关于构建模块化军事素质培养体系的思考

模块化军事素质培养体系的核心和特色是既相对独立又密切联系的6个“模块”;这6个“模块”分别在人才培养的不同阶段实施,达到阶段教育目的,并有机地整合成为一个整体,使人才达到最终的培养目标。     

“4+1“模式军事人才培养综合素质评价研究

利用突变级数法的基本思想和突变系统的4种常用类型:尖点突变、燕尾突变、蝴蝶突变、因第安人茅舍突变,依据灰色理论和模糊数学,建立多目标的突变评价方法模型。在建立新型军事人才综合素质评价指标体系的基础上,运用突变模型对新型军事人才的综合素质进行了综合评价。     

如何在课程教学中培养学员的素质和能力

如何实施素质教育是教育改革中的重要课题,本文根据教学实际,结合教学过程和教学内容对学员进行学习指导,提出培养学员素质和能力的途径。     

软件开发若干问题分析

随着各种MIS系统的需求量急剧增加,MIS系统质量的高低决定着计算机应用所产生效益的大小,提高软件质量已是用户和计算机工作者均特别关注的问题。分析了目前MIS系统开发中存在的问题及影响软件质量的因素,并提出了相应的解决办法。     

贯彻科技兴军战略,提高军事职业教育质量水平

发展军事职业教育是健全新型军事人才培养体系的重大举措。贯彻科技兴军战略,必须深刻认识提高军事职业教育质量水平的重大意义,清晰把握提高军事职业教育质量水平的内在要求,切实找准提高军事职业教育质量水平的重要抓手。     

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.     

更新美术教育思想 促进素质教育实施

美术教育是促进素质教育的一个很重要的方面。它对培养学生的创新意识和创造能力有着不可替代的作用。树立全新的美术教育思想 ,可促进素质教育深入开展     

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.     

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.     

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