An Optimal Inspection and Replacement Policy

An optimal inspection and replacement policy is discussed for a unit which assumes any one of several Markov states. The policy evaluation function is the s-expected cost-per-unit-time over an infinite time span. The problem is formulated as a semi-Markov decision process with a modified policy-improvement routine. Some properties of the optimal policy are discussed, for example, the control limit rule holds and the inspection time interval becomes shorter as degradation progresses.     

A Multistage Interleaved Synchronous Buck Converter With Integrated Output Filter in 0.18 μm SiGe Process

The design and analysis of a fully integrated multistage interleaved synchronous buck dc-dc converter with on-chip filter inductor and capacitor is presented. The dc-dc converter is designed and fabricated in 0.18 mum SiGe RF BiCMOS process technology and generates 1.5 V-2.0 V programmable output voltage supporting a maximum output current of 200 mA. High switching frequency of 45 MHz, multiphase interleaved operation, and fast hysteretic controller reduce the filter inductor and capacitor sizes by two orders of magnitude compared to state-of-the-art converters and enable a fully integrated converter. The fully integrated interleaved converter does not require off-chip decoupling and filtering and enables direct battery connection for integrated applications. This design is the first reported fully integrated multistage interleaved, zero voltage switching synchronous buck converter with monolithic output filters. The fully integrated buck regulator achieves 64% efficiency while providing an output current of 200 mA.     

一种具有弹性服务质量要求的多业务最优接纳控制策略

随着无线网络所支持的业务种类的增加和具有弹性服务质量要求的业务的大量出现，与服务质量保证密切相关的呼叫接纳控制问题成了近年来无线网络研究的热点之一。本文研究了基于准马尔可夫决策过程方法的多业务最优呼叫接纳控制问题。根据业务的特点，首先引入了带宽分配满意度函数和收益率函数，在此基础上，提出了基于带宽分配满意度的最优带宽分配算法和基于准马尔可夫决策过程方法的最优呼叫接纳控制策略。计算结果表明，本文方案能够在对各类业务的呼叫阻塞率进行适当权衡的前提下，进一步提高网络的期望收益率和期望带宽利用率，同时满足了各类业务的最低服务质量要求。     

Cross Training in Serial Production With Process Characteristics and Operational Factors

Worker multifunctionality has been recognized as a tool for enhancing system flexibility and performance. This paper investigates the impacts of worker multifunctionality in a heterogeneous serial production system in the presence of individual differences in experiential learning and forgetting. The tradeoffs of multifunctionality and cross training are examined in conjunction with several process characteristics and operational decisions including staffing level, system bottleneck position, task similarity degree, and worker rotation interval. The results show the relationships between the preferred level of worker multifunctionality and both process characteristics and operational decisions. In several cases, minimum multifunctionality and short worker rotation intervals provide improved system performance. Additionally, process characteristics, such as the position of the system bottleneck and the degree of task similarity, have impacts on individual learning--forgetting behaviors and, subsequently, on decisions relating to multifunctionality levels and system performance.     

A Computational Model for Determining the Optimal Preventive Maintenance Policy With Random Breakdowns and Imperfect Repairs

We consider a system that is subject to random failures, and investigate the decision rule for performing renewal maintenance or preventive replacement (PR). This type of maintenance policy involves two decision variables. The first decision variable is the time between preventive replacements, or a fixed cycle time. To avoid unnecessary renewals or replacements at the end of a cycle, a cut-off age is introduced as the second decision variable. At the end of every cycle, if the system's virtual age is equal to or greater than the cut-off age, it will undergo a renewal or replacement; otherwise the renewal decision will be postponed until the end of the next cycle. Random failures can occur, however; and the system receives emergency imperfect repairs (ER) at these times. Hence, within a PR cycle, a second decision time is identified. If an ER occurs between the start of a cycle and this second decision time, then the planned PR would still be performed at the end of the cycle. However, if the first ER occurs after this second decision time, then the PR at the end of the cycle is skipped over, and the next planned PR would take place at the end of the subsequent cycle. With this simple mechanism, PR which follow on too closely after an ER are avoided, thus saving the unnecessary expense. We develop a computational model to determine the optimal maintenance policy with these two decision variables