have been deploying Design for Six Sigma (DFSS) to build Six Sigma momentums in the area of design and development for their products and processes. To explore the possibility of having a DFSS complement systems engineering process, this process reviews the systems engineering with their categories of effort and DFSS with its methodologies. A comparison of the systems engineering process and DFSS indicates that DFSS can be a complement to systems engineering for delivering higher quality products to customers faster at a lower cost. We suggest a simplified framework of systems engineering process, that is, PADOV which was derived from the generic systems engineering process which has been applied to the development of T-50 advanced supersonic trainer aircraft by Korea Aerospace Industries (KAI) with technical assistance of Lockheed Martin. We demonstrated that each phase of PADOV framework is comprehensively matched to the pertinent categories of systems engineering effort from various standards.

Korea has shown a tremendous leap in economic development in a short span of time, and the world is watching Korea's economy with keen interest. Development of industries that are implementing information systems (IS) has played a role in leading economic growth in Korea. Because of the success of Korean firms, the creation of case studies for implementing IS in Korean firms was attempted. Despite the many case studies, analysis of the motivations and results, for implementing IS as a firm's strategic purpose, was rarely conducted. Therefore, this paper investigates some Korean firms' cases studies in order to show the best practice example of implementing and adopting IS strategically. Nine cases of Korean firms' strategic use of IS were analyzed in various industry fields. Each case consists of the following four categories: company overview, background implementing IS, adoption of IS for strategic purpose, and the results of implementing IS. In order to help various companies to take an action with their IS implementation and its strategic use, implications from the cases are summarized to show how Korean firms strategically introduced IS for solving particular problems that they had faced.

This study proposes a multi-level data analysis approach to identify both superficial and latent relationships among variables in the data set obtained from a vocational rehabilitation (VR) services program of people with significant disabilities. At the first layer, data mining and statistical predictive models are used to extract the superficial relationships between dependent and independent variables. To supplement the findings and relationships from the analysis at the first layer, association rule mining algorithms at the second layer are employed to extract additional sets of interesting associative relationships among variables. Finally, nonlinear nonparametric canonical correlation analysis (NLCCA) along with clustering algorithm is employed to identify latent nonlinear relationships. Experimental outputs validate the usefulness of the proposed approach. In particular, the identified latent relationship indicates that disability types (i.e., physical and mental) and severity (i.e., severe, most severe, not severe) have a significant impact on the levels of self-esteem and self-confidence of people with disabilities. The identified superficial and latent relationships can be used to train education program designers and policy developers to maximize the outcomes of VR training programs.

With the development of computer storage and the rapidly growing ability to process large amounts of data, the multivariate control charts have received an increasing attention. The existing univariate and multivariate control charts are a single hypothesis testing approach to process mean or variance by using a single statistic plot. This paper proposes a multiple hypothesis approach to developing a new multivariate control scheme. Plotted Hotelling's $T^2$ statistics are used for computing the corresponding p-values and the procedure for controlling the false discovery rate in multiple hypothesis testing is applied to the proposed control scheme. Some numerical simulations were carried out to compare the performance of the proposed control scheme with the ordinary multivariate Shewhart chart in terms of the average run length. The results show that the proposed control scheme outperforms the existing multivariate Shewhart chart for all mean shifts.

The present paper extends the idea of tightened-normal-tightened sampling scheme to group acceptance sampling plans under the time truncated life tests. We consider three famous distributions that are widely used in the area of reliability such as the generalized exponential distribution, the Weibull distribution, and the Birnbaum-Saunders distribution in the proposed sampling plan. The plan parameters are determined such that the producer's risk and the consumer's risk are satisfied at the specified median life. Extensive tables showing plan parameters are provided at various values of the experiment time and the consumer's risk for each of three distributions for the practical use. Some examples are given to illustrate the procedure of the proposed plan.

This research proposes a framework of buffer management for multi-project systems in the critical chain project management (CCPM) method, expressed in the form of max-plus linear (MPL) representation. Since time buffers are inserted in the projects for absorbing uncertainties in task durations and protecting the completion times, the proposed method provides a procedure for frequently surveying the rates of consumed buffers and the rate of elapsed times. Their relation expresses the performance of the projects which is plotted on a chart through the completed processes. The chart presents the current performance of the projects and their interaction, which alerts managers to make necessary decisions at the right time for managing each project and the entire multi-project system. The proposed framework can analyze the complex system readily, and it enables managers to make an effective decision on scheduling. The effectiveness of the framework is demonstrated through a numerical example.