In this paper, we evaluate life annuity plans for Korean pre-retired single and married couple participating Korea National Pension (KNP) and find optimal life annuity strategy by using utility-based measurements called AEW (Annuity Equivalent Wealth). Specifically, we extend a previous study to obtain a detailed optimal combination of annuitizing age and wealth in terms of percentage of net wealth at the time of retirement. A nonlinear optimization model is formulated with the objective of maximizing utility on consumption and bequest, and the dynamic programming (DP) technique is used to solve this problem. We find that there exist consistent patterns in optimal combinations of annuitizing age and wealth. Also, for all cases the optimal combination is significantly better than several other combinations. The results indicate that using the optimal approach can be beneficial to practitioners in insurance industry and prospective purchasers of life annuity. We conclude the paper with some discussions and suggestions.

The automatic radiopharmaceutical module consists of several 2-way valves, couple of syringes, gas supply unit, heating(cooling) unit and sensors to control the chemical reagents as well as to help the chemical reaction. In order to control the actuators of radiopharmaceutical module, the process is tabulated using spread sheet as like excel. Unlike the common program, a trivial error is too critical to allowed in the process because the error can lead to leak the radioactive reagent and to cause the synthesis equipment failure during synthesizing. Hence, the synthesis process has been validated using graphic simulation while the operator checks the whole process visually and undergoes trial and error. The verification of the synthesis process takes a long time and has a difficulty in finding the error. This study presents a methodology to verify the process algebraically while the radiopharmaceutical module is converted to the network model. The proposed method is validated using actual synthesis process.

In This Study, New Product Development Activities, Innovation Activities, Technical Cooperation Activities may have an Impact on Competitive Advantage, Development Performance and Business Performance. The aim of Empirical Analyze is to identify the Structural Causal Relationship among the Activities and Performance Factors. We get the Results as Follows : New Product Development Activities have a Positive Impact on Competitive Advantage as well as the Development Performance. Technological Innovation Activities have a Positive Impact on Competitive Advantage, and do not have enough Impact on the Development Performance. Technical Cooperation Activities have a Positive Impact on the Development Performance, and do not have enough Impact on the Competitive Advantage, Competitive Advantage has a Positive Impact on the Development Performance as well as the Business Performance. Development Performance has a Positive Impact on the Business Performance.

The traditional AHP(Analytic Hierarchy Process) is to evaluate subjectively the alternatives in the view point of each of criteria and has been widely used at the fields of real world application. The AHP has some drawbacks that makes it difficult to keep the consistency of decision makers' input and take too long to get accurate results because of requiring lots of pairwise comparison between criteria and alternatives. This research is to propose and develop a Hybrid-AHP system for complementing the critical points of traditional AHP methodologies. This system gets the quantitative information as well as qualitative inputs as the comparative ones between criteria and alternatives. We use the input as various type of information such as quantitative values, 9-scale ratings, and fuzzy-based inputs. Finally, we applied the system to the case of choosing strategic industries. The case study have shown the use of various input methods saves processing time, and reduces the input burden of users.

The multi-reservoir operation problem for efficient utilization of water resources involves conflicting objectives, and the problem can be solved by varying weight coefficient on objective functions. Accordingly, decision makers need to choose appropriate weight coefficients balancing the trade-offs among multiple objectives. Although the appropriateness of the weight coefficients may depend on the total amount of water inflow, reservoir operating policy may not be changed to a certain degree for different hydrological conditions on inflow. Therefore, we propose to use fuzzy Data Envelopment Analysis (DEA) to rank the weight coefficients in consideration of the inflow variation. In this approach, we generate a set of Paretooptimal solutions by applying different weight coefficients on Coordinated Multi-reservoir Operating Model. Then, we rank the Pareto-optimal solutions or the corresponding weight coefficients by using Fuzzy DEA model. With the proposed approach, we can suggest the best weight coefficients that can produce the appropriate Pareto-optimal solution considering the uncertainty of inflow, whereas the general DEA model cannot pinpoint the best weight coefficients.

Manufacturing enterprises have been doing their best endeavors to obtain competitiveness using various methodologies, such as information technology. In order to achieve competitiveness, they are adopting manufacturing execution system (MES). MES is a total management system that manages from the beginning of the production by product order until the quality inspection of the finished product. And MES is an inter-mediator for supplementation of information gap between ERP and inspection machine and equipment. This paper describes on establishment of effective strategy based on BPR methodology and implementation of MES small and medium PCB manufacturing company with multiple-types of products and mixed process flows. And then we proposed evaluation model based on balanced score card (BSC) for considering non-finance elements as well as finance elements. With evaluation model, we analyzed benefits and effects of MES.

This paper develops a mathematical model which searches an optimum lot size of a press line, and applies this model to the scheduling of the press line. This mathematical model is not a widely studied cost model but a model which considers the utilization of the press line under a lean production system. In this paper, the optimum lot size is a minimum lot size which does not exceed the total work time of the press line. A production volume and the priority of the production in the press line are adjusted using this optimum lot size. A mathematical model developed in this paper will allow determining the optimum lot size easily in case of variable production environments such as an introduction of a new product and a fluctuation of production volume of each item. Therefore, our model will make a better scheduling of the press line and will enhance the utilization of it.

The amount of Meta-data to be managed increases with development of information technology. However, when trying to integrate and share product information of heterogeneous systems within or between companies, sharing of information is impossible if product information classification systems are different. Due to the situation mentioned above, engineers judge the product information classification system and maps corresponding Meta-data for document-based sharing. Judging exponentially increasing amount of data by engineers and sharing product information using documents create great amount of time delay and errors in data handling. Therefore, construction of a system for integrated management and interoperability between product information based on semantic information similar to engineer's judgment is required. This paper proposes a methodology and necessity of a system for interoperability of product information based on semantic web, and also designs a system to integrate heterogeneous systems with different product information using rule based reasoning. This paper also suggests a system base for interoperability and integration of product information between heterogeneous systems by integrating the product information classification system semantically.

In this paper, we deal with a problem improving the productivity of a discrete production line for filling a printer cartridge with toner. We develop a new technology for controlling the weight of toner which must be filled in a cartridge and reform the current line based on our new control technology to result in more than 35% improvement of productivity as well as the control accuracy. In detail, first, we find a bottleneck process, the toner-filling process which gives the current production cycle times. Second, we divide the processing time of the bottleneck into several work elements and find the rotation time of an AC servomotor to be further reduced. Third, in order to reduce the rotation time, we develop a mathematical control-time model for determining the rotation time. Finally, we reform the current line partially as required by the change of the new control method.

In the shipbuilding industry, since production processes are so complicated that the data collection for decision making cannot be fully automated, most of production planning and controls are based on the information provided only by field workers. Therefore, without sufficient information it is very difficult to manage the whole production process efficiently. Job status is one of the most important information used for evaluating the remaining processing time in production control, specifically, in block assembly shop. Currently, it is checked by a production manager manually and production planning is modified based on that information, which might cause a delay in production control, resulting in performance degradation. Motivated by these remarks, in this paper we propose an efficient algorithm for identifying job status in block assembly shop for shipbuilding. The algorithm is based on the multi-layer perceptron neural network model using two key factors for input parameters. We showed the superiority of the algorithm by using a numerical experiment, based on real data collected from block assembly shop.