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首页> 外文会议>Reliability and Maintainability Symposium (RAMS), 2012 Proceedings - Annual >The throughput, reliability, availability, maintainability (TRAM) methodology for predicting chemical plant production
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The throughput, reliability, availability, maintainability (TRAM) methodology for predicting chemical plant production

机译：用于预测化工厂产量的吞吐量，可靠性，可用性，可维护性（TRAM）方法

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Fault tree analysis is a method for evaluating reliability and availability in terms of equipment system “states”, but this method does not lend itself easily to the evaluation of equipment interactions through time. This makes fault trees difficult to use for the analysis of systems whose reliability and availability depend on complex interactions between its subsystems. This difficulty is overcome by combining fault trees with discrete event simulation methods. The new TRAM methodology combines models and techniques for the analysis of throughput, availability, reliability, and maintainability into a single approach. This paper describes the TRAM methodology and illustrates it with an application to a chemical processing plant. TRAM combines fault tree analysis at a low level of the system description and discrete event simulation at a higher level to create a new method for analyzing the availability and throughput capacity of material processing plants. Failure and repair data is modeled stochastically by a very flexible type of finite mixture distribution that allows the analyst to separate the effects of different repair strategies, such as the reliance on procurement of off-site (vs. on-site) spare parts. An important application of the TRAM method is to facilitate the design of a plant that tolerates outages of its subsystems in the most efficient way possible. Mitigation strategies including in-process storage, alternate work-flows, availability of spare parts, and design for over-production: all of these can be assessed using the TRAM approach, and it thereby facilitates the design of more robust manufacturing systems. The TRAM methodology enables sophisticated “what-if” analyses of alternative designs, e.g. equipment sets, capacities (tanks sizes), shift schedules, spare parts, etc. to optimize plant design and operation. It is a stochastic, time dependent process that provides probabilities of success (or failure) and con- idence bounds on availability and throughput. Finally, the TRAM methodology can help plant managers and owners to focus on the plant production metrics by which they are compensated, and not solely on abstract metrics such as availability. Accordingly, TRAM is potentially a more influential tool in the industry than conventional RAM methods. The TRAM method is based on the discrete event formalism developed by Zeigler et al. [1], and explained further in [2]. In TRAM the plant model is completely separated from the simulation engine and can be specified by input data contained in an XML file. Alternatively, the user can construct connections between subsystem components using a graphical user interface. The GUI is very useful in supporting the verification of the correct mass balance in the model.
机译：故障树分析是一种根据设备系统“状态”评估可靠性和可用性的方法，但是这种方法不易用于评估随时间变化的设备交互作用。这使得故障树难以用于分析其可靠性和可用性取决于其子系统之间复杂交互的系统。通过结合故障树和离散事件模拟方法可以克服此困难。新的TRAM方法将用于分析吞吐量，可用性，可靠性和可维护性的模型和技术组合在一起。本文介绍了TRAM方法，并将其应用于化工厂进行说明。 TRAM结合了系统描述底层的故障树分析和更高层次的离散事件模拟，从而创建了一种新的方法来分析材料加工厂的可用性和生产能力。故障和维修数据是通过非常灵活的有限混合物分布模型随机建模的，该类型的有限混合分布使分析人员可以区分不同维修策略的影响，例如依赖于现场（相对于现场）备件的采购。 TRAM方法的一个重要应用是简化工厂的设计，以最有效的方式容忍其子系统的故障。缓解策略包括流程中存储，替代工作流程，备件可用性和过度生产设计：所有这些都可以使用TRAM方法进行评估，从而有助于设计更可靠的制造系统。 TRAM方法可以对替代设计进行复杂的“假设分析”，例如设备集，能力（油箱尺寸），班次时间表，备件等，以优化工厂的设计和运营。它是一个随机的，与时间有关的过程，提供成功（或失败）的概率以及可用性和吞吐量的置信度。最后，TRAM方法可以帮助工厂经理和所有者专注于补偿他们的工厂生产指标，而不仅仅是关注诸如可用性等抽象指标。因此，与传统的RAM方法相比，TRAM在行业中可能是更具影响力的工具。 TRAM方法基于Zeigler等人开发的离散事件形式。 [1]，并在[2]中进一步说明。在TRAM中，工厂模型与仿真引擎完全分离，可以通过XML文件中包含的输入数据来指定。或者，用户可以使用图形用户界面在子系统组件之间构建连接。 GUI在支持验证模型中正确的质量平衡方面非常有用。

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