摘要
复杂产品是客户需求复杂、产品组成复杂、产品技术复杂、制造流程复杂、试验维护复杂、项目管理复杂、工作环境复杂的一类产品。复杂产品由原材料加工为产品或半成品的过程,通常是在多级制造系统(Multistage Manufacturing System, MMS)内完成的。多级制造系统的各级子系统可以实现加工、装配或其他能够增值的制造过程,由工作单元、车间、分厂或企业组成。在复杂产品多级制造系统中,各级系统之间一般关系复杂、生产种类繁多、产品结构复杂、信息交流频繁。其生产计划及生产管理十分复杂,因此研究多级制造系统生产计划与调度集成优化非常重要。
本文以复杂产品多级制造系统为研究对象,提出以生产计划与调度集成优化研究为核心,以产品标准时间计算研究和制造资源与任务集成建模研究为辅的多级制造系统生产计划与调度集成优化关键技术的研究。主要工作有:
(1)针对多级制造系统生产计划与调度集成优化过程中所需要的大量准确的产品工时信息,提出预处理研究:复杂产品多级制造系统产品标准时间计算研究。在分析当前标准时间和工时计算研究现状和不足的基础上,提出了基于基元操作(Primitive Operation, PO)的人工作业标准时间计算研究以及基于设备类型和基元操作的产品标准时间计算方法。
(2)针对多级制造系统生产计划与调度集成优化过程中所需要的复杂的制造资源信息,提出预处理研究:复杂产品多级制造系统制造资源与任务集成建模研究。针对制造资源模型描述底层化和制造资源信息集成度低的问题,提出了制造资源的能力制造单元(Capacity Manufacturing Unit, CMU)和基于CMU的制造资源与任务集成模型(Manufacturing Resource and Task Integrated Model, MRTIM)。
提出的复杂产品多级制造系统产品标准时间计算方法能够比较准确、快捷地制定产品工时,MRTIM模型把制造资源、任务、工时、人员配置等多种信息集成在同一个模型框架内并建立起了映射关系,从而为生产计划与调度集成优化提供快速、准确的信息支持。在预处理研究的基础上,提出本文的核心研究内容:
(3)复杂产品多级制造系统的生产计划与调度集成优化(Integrated Optimization of Production Planning and Scheduling, IOPPS)建模研究。针对串行生产计划和调度存在的计划与调度割裂、计划难以响应调度过程中的变化、变化不能及时反馈的问题,提出了生产计划与调度集成优化研究。针对多级制造系统的典型子系统,提出了柔性作业车间和置换流水车间的生产计划与调度集成优化完备建模问题定义及其基于多种目标和约束的多产品生产计划与调度集成优化完备模型;针对生产关系复杂、计划与调度信息交互频繁的多级制造系统,提出了多级制造系统生产计划与调度集成优化建模问题的定义,建立了考虑各级系统之间生产衔接等问题的多级制造系统生产计划与调度集成优化完备模型。解决了串行生产计划和调度存在的问题和多层次结构产品的生产计划与调度综合优化建模问题,实现了多级制造系统及其单级子系统中生产计划与调度的同时优化。
(4)复杂产品多级制造系统的生产计划与调度集成优化模型求解算法研究。针对生产计划与调度集成优化完备模型难于求解的问题,采用全空间(Full Space)启发式求解方式来求解此问题。提出了改进离散微粒群优化(Modified Discrete Particle Swarm Optimization, MDPSO)算法和基于并行MDPSO的文化算法(Cultural Algorithm based on MDPSO, CA-MDPSO)。在经典微粒群优化算法(Particle Swarm Optimization, PSO)基础上,对其编码方式、解码方式、进化方式进行相应的改进,提出改进的离散微粒群优化(MDPSO)算法来解决生产计划与调度集成优化问题,仿真和算法比较实验结果证明了算法的有效性;将提出的MDPSO进化算法嵌入到文化算法的进化框架中,提出基于并行MDPSO的文化算法(CA-MDPSO)来解决多级制造系统生产计划与调度集成优化问题,仿真和算法比较实验结果证明了算法的有效性。解决了多级制造系统及其单级子系统生产计划与调度集成优化完备模型的求解问题,在新兴智能优化算法改进及其在生产计划与调度集成优化领域的应用研究方面有所贡献。
(5)为了对提出的方法和模型进行系统实现和验证,设计了基于网络运行的复杂产品多级制造系统生产计划与调度集成优化的原型系统,实现了产品标准时间实时计算、调用,制造资源与任务集成建模、查找,生产计划与调度集成优化的建模、求解等功能,完整地对论文的核心思想进行了验证和系统实现。
本文的研究成果在一定程度上丰富了复杂产品多级制造系统生产计划与调度集成优化关键技术的研究,从产品的标准时间建立、制造资源与任务信息的明晰化到车间生产计划与调度集成优化工作的开展,构成了一个有机的整体。提出的关键技术不仅在理论方面有所突破,而且可以有效提升制造企业的竞争力,达到在不增加或少增加投入的情况下,提高企业生产力、资源利用率和决策管理能力的目的。
Complex products are a kind of product which has complicated demand, production technology, manufacturing process, system maintenance, project management and work environment. The process from raw materials to products or semi-finished products for complex products is usually completed in the multistage manufacturing system. The subsystems of multistage manufacturing system may be the work unit, workshops of an enterprise or the enterprises of an enterprise union, which can achieve the machining, assembly and other value adding manufacturing process. In the complex products multistage manufacturing system, the production relationship among subsystems is complex, the production type is various, the processing object is changing constantly and the information communication is frequent. Therefore, its production planning and management is very complicated and integrated optimization of production planning and scheduling of multistage manufacturing system for complex products seems very important.
In this dissertation, we focused on integrated optimization of production planning and scheduling study, the product man-hour calculation study and manufacturing resource modeling study. The main study is summarized as follows:
(1) To provide the abundant and accurate product man-hour for integrated optimization of production planning and scheduling of the multistage manufacturing system, the product standard time calculation study was presented as the pretreatment study for integrated optimization of production planning and scheduling. After the analysis on the current standard time and man-hour calculation study, the manual standard time calculation based on primitive operation(PO) and the product standard time calculation based on primitive operation and equipment type were presented.
(2) To provide the complex manufacturing resource and task information for integrated optimization of production planning and scheduling of the multistage manufacturing system, the manufacturing resource and task integrated modeling study was presented as the pretreatment study for integrated optimization of production planning and scheduling. In order to solve the manufacturing resource description and integration, the Capacity Manufacturing Unit(CMU) and the Manufacturing Resource and Task Integrated Model(MRTIM) based on CMU were proposed.
The proposed standard time calculation method can calculate product standard time accurately and rapidly, and the MRTIM can integrate the manufacturing resource, task, man-hour and person configuration in a frame and construct the mapping relationship. They provide a strong support for production planning and scheduling rapidly and accuratedly. On the basis of pretreatments study, the core research content of this dissertation were proposed.
(3) The integrated optimization of production planning and scheduling modeling study on complex products multistage manufacturing system. In the traditional serial production planning and scheduling, the production planning and scheduling are dissevered, and the plan cannot respond the changes in the scheduling process, the changes in the scheduling process cannot be fed back to plan. In order to solve this problem, the integrated optimization of production planning and scheduling study was presented. Firstly, the classical subsystems integrated optimization of production planning and scheduling definition and detailed model of the multistage manufacturing subsystem were proposed, such as Flexible Jobshop and Permutation Flowshop; Then the multistage manufacturing system integrated optimization of production planning and scheduling model was presented, which considered the complex production relation among subsystems and the frequent communication between production planning and scheduling. Therefore, the modeling study achieves the simultaneous optimization of production planning and scheduling, and the defect of serial production planning and scheduling is overcome and the integrated optimization of production planning and scheduling for multiproduct is solved.
(4) The algorithm study of integrated optimization of production planning and scheduling detailed model for complex products multistage manufacturing system. To solve the multistage manufacturing system integrated optimization of production planning and scheduling model in full space, the Modified Discrete Particle Swarm Optimization(MDPSO) algorithm and the Cultural Algorithm based on MDPSO(CA-MDPSO) were presented. MDPSO algorithm has unique encoding and decoding mode and modified evolutionary approach compared with classical Particle Swarm Optimization(PSO). CA-MDPSO is the combination of MDPSO algorithm, Cultural algorithm and Genetic algorithm and possesses two-level evolution frame. The experiment and comparison with other classical algorithms verifies the validity of the presented algorithms. This section solved the integrated optimization of production planning and scheduling model and improved the new intelligent optimization algorithms and extended their application in integrated optimization of production planning and scheduling domain.
(5) The prototype system of complex products multistage manufacturing system integrated optimization of production planning and scheduling based on network was designed, which verified the presented theory and methods inextenso, such as product standard time calculation and search, manufacturing resource and task modeling and resource search and integrated optimization of production planning and scheduling.
The research makes some contributions in key techniques of multistage manufacturing system integrated optimization of production planning and scheduling study. From the product basic standard time establishment, the vitrification of manufacturing resource and the implement of integrated optimization of production planning and scheduling, the presented research form an organic whole. The presented key technology not only make a breakthrough in the theory study, but also can effectively enhance the competitiveness of manufacturing enterprises, and improve the enterprise productivity, resource utilization and management capacity with no investment or less investment consequently.
引文
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