基于多目标的虚拟制造单元运行优化方法研究

发布时间：2019-02-22 20:15

【摘要】：制造业要满足消费者订单的快速变化和市场环境的动态调整,必须改变传统的大规模生产模式,多品种小批量生产模式已经成为信息时代制造业的主导生产方式,也是工业4.0时代的重要生产组织和管理模式之一。在“中国制造2025”战略的实施过程中,制造基础不断强化,多品种小批量生产模式成为智能制造发展行动计划的重要内容。虚拟制造单元(Virtual manufacturing cell,VMC)是实现多品种小批量生产模式的一种新的车间制造模式,也是实现数字化、网络化、智能化制造的技术支撑。本论文以虚拟制造单元的资源优化、生产调度以及多目标虚拟制造单元优化方案决策为研究重点,主要研究内容如下：1、多品种小批量生产模式下客户目标个性鲜明、不同企业或企业内部部门往往呈现相互冲突的目标诉求；生产环境复杂多变、生产制造系统内外不可避免的不确定性扰动,导致生产过程呈现动态多变的特征。引入基于车间动态重构实现任务的分解与虚拟制造单元的生成,达到设备资源动态优化组合；应用成组技术,将多品种小批量生产转换为批量生产,提高制造资源的利用率、降低生产成本。2、在分析虚拟制造单元构建技术、启发式算法和Pareto占优技术等基础上,提出基于Pareto占优的改进自由搜索算法求解多目标虚拟制造单元资源优化问题,并证明所提算法的收敛性,分析算法的收敛速度和复杂度。3、单元生产调度是单元内部自主决策的工序排序与机器分配过程,是虚拟制造单元运行的重要步骤,引入Pareto占优技术,改进种群维护策略,提出基于改进遗传算法求解单元生产调度。针对虚拟制造单元的不确定性扰动,运用滚动窗口和泛灰数技术,研究了一类工序加工时间为区间数的重调度策略,并通过实例进行验证。4、通过虚拟制造单元资源优化和生产调度,生成多品种小批量制造模式候选方案,为实现虚拟制造单元的整体优化,提出基于Pareto占优解集的双层联合决策模型,采用分步决策与信息反馈相结合的原则,运用决策者信息偏好机制和多属性决策方法,实现虚拟制造单元运行整体方案的优化决策。
[Abstract]:In order to satisfy the rapid change of consumer orders and the dynamic adjustment of market environment, the manufacturing industry must change the traditional large-scale production mode. The multi-variety and small-batch production mode has become the leading mode of manufacturing in the information age. It is also one of the important production organization and management models in the 4.0 era of industry. In the process of implementing the "made in China 2025" strategy, the manufacturing foundation has been continuously strengthened, and the multi-variety and small-batch production model has become an important part of the intelligent manufacturing development action plan. Virtual manufacturing unit (Virtual manufacturing cell,VMC) is a new workshop manufacturing model to realize multi-variety and small-batch production mode, and it is also the technical support to realize digital, networked and intelligent manufacturing. This thesis focuses on the resource optimization, production scheduling and multi-objective virtual manufacturing cell optimization scheme decision. The main research contents are as follows: 1. In the multi-variety and small-batch production mode, the customer's objective personality is distinct. Different enterprises or internal departments of enterprises often present conflicting goals and demands; The production environment is complex and changeable, and the inevitable uncertainty disturbance inside and outside the production manufacturing system leads to the dynamic characteristics of the production process. The task decomposition based on workshop dynamic reconfiguration and the generation of virtual manufacturing cell are introduced to achieve the dynamic combination of equipment resources. With the application of group technology, multi-variety and small-batch production is converted into batch production, which improves the utilization rate of manufacturing resources and reduces production cost. 2. Based on the analysis of virtual manufacturing cell construction technology, heuristic algorithm and Pareto dominant technology, etc. An improved free search algorithm based on Pareto is proposed to solve the multi-objective virtual manufacturing cell resource optimization problem. The convergence of the proposed algorithm is proved, and the convergence speed and complexity of the algorithm are analyzed. Unit production scheduling is an important step of virtual manufacturing unit (VMU) operation. It is an important process of scheduling and machine allocation for autonomous decision making within a unit. The dominant technology of Pareto is introduced to improve the population maintenance strategy. An improved genetic algorithm is proposed to solve unit production scheduling. In view of the uncertainty disturbance of virtual manufacturing cell, a kind of rescheduling strategy with processing time of interval number is studied by using rolling window and pan-grey number technology. In order to realize the overall optimization of virtual manufacturing cells, a two-layer joint decision model based on Pareto dominating solution set is proposed to realize the overall optimization of virtual manufacturing cells by optimizing the resources of virtual manufacturing cells and production scheduling. Based on the principle of the combination of step decision and information feedback, decision makers' information preference mechanism and multi-attribute decision making method are used to realize the optimal decision of the whole scheme of virtual manufacturing cell operation.
【学位授予单位】：合肥工业大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：F424;F273

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