装备制造企业前向物流智能平衡模式研究
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摘要
装备制造业是为国民经济发展和国防建设提供技术装备的基础性产业,是国家综合国力的具体体现。然而,目前我国装备制造企业对市场的快速反应能力差、产品开发周期长、生产成套性差、交货期长等问题已成为在国际、国内竞争中屡屡失利的重要原因之一,且都可归为企业前向物流平衡问题。发达国家已能较好解决这一问题,我国装备制造企业整体水平偏低,信息化水平低,短期内很难通过复制国外模式解决,迫切需要研究适合我国实际情况的有效解决方案,促进集群网络化制造,增强我国装备制造企业的竞争实力。
本文在进行厂校2005年合作项目:张家口煤矿机械有限公司(ZMJ)精确化计划与控制和河北省科技厅06年指导性计划项目:大型装备制造企业精细生产计划智能支持方法研究基础上,通过文献综述分析了我国装备制造企业前向物流研究现状和存在问题,选择中煤集团某国有大型煤机制造企业为代表进行了实地研究,从前向物流整体出发,提出了以智能化技术支持的前向物流动态平衡的解决思路,提出了适应我国国情的装备制造企业前向物流智能平衡模式。论文首先构建总体框架,指出框架中的关键技术,然后分项进行了研究。包括订单排序方法,面向订单的项目型组织设计,设计与制造并行流程再造,变型件快速设计系统、生产提前期智能估算系统和车间调度智能支持系统开发设计。
主要结论:
(1)该类企业属于典型的OKP类型,订单进度控制不力是问题的主要表现。因此提出以订单为核心,建立面向订单的项目型组织结构,加强部门间对订单的跟踪控制,保证订单按期配套出产。
(2)多变市场导致企业技术数据变化频繁,ERP尚缺乏提供动态信息支持,加剧了装备制造企业全面信息化和应变市场的难度。本文认为应集中研究支持ERP的动态数据智能生成解决方案。
(3)本文进行了订单优先级排序、设计和生产并行流程、快速设计、生产提前期估算、车间调度等系统研究,经验证达到预期目标。
主要创新点:
(1)基于产品族数据管理和相似性识别的变型件快速设计方法。
(2)结合模糊聚类的改进型RBF网络训练方法。
(3)将模拟退火算法与多种群遗传算法融入到传统遗传算法中,提出了采用混合遗传算法求解有限能力作业车间调度模型。
Equipment manufacturing industry is the basic industry for national economy and defense, as well as a symbol for overall national strength. However, China's equipment manufactories are facing serious problems like poor capability of quick response to the changing markets, over-long product development cycle, incompleteness of product sets, long delivery time, and so on. These problems, which can be eventually traced back to forward materials handling, have become one of the important reasons of losing ground for China's equipment manufactories in the international and domestic competitions. The developed contries have been able to get these problems settled properly, whereas China's equipment manufactories are in such a low level of development and information technology, that it is very difficult to solve these problems in a short term by copying foreign models. There is an urgent need to study effective solutions, compatible to China's actual situation, in order to promote cluster networked manufacturing, to enhance China's equipment manufactories competitiveness.
In this dissertation, based on the 2005 year’s cooperative project“ZMJ’s Precision Planning and Control”between Zhangjiakou Coal Mine Machinery Co., Ltd.(ZMJ) and Hebei University of Technology(HEBUT), as well as the 2006 year’s guidance project“Intelligence Supporting Methods for Large Equipment Manufactories’Precision Production Planning”from Hebei Provincial Science & Technology Department, the current study situation and problems remained in topics about forward materials handling in China’s equipment manufactories are analyzed through literature review, an on-site study is conducted in a selected large equipment manufactory from China National Coal Group Corporation, and henceforth from the perspective of overall forward materials handling, a solution idea using intelligence supporting methods for dynamic balance to forward materials handling is proposed, and the intelligent balance model compatible to China’s situation for forward materials handling in equipment manufactories is put forward. Furthermore, the overall framework of the dissertation is firstly developed, follwed by comments about key technologies to be used, then issues discussed sequentially including orders sorting method, orders-oriented project organization design, parallel process reengineering of design and manufacturing, rapid design system for deformable parts, intelligent lead-time estimating system, and the design of intelligent workshop scheduling support system.
Major conclusions:
(1) The manufactory in discussion is a typical one-of-a-kind production (OKP) enterprise; its weak control on order progress is the main problem. Therefore, a solution is proposed with focus on orders, by establishing orders-oriented project organization, strengthening orders tracking control across strategic businee units, to ensure matching orders completed on due time.
(2) The changing market leads to frequent changes in corporate technical data and ERP is still lack of dynamic information support, this intensified the manufactory’s difficulties for comprehensive information system and response to the changing market. This article holds that the relative studies should focus on intelligent dynamic data generation solutions to support ERP.
(3) Studies conducted in this dissertation about orders priority sorting, parallel flow of design and manufacturing, rapid design, lead-time estimating methods, workshop scheduling, are verified to achieve the desired objectives. Major innovation view-points:
(1) Rapid design methods for deformable parts using product family data management and similarity identification approach;
(2) Improved RBF-neural networks training methods using fuzzy clustering approach;
(3) A scheduling model solver for limited capacity workshop using mixed genetic algorithm on the basis of simulated annealing algorithm and multiple-population genetic algorithm (MPGA).
本文在进行厂校2005年合作项目:张家口煤矿机械有限公司(ZMJ)精确化计划与控制和河北省科技厅06年指导性计划项目:大型装备制造企业精细生产计划智能支持方法研究基础上,通过文献综述分析了我国装备制造企业前向物流研究现状和存在问题,选择中煤集团某国有大型煤机制造企业为代表进行了实地研究,从前向物流整体出发,提出了以智能化技术支持的前向物流动态平衡的解决思路,提出了适应我国国情的装备制造企业前向物流智能平衡模式。论文首先构建总体框架,指出框架中的关键技术,然后分项进行了研究。包括订单排序方法,面向订单的项目型组织设计,设计与制造并行流程再造,变型件快速设计系统、生产提前期智能估算系统和车间调度智能支持系统开发设计。
主要结论:
(1)该类企业属于典型的OKP类型,订单进度控制不力是问题的主要表现。因此提出以订单为核心,建立面向订单的项目型组织结构,加强部门间对订单的跟踪控制,保证订单按期配套出产。
(2)多变市场导致企业技术数据变化频繁,ERP尚缺乏提供动态信息支持,加剧了装备制造企业全面信息化和应变市场的难度。本文认为应集中研究支持ERP的动态数据智能生成解决方案。
(3)本文进行了订单优先级排序、设计和生产并行流程、快速设计、生产提前期估算、车间调度等系统研究,经验证达到预期目标。
主要创新点:
(1)基于产品族数据管理和相似性识别的变型件快速设计方法。
(2)结合模糊聚类的改进型RBF网络训练方法。
(3)将模拟退火算法与多种群遗传算法融入到传统遗传算法中,提出了采用混合遗传算法求解有限能力作业车间调度模型。
Equipment manufacturing industry is the basic industry for national economy and defense, as well as a symbol for overall national strength. However, China's equipment manufactories are facing serious problems like poor capability of quick response to the changing markets, over-long product development cycle, incompleteness of product sets, long delivery time, and so on. These problems, which can be eventually traced back to forward materials handling, have become one of the important reasons of losing ground for China's equipment manufactories in the international and domestic competitions. The developed contries have been able to get these problems settled properly, whereas China's equipment manufactories are in such a low level of development and information technology, that it is very difficult to solve these problems in a short term by copying foreign models. There is an urgent need to study effective solutions, compatible to China's actual situation, in order to promote cluster networked manufacturing, to enhance China's equipment manufactories competitiveness.
In this dissertation, based on the 2005 year’s cooperative project“ZMJ’s Precision Planning and Control”between Zhangjiakou Coal Mine Machinery Co., Ltd.(ZMJ) and Hebei University of Technology(HEBUT), as well as the 2006 year’s guidance project“Intelligence Supporting Methods for Large Equipment Manufactories’Precision Production Planning”from Hebei Provincial Science & Technology Department, the current study situation and problems remained in topics about forward materials handling in China’s equipment manufactories are analyzed through literature review, an on-site study is conducted in a selected large equipment manufactory from China National Coal Group Corporation, and henceforth from the perspective of overall forward materials handling, a solution idea using intelligence supporting methods for dynamic balance to forward materials handling is proposed, and the intelligent balance model compatible to China’s situation for forward materials handling in equipment manufactories is put forward. Furthermore, the overall framework of the dissertation is firstly developed, follwed by comments about key technologies to be used, then issues discussed sequentially including orders sorting method, orders-oriented project organization design, parallel process reengineering of design and manufacturing, rapid design system for deformable parts, intelligent lead-time estimating system, and the design of intelligent workshop scheduling support system.
Major conclusions:
(1) The manufactory in discussion is a typical one-of-a-kind production (OKP) enterprise; its weak control on order progress is the main problem. Therefore, a solution is proposed with focus on orders, by establishing orders-oriented project organization, strengthening orders tracking control across strategic businee units, to ensure matching orders completed on due time.
(2) The changing market leads to frequent changes in corporate technical data and ERP is still lack of dynamic information support, this intensified the manufactory’s difficulties for comprehensive information system and response to the changing market. This article holds that the relative studies should focus on intelligent dynamic data generation solutions to support ERP.
(3) Studies conducted in this dissertation about orders priority sorting, parallel flow of design and manufacturing, rapid design, lead-time estimating methods, workshop scheduling, are verified to achieve the desired objectives. Major innovation view-points:
(1) Rapid design methods for deformable parts using product family data management and similarity identification approach;
(2) Improved RBF-neural networks training methods using fuzzy clustering approach;
(3) A scheduling model solver for limited capacity workshop using mixed genetic algorithm on the basis of simulated annealing algorithm and multiple-population genetic algorithm (MPGA).
引文
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