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An economic analysis of false alarms and no fault found events in air vehicles

机译:飞机误报和未发现故障事件的经济分析

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False Alarms (FAs) that occur in a fielded system and No Fault Found (NFF) events that are discovered after line replaceable units (LRUs) have been returned to repair are costly situations whose full impact is difficult to put into monetary terms. For that reason, pragmatic economic models of NFFs are difficult to develop. In this paper, we deal with the problem of having to differentiate between NFFs of good units under test (UUTs) and of faulty UUTs. While we cannot tell which UUT is good and which is faulty, we can determine using probabilities what percentage of the NFFs are faulty and what percentage are good. Based on these probabilities, we can evaluate various strategies. Assigning cost factors that are knowable, such as the cost of testing a UUT, the cost we incur for good UUTs vs. costs we incur for faulty UUTs and various test and repair costs, we can calculate the performance of various strategies and assumptions. In this paper, we formulate three strategies: 1) We assume all NFF UUTs are good and are willing to endure the cost of bad actors (i.e. faulty UUTs) sent back to the aircraft. 2) We assume all NFF UUTs are faulty and we environmentally stress all NFF UUTs, hoping to fix some and avoid bad actors. 3) We rely on the technician to reasonably select some NFF UUTs and perform appropriate repair. We formulate each of these strategies for a case when NFF is 70%. The formulation is similar with any NFF distribution, but the coefficients in each formula will be different. With proper cost data, we can actually decide which strategy works best. We conclude by tabulating the formulas and calculate NFF costs for an example situation. The numbers we picked for this example may be appropriate for some operations, but not for others. As a follow-up to this paper we would like to validate the model with real data, which may be available in some military and commercial avionics maintenance departments.
机译:现场系统中发生的虚假警报(FA)以及将线路可更换单元(LRU)返还维修后发现的未发现故障(NFF)事件是昂贵的情况,很难将其全部影响用金钱计算。因此,难以发展出实用的非农金融模型。在本文中,我们处理的问题是必须区分好被测单元(UUT)和有故障的UUT的NFF。虽然我们无法确定哪个UUT良好以及哪个UTF有故障,但是我们可以使用概率确定NFF的故障百分比和良好的百分比。基于这些概率,我们可以评估各种策略。分配已知的成本因素,例如测试UUT的成本,我们为良好的UUT招致的成本与我们为故障的UUT招致的成本以及各种测试和维修成本,我们可以计算各种策略和假设的性能。在本文中,我们制定了三种策略:1)我们假设所有NFF UUT都是好的,并且愿意忍受送回飞机的不良行为者(即故障UUT)的成本。 2)我们假设所有NFF UUT均存在故障,并且我们在环境方面对所有NFF UUT施加压力,希望对其进行修复并避免不良行为。 3)我们依靠技术人员合理地选择一些NFF UUT并进行适当的维修。我们针对NFF为70%的情况制定每种策略。任何NFF分布的公式都相似,但是每个公式中的系数都不同。有了适当的成本数据,我们实际上可以决定哪种策略最有效。我们通过对公式列表进行总结并计算示例情况的NFF成本。我们为该示例选择的数字可能适用于某些操作,但不适用于其他操作。作为本文的后续,我们想用真实数据验证模型,该数据可能在某些军事和商业航空电子维修部门中可用。

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