• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.199-208
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• 2014

Purpose: This paper explains how to obtain the Bayes estimates of the whole launch vehicle and of a vehicle stage, respectively, for a newly developed expendable launch vehicle. Methods: We determine the parameters of the beta prior distribution using the upper bound of the 60% Clopper-Pearson confidence interval of failure probability which is calculated from previous launch data considering the experience of the developer. Results: Probability that a launch vehicle developed from an inexperienced developer succeeds in the first launch is obtained by about one third, which is much smaller than that estimated from the previous research. Conclusion: The proposed approach provides a more conservative estimate than the previous noninformative prior, which is more reasonable especially for the initial reliability of a new vehicle which is developed by an inexperienced developer.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.365-379
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• 1997

Currently the problem of air pollution caused by the motor vehicle emission is of the most serious problems to be solved. Life Cycle Assessment is a process to evaluate the environmental burdens associated with a product or process by identifying and quantifying energy and materials used and wasters to the environment. This paper establishes a Life Cycle Assessment Systems which satisfies the criteria motor vehicle emission for the automobile producers who are currently producing the automobiles with catalytic convert. This plan also considered the constraint of the effective motor vehicle emission by way of the exhaust gas recirculation, electronic fuel injection, closed loop carburetor. In order to develope the performance of the LCA systems, the recent emissions test data have also been applied. The result of the development LCA systems has proved that the LCA plans presented in this paper satisfies the criteria motor vehicle emission and will be contributed to constrain the motor vehicle emission most effectively.

• International Journal of Automotive Technology
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• v.6 no.5
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• pp.491-499
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• 2005

There are different types of vehicle impacts recorded every year, resulting in many injuries and fatalities. The severity of these impacts depends on the aggressivety and incompatibility of vehicle-to-roadside hardware impacts. The aim of this paper is to investigate and to enhance crashworthiness in the case of full barrier impact using a new idea of crash improvement. Two different types of smart structures have been proposed to support the function of the existing vehicle. The work carried out in this paper includes developing and analyzing mathematical models of vehicle-to-barrier impact for the two types of smart structures. It is proven from analytical analysis that the mathematical models can be used in an effective way to give a quick insight of real life crashes. Moreover, it is shown that these models are valid and flexible, and can be useful in optimization studies.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.119-131
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• 1988

Vehicle Scheduling Problem (VSP) is a generic name given to a whole class of problems involving the visiting of "stations" by "vehicles," where a time is associated with each activity. The studies performed to date have the common feature of a single objective while satisfying a set of restrictions and known customer supplies or demands. However, VSPs may involve relevant multiple objectives and probabilistic supplies or demands at stations, creating multicriteria stochastic VSPs. This paper proposes a heuristic algorithm based on goal programming approach to schedule the most satisfactory vehicle routes of a bicriteria VSP with probabilistic supplies at stations. The two relevant objectives are the minimization of the expected travel distance of vehicles and the minimization of the due time violation for collection service at stations by vehicles. The algorithm developed consists of three major stages. In the first stage, an artificial capacity of vehicle is determined, on the basis of decision maker's subjective estimates. The second one clusters a set of stations into subsets by applying an efficient cluster method developed. In the third one, the stations in each subset are scheduled by applying an iterative goal programming heuristic procedure to each cluster.

• Management Science and Financial Engineering
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• v.3 no.1
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• pp.1-14
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• 1997

We address the problem of determining the sequence of a vehicle with fixed capacity to visit n nodes at which a predetermined amount is picked up and/or delivered. The objective is to minimize the total travel distance of the vehicle, while satisfying the pick-up/delivery requirements and feasibility at all nodes. Existing methods for the problem allows the vehicle to visit a node twice, which is impractical in many real situations. We propose a heuristic algorithm, in which every node is visited exactly once. Computational results using random problems indicate that the proposed heuristic outperforms existing methods for practical range of the number of nodes in reasonable computation time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.1-10
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• 2011

This paper addresses the analysis of the travel distance and order picking time of the vehicle in a aisle when items are picked by the batch in a warehouse system. Batching is to combine several orders in a single tour of the storage/retrieval machine. An advantage of batching is that the length of a tour for a batch of orders is shorter than the sum of the individual orders' tour lengths. The average travel distance and order picking time when a batch is picked in a aisle of the warehouse systems are analyzed for the batch size. And when the vehicle is idle, the dwell point of the vehicle to minimize to the response distance is analyzed. As the batch size is increased, average order picking time per item is decreased. The problem is analyzed and a numerical example is showed to explain the problem.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.295-301
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• 2005

It is not easy to apply fault-tolerant techniques which are used in conventional computer systems successfully to the field of embedded computing system directly. In this paper, we study on the way of minimizing hardware and/or software backups for vehicle embedded computing systems. First, we group parts that constitute vehicle embedded systems and next feature subset is determined using the grouping information derived. The possibility of implementing graceful degradation capability in vehicle embedded systems is verified.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.39-49
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• 2006

Forklift achieves transportation of freight and continues loading and unloading work repeatedly long for hours in industry spot. Therefore, drivers feel tired make a mistake for wrong operation of vehicle caused by continuous work. These components are resulted in CTDs, some industrial accident. That is the forklift need to ergonomics access. So, in this paper, requirements of forklift user were abstracted using questionnaire, produced important design factor for pedal and lever using QFD(Quality Function Deployment), and then suggested ergonomic considerations for industrial accident prevention.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1434-1439
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• 2012

Vehicle is a dynamic system combined with various parameters. Dynamic characteristics of a vehicle can vary with the change of these parameters. To investigate the effect of the design parameter on vehicle handling performance the sensitivity analysis is carried out by the numerical method. The vehicle model is described by equivalent cornering stiffness that considers parameters of suspension and steering system. As the analysis results show the effect on the static and dynamic characteristics of the vehicle system, the sensitivity analysis can be used for synthesis of the design parameters to improve the vehicle handling characteristics at the design stage as well as during the vehicle test under development.

• Journal of the Korea Safety Management & Science
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• v.15 no.2
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• pp.193-204
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• 2013

The growing logistics strategy of a company is to optimize their vehicle route scheduling in their supply chain system. It is very important to analyze for continuous pickups and delivery vehicle scheduling. This paper is a computational study to investigate the effectiveness of continuous pickups and delivery vehicle routing problems. These scheduling problems have 3 subproblems; Inbound Vehicle Routing Problem with Makespan and Pickup, Line-haul Network Problem, and Outbound Vehicle Routing Problem with Delivery. In this paper, we propose 5 heuristic Algorithms; Selecting Routing Node, Routing Scheduling, Determining Vehicle Type with Number and Quantity, and Modification Selecting Routing Node. We apply these Algorithms to S vehicle company. The results of computational experiments demonstrate that proposed methods perform well and have better solutions than other methods considering the basic time and due-date.