对提高大学作战指挥专业硕士研究生培养质量的几点思考

武警工程大学自1998年成为作战指挥学硕士学位授予点后,经过十几年的不懈努力和逐步发展,研究生培养质量不断提高。但在发展的同时也存在一些问题,这些问题如不能很好地解决,将制约作战指挥专业硕士研究生培养的质量。就影响和制约作战指挥专业硕士研究生培养质量的因素为切入点,对当前乃至以后提高大学作战指挥专业硕士研究生培养质量提出了几点建议。     

当代教师的基本素养

随着社会对人才培养质量要求的提高,对教师的素质有了更高的要求,要求当代教师具备教学反思的能力、终身学习的理念、执着的教育追求、高度的责任感、仁爱之心、宽容的情怀等基本素养。     

车辆装备保障分队单兵训练质量组合评价分析

针对当前部队车辆装备保障分队单兵训练质量评价中所存在的问题和不足,综合运用集对分析一四元联系数理论、马尔可夫链模型和熵权双基点法,尝试提出一种新的评价分析方法——SHE组合评价分析法,排除单兵原有基础差异对年度训练考核成绩的影响,考虑评价对象之间的情感因素和分队训练条件对单兵训练质量的影响,从而使评价显得更加客观、公正和公平．最后,结合算例,分析说明了此方法的具体应用．     

Scheduling recurrent construction

A problem we call recurrent construction involves manufacturing large, complex, expensive products such as airplanes, houses, and ships. Customers order configurations of these products well in advance of due dates for delivery. Early delivery may not be permitted. How should the manufacturer determine when to purchase and release materials before fabrication, assembly, and delivery? Major material expenses, significant penalties for deliveries beyond due dates, and long product makespans in recurrent construction motivate choosing a release timetable that maximizes the net present value of cash flows. Our heuristic first projects an initial schedule that dispatches worker teams to tasks for the backlogged products, and then solves a series of maximal closure problems to find material release times that maximize NPV. This method compares favorably with other well‐known work release heuristics in solution quality for large problems over a wide range of operating conditions, including order strength, cost structure, utilization level, batch policy, and uncertainty level. Computation times exhibit near linear growth in problem size. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

【专题】人工智能装备质量监督效能研究

近年来,人工智能技术迅速发展和渐趋成熟,在装备领域的应用大放异彩,极大地拓展了传统装备性能,特别是自主性和智能化水平。但人工智能算法本身固有的逻辑推理性差、具有不可解释性和需要学习训练等特性给人工智能装备的质量监督带来了新挑战,现有评价手段的欠缺也使人工智能装备发展在实用可靠方面充满不确定性。本文在总结归纳人工智能装备新特性拓展和质量监督新挑战的基础上,重点围绕有效提升人工智能装备的质量监督展开研究。提出应在夯实基础能力设施建设、注重日常数据采集整理、灵活技术状态管控、研究有效评价手段、强化人才队伍建设和闭环质量信息反馈与利用等六方面加强人工智能装备质量监督的措施建议,以期为人工智能装备的发展建设提供参考。     

信息管理系统开发中的进度控制

分析了信息系统开发项目的特点,开发过程中进度控制的一般工作流程及进度控制中经常遇到的问题与难点,针对某质量信息管理与辅助决策系统中进度控制实际流程,给出了常见问题与困难的解决方案。同时指出:应用挣值分析法评估项目进度时应对信息系统的重点、难点模块进行特殊监控。     

Allocation of quality improvement targets based on investments in learning

Purchased materials often account for more than 50% of a manufacturer's product nonconformance cost. A common strategy for reducing such costs is to allocate periodic quality improvement targets to suppliers of such materials. Improvement target allocations are often accomplished via ad hoc methods such as prescribing a fixed, across‐the‐board percentage improvement for all suppliers, which, however, may not be the most effective or efficient approach for allocating improvement targets. We propose a formal modeling and optimization approach for assessing quality improvement targets for suppliers, based on process variance reduction. In our models, a manufacturer has multiple product performance measures that are linear functions of a common set of design variables (factors), each of which is an output from an independent supplier's process. We assume that a manufacturer's quality improvement is a result of reductions in supplier process variances, obtained through learning and experience, which require appropriate investments by both the manufacturer and suppliers. Three learning investment (cost) models for achieving a given learning rate are used to determine the allocations that minimize expected costs for both the supplier and manufacturer and to assess the sensitivity of investment in learning on the allocation of quality improvement targets. Solutions for determining optimal learning rates, and concomitant quality improvement targets are derived for each learning investment function. We also account for the risk that a supplier may not achieve a targeted learning rate for quality improvements. An extensive computational study is conducted to investigate the differences between optimal variance allocations and a fixed percentage allocation. These differences are examined with respect to (i) variance improvement targets and (ii) total expected cost. For certain types of learning investment models, the results suggest that orders of magnitude differences in variance allocations and expected total costs occur between optimal allocations and those arrived at via the commonly used rule of fixed percentage allocations. However, for learning investments characterized by a quadratic function, there is surprisingly close agreement with an “across‐the‐board” allocation of 20% quality improvement targets. © John Wiley & Sons, Inc. Naval Research Logistics 48: 684–709, 2001     

影响武器装备维修质量的基本要素分析

制约、影响维修质量的因素是多方面的.从武器装备系统的全寿命过程出发,将影响维修质量的基本要素概括为7个方面即维修人员素质、维修设备与设施的状况、装配工艺、维修生产环境、原材料、备品备件的质量、维修管理制度等.通过具体研究、分析影响维修质量的这些因素及其特征量,指明这是实现维修质量管理和评定目标的必经之路,只有影响因素明确了,才能有的放矢地对维修质量进行管理、控制与评定.     

关于装备使用阶段质量问题的探讨

在装备使用阶段部队活动的目的是为了充分发挥、保持、恢复和改善装备的综合保障性能,减少保障人力和费用、缩短保障时间,以满足作战和任务的要求.这些性能、费用和时间的要求正是装备质量的特性.质量要求在论证阶段提出,质量特性在设计和生产制造过程中形成,在使用过程中得到表现.装备质量的表现是使用方对装备质量的最终要求.可以考虑采用全面质量管理的方法,结合部队管理特点,进行使用质量管理.     

航天软件的配置管理

航天软件一般是航天系统中的一个要害软件.要开发一个合格的航天软件,必须严格遵循软件的配置管理.首先论述了航天软件的基本要求,在此基础上较详细介绍了软件配置管理的方法、步骤和要求.