The impact of component commonality on composite assembly policies

Assemble in Advance (AIA) policy reduces assembly cost due to advance planning, while Assemble to Order (ATO) policy eliminates assembly of excessive (more than demanded) units. The tradeoffs between the two policies have been studied in the past for single product environments. Moreover, it was shown that it is beneficial to employ AIA and ATO simultaneously. In this article, we study the employment of such a composite assembly policy in a multiproduct environment with component commonality. When common components are used, ATO may also enable us to benefit from the risk pooling effect. We provide important managerial insights such as: the multiperiod problem is myopic and changes in inventory levels due to the use of common components, and demonstrate the potential profit increase compared to other policies.© 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

BTT 导弹自动驾驶仪的多变量频域法解耦设计

研究了一种耦合严重的ＢＴＴ 导弹偏航－滚动通道非方阵模型的自动驾驶仪的设计问题。首先采用内闭环回路法对模型进行了方阵化, 然后采用基于奈奎斯特阵列法思想的多变量频域法进行了设计。仿真表明了自动驾驶仪设计的解耦效果明显     

采用固液冲压发动机的地空导弹弹道建模

针对采用固液混合冲压发动机的地空导弹弹道设计中出现的新问题, 给出了解决这些问题的弹道设计方法, 并利用弹道仿真对其进行了验证。     

特大规模组合电路高速测试生成系统ATGTA-1

针对特大规模组合电路和全扫描设计电路提出了一种高速测试生成方法，并建成了相应的测试生成系统ＡＴＧＴＡ－１。该系统采用有限回溯测试模式产生方法生成测试码，采用ｎ（机器字长）个测试码并行的单故障传播方法模拟验证测试覆盖。测试生成与故障模拟为ｎ对１紧耦合集成方式。该系统运行１０个Ｂｅｎｃｈｍａｒｋ电路，取得了低测试长度、高故障覆盖、高效率的良好效果。     

用神经网络建立反后坐装置参数对其性能的影响模型

详细分析火炮反后坐装置影响因素基础上,用人工神经网络建立了完整的反后坐装置参数对其性能的影响模型,运用算例证明了神经网络在反后坐装置中应用的可行性。所提出的提灌法使网络的学习更加灵活,收敛更快。     

浅析炮车比

本文以坦克发射时车体的角振幅和乘员所受加速度不超过一定值为基础,推导了炮车比极限值的理论公式;并对影响炮车比极值的因素进行了分析,最后,以59式坦克为例得出炮车比不超过1.71,该结论具有普遍意义.     

关于潜艇装备劳兰C导航仪技术问题的研究

本文提出了一种改善潜艇现有天线接收性能的方法,从而解决了在潜艇上安装使用劳兰C导航仪的关键技术问题。     

Dynamic coordination of production planning and sales admission control in the presence of a spot market

We consider the decision‐making problem of dynamically scheduling the production of a single make‐to stock (MTS) product in connection with the product's concurrent sales in a spot market and a long‐term supply channel. The spot market is run by a business to business (B2B) online exchange, whereas the long‐term channel is established by a structured contract. The product's price in the spot market is exogenous, evolves as a continuous time Markov chain, and affects demand, which arrives sequentially as a Markov‐modulated Poisson process (MMPP). The manufacturer is obliged to fulfill demand in the long‐term channel, but is able to rein in sales in the spot market. This is a significant strategic decision for a manufacturer in entering a favorable contract. The profitability of the contract must be evaluated by optimal performance. The current problem, therefore, arises as a prerequisite to exploring contracting strategies. We reveal that the optimal strategy of coordinating production and sales is structured by the spot price dependent on the base stock and sell‐down thresholds. Moreover, we can exploit the structural properties of the optimal strategy to conceive an efficient algorithm. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

车载式回转起竖平台起竖执行机构选型分析

给出了车载式回转起竖平台起竖执行机构可供选用的机构方案;重点讨论了包含一个可变长度构件且为滚珠丝杆的四连杆机构——摇块机构和转动导杆机构两方案的结构参数计算方法和受力分析方法;通过对比分析,在满足功能要求的前提下,确定了相对较优的摇块机构方案并付之实践,效果理想。     

Optimal control of a production‐inventory system with both backorders and lost sales

We consider the optimal control of a production inventory‐system with a single product and two customer classes where items are produced one unit at a time. Upon arrival, customer orders can be fulfilled from existing inventory, if there is any, backordered, or rejected. The two classes are differentiated by their backorder and lost sales costs. At each decision epoch, we must determine whether or not to produce an item and if so, whether to use this item to increase inventory or to reduce backlog. At each decision epoch, we must also determine whether or not to satisfy demand from a particular class (should one arise), backorder it, or reject it. In doing so, we must balance inventory holding costs against the costs of backordering and lost sales. We formulate the problem as a Markov decision process and use it to characterize the structure of the optimal policy. We show that the optimal policy can be described by three state‐dependent thresholds: a production base‐stock level and two order‐admission levels, one for each class. The production base‐stock level determines when production takes place and how to allocate items that are produced. This base‐stock level also determines when orders from the class with the lower shortage costs (Class 2) are backordered and not fulfilled from inventory. The order‐admission levels determine when orders should be rejected. We show that the threshold levels are monotonic (either nonincreasing or nondecreasing) in the backorder level of Class 2. We also characterize analytically the sensitivity of these thresholds to the various cost parameters. Using numerical results, we compare the performance of the optimal policy against several heuristics and show that those that do not allow for the possibility of both backordering and rejecting orders can perform poorly.© 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010