摘要
模具是装备制造业的重要组成部分,模具生产水平的高低,已经成为衡量一个国家产品制造水平高低的重要标志。虽然企业不断引进高端数控加工装备,但在高端精密模具制造技术水平方面与发达工业国家仍存在较大的差距。加工精度不高、制造周期普遍过长、订单交货拖期严重是制约我国模具企业国际竞争力的三大关键因素。究其原因,主要是缺乏一种适应模具制造特点的有效生产控制方法。
面向资源的单件工程订货型生产方式使得模具制造过程中充满着大量各种不确定性因素,这给模具车间制订合理可行的作业计划带来了一定的困难。而在基准方案执行当中,突发事件的频繁冲击将使得初始制订的基准调度方案可执行性不强。因此,必须采取有效的预先防范手段,以及合理的重调度方法与控制策略,确保生产计划按时按质完成。
本文在国家自然科学基金(50675039、50875051)和国家863计划资助项目(2006AA04Z132)的联合资助下研究不确定环境下的模具制造车间前摄与反应式调度问题。根据模具制造单元的特点,对不确定因素进行了分析及建模,详细探讨了不确定环境下模具制造车间调度决策机制,重调度驱动机制,建立了相关调度模型和求解算法。模具柔性流水车间前摄与反应式调度决策支持系统的实施,将有助于提高企业生产计划与控制水平,增强企业市场竞争力。
本文的主要工作包含以下几个方面：
1、提出了以主关键件为控制指针的模具生产组织结构,建立了不确定环境下模具柔性流水车间模型,并针对三种主要不确定因素建立了数学模型,最后提出了模具制造车间前摄与反应式调度框架；
2、基于工时离散概率模型,分析工时组合情况。在此基础上,提出了以最大化稳定度为优化目标的前摄性调度模型,提出了一种变宽集束搜索求解算法,通过与定宽集束搜索算法的对比分析,表明在求解质量和计算耗时方面均具有优势；
3、定义了工序延期概念,提出了工序累积延期的计算方法。针对模具柔性流水车间存在隐性不确定因素和显性不确定因素的影响,提出了基于累积延期和事件触发混合驱动的反应式调度机制,建立了基于Plant Simulation的仿真模型,分析了混合驱动机制的属性,并与周期性重调度、事件驱动重调度进行了对比分析,结果表明该混合驱动机制能获得较低的反应式调度频率,并且在急单插入频率较高的情况下还能保持良好的调度性能；
4、基于上述调度衡量指标,提出了模具柔性流水车间两阶段反应式调度模型,包含局部修补调度和反应式调度两个阶段。当混合驱动机制触发反应式调度,首先执行反应式调度模型的第一阶段：局部修补调度。在局部修补阶段,将稳定性指标作为首要考虑因素,工件在机器上的加工序列不变,对于受影响工序在时间轴上延后其开始加工时间。采用约束传播树表示,提出了基于约束传播树的受影响工序局部修补算法。将所提算法与传统右移(Right Shift)重调度方法比较,分析了在机器故障和急单插入情况下局部修补算法具有一定优越性；
5、通过局部修补算法求解得到调度方案后,通过设定一个评价模型,包括拖期情况分析,拖期惩罚成本分析,以辅助调度人员进行决策,由计划调度员根据情况交互启动第二阶段。在第二阶段的反应式调度：双目标反应式调度。构建了兼具有效性和稳定性的双目标反应式调度模型,将基于欧几里得拥挤距离的非支配排序与基于聚类算法的精英归档策略相结合,提出一种改进的多目标遗传算法进行反应式调度模型求解,并与NSGA-Ⅱ算法进行比较,仿真结果显示,由于采用了基于欧几里德拥挤距离的非支配排序,MMOGA算法求得的非劣解分布比NSGA-Ⅱ算法更均匀,更靠近近似Pareto最优前端；
6、分析了企业基本业务流程和生产计划递阶协调控制模式,设计了系统的功能模块和数据库,开发了一套模具柔性流水车间前摄与反应式调度决策支持系统,用于辅助生产总调协调整个生产车间活动,及时对突发事件作出反应,应用效果良好。
Moulds and Dies (M&D) serve as an essential constituent for total equipment manufacturing industry, whose manufacturing abilities have been an important symbol to measure industrial production abilities of a country. Although companies continue to introduce and improve the high-level CNC machining equipment, there is still large gap between China and other advanced industrial countries in the manufacture technology of high-level precision mould, which mainly reflected in the machining accuracy is lower, the manufacturing cycle is generally too long, and the order delivery tardiness is serious. Those factors restrict the international competitiveness of our mould companies. The main reason is that mould companies lack an effective and proper production control approach.
M&D manufacturing is single piece production order form with resource-oriented so that the manufacturing process is filled with large variety of uncertainties. Hence, it is difficult to make a reasonable and feasible baseline schedule in the mould shop floor. During the schedule executing, frequent impact of unexpected events will make the baseline schedule infeasible. Therefore, it is necessary to take effective proactive-measures, and reasonable rescheduling and control strategy to ensure that the production plan is completed on time.
Supported by the National Natural Science Foundation of China (Grant No.50675039,50875051) and the National High-Tech. R&D Program of China (Grant No.2006AA04Z132), our research focused on proactive and reactive scheduling for mould manufacturing workshop under uncertain environments. The modeling methods for uncertainty were analyzed. The following three issues were discussed in detail:the decision-making mechanism of M&D workshop under uncertain environments, the driven mechanism of rescheduling, and the model and algorithm of scheduling. The implementation of proactive-reactive scheduling decision support system of M&D Flexible Flow Shop will help to improve production planning and control, and enhance the market competitiveness of company.
The research mainly includes the following aspects.
1. Organizational structure of M&D production based on controller of key parts was proposed. The M&D Flexible Flow Shop under uncertain environments was built. The mathematical models for the three major uncertainties were built, and the proactive-reactive scheduling framework was proposed.
2. The combination of processing time based on discrete probability model was analyzed. A proactive scheduling model of three stages flexible flow shop was built, which objective was to maximize schedule stability. Furthermore, a width-variable beam search(VBS) algorithm was presented for solving the proactive scheduling model. Finally, the comparative analysis with the fixed width beam search(FBS) was pursued. And, the computational results show that the presented algorithm has a good balance between solution quality and computation time.
3. The operation delay was defined and the calculation method of cumulative task delays was presented. The hybride-driven mechanism based on cumulative delays and even-driven was proposed to deal with recessive uncertainty and dominant uncertainty. The simulation model based on Plant Simulation was built to analyze the properties of the hybrid-driven mechanism. The comparative analysis of periodic rescheduling, event-driven rescheduling and hybrid-driven rescheduling were pursued.
4. Two-stage reactive scheduling model of mould workshop was proposed based on the reactive scheduling measures. The two-stage reactive scheduling model includs local repair scheduling and reactive scheduling. The local repair scheduling procedure was implemented when the hybrid-driven mechanism was triggered. In local repair stage, the stability was priory consideration. The sequence of job on the machine was keep the same, but the processing time of the affected operation was delayed along the time axis. The constraint propagation tree was defined and affected operation local repair algorithm was proposed. The comparative analysis of the local repair algorithm and Right Shift rescheduling was pursued.
5. The new schedule generated by local repair algorithm will be evaluated by evaluation model and the dispatcher. If new schedule caused serious tardiness or high tardiness penalty costs, it needed to go to the second stage of reactive scheduling. The multi-object reactive scheduling model that simultaneously considered efficiency and stability was built. A modified multi-objective genetic algorithm for reactive scheduling model was proposed, which combined the Euclid crowded distance based non-dominated sorting and clustering algorithm based elite archiving strategy.The comparative analysis of modified multi-objective genetic algorithm and NSGA-Ⅱ was carried out. Simulation results show that because of the Euclid crowded distance based non-dominated sorting, MMOGA algorithm can obtained more uniform Pareto distribution than the NSGA-Ⅱ algorithm, can obtained closer approximation of the Pareto optimal front-end;
6. Enterprise business processes and production planning hierarchical coordination control mode was analyzed. The system function module and the database were designed. The flexible flow shop proactive and reactive scheduling decision support system was developed for coordinating the whole production workshop activities.
引文
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