There are various types of unexpected troubles in service of a thermal power plant, which consists of many complicated high-tech mass equipments. The troubles are mostly caused by the manufacturing defects, the material deteriorations, the human errors, and others. Failures of its system due to the troubles, can bring on the extravagant economic loss and the qualitative degradation of electricity. Especially, it is most important to find a way to decrease human errors because it can result in not only the economic loss, but also morale declination of employees or the department related to the trouble. Therefore, we categorize previous troubles related to the human errors, and try to show the causations and the counter-measures based on the various categories such as maintenance, an operation, and system of the thermal power plants.

Connected-(r,s)-out of-(m,n) : F system is an important topic in redundancy design of the complex system reliability and it's maintenance policy. Previous studies applied Monte Carlo simulation and genetic, simulated annealing algorithms to tackle the difficulty of maintenance policy problem. These algorithms suggested most suitable maintenance cycle to optimize maintenance pattern of connected-(r,s)-out of-(m,n) : F system. However, genetic algorithm is required long execution time relatively and simulated annealing has improved computational time but rather poor solutions. In this paper, we propose the ant colony optimization approach for connected-(r,s)-out of-(m,n) : F system that determines maintenance cycle and minimum unit cost. Computational results prove that ant colony optimization algorithm is superior to genetic algorithm, simulated annealing and tabu search in both execution time and quality of solution.

In Korean peninsular, Air Defense with SAM(Surface-to-Air Missile) is very important, because of threatening by North Korea's theater ballistic missiles installed with nuclear or biochemistry. Effective and successful defense operation largely depends on two factors, SAM's location and the number of SAM for each target based on missile's availability in each SAM's location. However, most previous papers have handled only the former. In this paper, we developed Multi-heuristic algorithm which can handle both factors simultaneously for solving allocation problem of the batteries and missile assignment problem in each battery. To solve allocation problem, genetic algorithm is used to decide location of the batteries. To solve missile assignment problem, a heuristic algorithm is applied to determine the number of SAM for each target. If the proposed model is applied to allocation of SAM, it will improve the effectiveness of missile defense operations.

This paper considers a transporter scheduling problem under dynamic block transportation environment in shipbuilding. In dynamic situations, there exist the addition or cancellation of block transportation requirements, sudden breakdowns and maintenance of transporters. The transportation of the blocks in the shipyard has some distinct characteristics. Some blocks are available to be picked up at a specific time during the planning horizon while some other blocks need to be delivered before a specific time. These requirements cause two penalty times : 1) delay times incurred when a block is picked up after a required start time, and 2) tardy times incurred when a block shipment is completed after the required delivery time. The blocks are located at different areas in the shipyard and transported by transporters. The objective of this paper is to propose heuristic algorithms which minimize the weighted sum of empty transporter travel times, delay times, and tardy times. Four heuristic algorithms for transporter scheduling are proposed and their performance is evaluated.

It is important to choose and develop right business model in the process of implementing the ubiquitous service concept. In particular, it is also required to build a method which can assist in establishing a business model in a competitive perspective to differentiate business strategy. However, we could not find the existing studies which tried to develop business model including methods on how to differentiate business strategy in a competitive environment. In this study, we propose an ontology for repository of ubiquitous business model and address on how to apply the proposed business model repository to real ubiquitous industry. We also built a repository of unlicensed wireless device industry to check the applicability of proposed ubiquitous business model ontology and to show the various examples. We expect that building the business model repository contributes to reduce the redundancy and inefficiency for industry as well as to increase likelihood of business success for an individual company.

Agile and flexible manufacturing systems make it mandatory that a control program should have features such as agility, flexibility, and reusability in order to run manufacturing unit smoothly. PLCs are the most frequently used control program in manufacturing systems. PLC programs are mostly programmed by subcontraction, which makes correction of code very difficult. As a result, it may cause delay during down time and ramp up time which leads to big loss of revenue and goodwill. To prevent delay during the times, this paper proposes systematic process analysis and application method for programmable logic controller like LLD (Ladder Logic Diagram). The proposed method uses modified human-error investing techniques for documentation and transforming technique to program LLD from the documentation. Furthermore, this paper demonstrates an example of piston mechanism to explain the proposed method.

Efficiency evaluation methods of manufacturing processes have relied on absolute measures such as defective rate and throughput per person, ignoring various process characteristics. To overcome the limitation, we propose an evaluation model which reflects characteristics of each process. It is composed of three measures : utilization, performance, and improvement. The suggested model utilizes a combination of DEA and AHP methods. The proposed method has been applied to efficiency evaluation of cellular phone case manufacturing processes.

The productivity increase by technological advance is the biggest driving force of economic growth. In this paper, we investigate the inputs and outputs of the manufacturing and service industries in Korea. We also estimate the total and partial factor productivities of both industries using the Solow model and the Kendrick model. Finally, we analyze the contribution of each input factor to industrial growth.

Digital Virtual Manufacturing is a technology to facilitate effective product developments and agile productions by digital model representing the physical and logical schema and the behavior of real manufacturing system, and it includes product, resources, processes and plant. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this research, we constructed a sophisticated digital virtual factory of a Korean automotive company's press shop. For efficient constructions of a digital virtual factory useful to kinematic simulations and visualizations, we analyzed entire business process and detailed activities of press engineering. Also, we evaluated geometries, structures, characteristics and motions of a plant and machines in press shop. The geometric model and related data of a virtual press shop are built and managed by a modeling standard defined in this paper. The virtual manufacturing simulation of press machines is conducted to evaluate kinematic motions, cycle time and locations of components using geometric models and related data. It's for interference checks and productivity improvements. We expect that this virtual press shop helps us to achieve great savings in time and cost in many manufacturing preparation activities in the new car development process of automotive companies.

Warehouses form an important link in a supply chain network. Among a variety of activities in warehouses, order picking is the process of retrieving a number of items out of storage to meet customer orders. Today, as the transactions through direct sales are wide spread, warehouses often receive a large amount of small orders to be handled within tight time windows, which makes fast and efficient order picking more important than ever. This paper examines a new order picking method where the concept of bucket brigade (BB) is applied. Bucket brigade is a way of dynamically coordinating workers who progressively perform a set of operations along a flow line. In bucket brigades, a worker is not assigned his jobs in a static way. Each worker takes a job from his predecessor when he is free. We identify some considerations when bucket brigades are applied to order picking activities. A new BB picking protocol is presented to improve existing BB picking protocols. Through simulation experiments, the performance of BB order picking is evaluated under various logistics environments.

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.