光纤陀螺温度场分析及结构优化设计

从导热微分方程出发,建立了光纤陀螺温度场有限元模型,对模型进行了稳态温度场和瞬态温度场仿真分析。利用铂电阻测温电路对仿真结果进行实验验证,两者相对误差小于3%,证明仿真分析的结果是正确和有效的。针对光纤环温度场分布不均匀的情况,对光纤陀螺结构进行了优化设计。光纤陀螺在25℃环境中稳定工作时,稳态温度场分析结果表明,优化设计后光纤环最高与最低温度差为0.05℃,较优化前的0.19℃减小了73.7%;将陀螺置于60℃环境且处于非开机状态时,10min瞬态温度场分析结果表明,优化设计后光纤环最高与最低温度相差0.11℃,较优化前的0.19℃减小了42.1%。     

Development programs for one‐shot systems using multiple‐state design reliability models

Design reliability at the beginning of a product development program is typically low, and development costs can account for a large proportion of total product cost. We consider how to conduct development programs (series of tests and redesigns) for one‐shot systems (which are destroyed at first use or during testing). In rough terms, our aim is to both achieve high final design reliability and spend as little of a fixed budget as possible on development. We employ multiple‐state reliability models. Dynamic programming is used to identify a best test‐and‐redesign strategy and is shown to be presently computationally feasible for at least 5‐state models. Our analysis is flexible enough to allow for the accelerated stress testing needed in the case of ultra‐high reliability requirements, where testing otherwise provides little information on design reliability change. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Optimal redesign decisions through failure rate estimates

To reduce the time-to-market of newly developed systems, manufacturers increasingly adopt strategies where systems are brought to market while system field reliability is still uncertain. These systems are typically sold under performance-based contracts, which incentivizes potential customers to invest in them despite reliability uncertainty. Such contracts make the manufacturer (partly) responsible for the availability of the system. Subsequently, when field reliability is lower than anticipated, the manufacturer may choose to redesign the system to avoid high contract penalties. Redesign is a costly effort which may substantially increase field reliability. Deciding when to redesign is challenging, especially because the initial failure rate estimate by the system's engineers is refined over time as failure data accrues. We propose a model that endogenizes the failure rate updating to analyze this tactical redesign decision. We study additive and multiplicative redesigns and show that the optimal policy has a control limit structure. We benchmark our optimal policy against a static counterpart numerically, and conclude that basing redesign decisions on the updated estimate of the failure rate can substantially reduce costs.