To meet rapidly changing market demands, manufacturers strive to increase both of productivity and diversity at the same time. As a part of those effort, they are applying flexible manufacturing systems that produce multiple types and/or options of products at a single production line. This paper studies such flexible manufacturing system with multiple types of products, multiple Bernoulli reliability machines and dedicated buffers between them for each of product types. As one of the prevalent control policies, priority based policy is applied at each machines to select the product to be processed. To analyze such system and its performance measures exactly, Markov chain models are applied. Because it is too complex to define all relative transient and its probabilities for each state, an algorithm to update transient state probability are introduced. Based on the steady state probability, some performance measures such as production rate, WIP-based measures, blocking probability and starvation probability are derived. Some system properties are also addressed. There is a property of non-conservation of flow, which means the product ratio at the input flow is not conserved at the succeeding flows. In addition, it is also found that increased buffer capacity does not guarantee improved production rate in this system.

In this paper, we present a new way to derive the mean cycle time of the G/G/m failure prone queue when the loading of the system approaches to zero. The loading is the relative ratio of the arrival rate to the service rate multiplied by the number of servers. The system with low loading means the busy fraction of the system is low. The queueing system with low loading can be found in the semiconductor manufacturing process. Cluster tools in semiconductor manufacturing need a setup whenever the types of two successive lots are different. To setup a cluster tool, all wafers of preceding lot should be removed. Then, the waiting time of the next lot is zero excluding the setup time. This kind of situation can be regarded as the system with low loading. By employing absorbing Markov chain model and renewal theory, we propose a new way to derive the exact mean cycle time. In addition, using the proposed method, we present the cycle times of other types of queueing systems. For a queueing model with phase type service time distribution, we can obtain a two dimensional Markov chain model, which leads us to calculate the exact cycle time. The results also can be applied to a queueing model with batch arrivals. Our results can be employed to test the accuracy of existing or newly developed approximation methods. Furthermore, we provide intuitive interpretations to the results regarding the expected waiting time. The intuitive interpretations can be used to understand logically the characteristics of systems with low loading.

Quinclorac, bentazone, 2,4-D, bensulfuron-methyl, dymuron, capropamide, pencycuron 및 ethofenprox를 동시에 분석할 수 있는 전처리 방법과 0.1% 인산 및 아세토니트릴을 이동상으로하고 225 nm를 측정파장으로 사용한 RP-HPLC(reverse phase-high performance liquid chromatography)법을 개발하였다. 동 농약성분들의 검출 및 정량한계는 각각 0.12〜0.84 ppm 및 0.34〜1.20 ppm이었고, 회수율은 78〜96%이었다. 본 방법을 통하여 시료 전처리에서 분석까지 기존 13시간이 소요된 총 분석시간을 3시간 이내로 줄일 수 있었다.