冷轧全流程生产计划与动态调度方法的研究与应用
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摘要
冷轧薄板企业生产计划与调度是信息化管理系统的核心功能之一,合理可行的生产计划可以人幅度地提高企业的管理水平和生产能力,但是制定企业生产计划与调度方案的过程,受到机组生产能力、库存变化、产品规格与质量、交货期等多方面因素的约束,具有动态性、适应性、鲁棒性的要求。本文依托国家“863计划”课题,针对目前冷轧薄板生产企业轧制过程的管理模式、生产方式,对轧制过程的生产计划与调度问题开展了深入系统的研究。本文的主要研究内容如下：
根据冷轧机组生产特点,为解决生产调度问题,把排产过程归纳为非对称双旅行商问题,以生产合同序列的宽度变化、入口厚度变化和出口厚度变化作求解的子目标,建立基于Pareto的多目标冷轧机组生产作业计划模型。构造了基于Pareto非支配集的自适应多目标蚁群算法,得到Pareto非支配解集表示调度结果,为机组生产调度系统提供多个可行的批量作业计划用于选择。
根据定货合同的特点,利用待产合同的宽度、入口厚度、出口厚度与交货期数据建立子空间聚类模型,提出了带有交货期区间特征的子空间聚类方法完成合同组批。根据宝钢冷轧薄板厂机组分布关系,以冷轧机组为中心结点,考虑机组的生产能力和工艺规程,建立了针对准时交货、合理分配产能和降低在制品库存的全流程合同计划模型,利用分时蚁群算法,依据合同的交货期、在制品库存和产品的生产流向要求,实现合同生产排产和产能分配。
通过研究宝钢冷轧薄板厂各个机组的生产特点,针对二次冷轧机组与平整机组之间、各个涂镀机组之间可以生产相同产品的特殊性,建立了基于部分重构的冷轧生产过程混杂Petri网生产调度模型,并分机组类别构造线性+规划模型。利用提出的有限搜索蚁群算法,限制算法搜索范围,在机组定修与计划工艺调整期间,对生产合同的生产流向进行部分生产重构。
通过研究冷轧薄板厂生产过程中突发故障、插入紧急合同等动态事件的特点,利用混杂Petri网和UML技术建立多Agent系统模型。针对全流程生产合同分配、可重构机组生产的不同情况,建立了相应的动态重调度模型。同时,将事件特征、时间等因素加入到蚁群搜索过程中,提出了用于求解的动态约束蚁群算法和基于蚁群聚类的合同选取方法。
基于上述模型与算法,应用软件工程技术开发了宝钢冷轧薄板厂的生产计划与调度系统,通过上海宝钢冷轧薄板厂的实际运行情况表明,本文提出的方法可以提高冷轧企业生产计划与调度过程的决策能力,达到了提高生产效率、减轻调度过程的复杂度和提高系统适应能力的目的。
One of the key functions is the production planning and scheduling of management information system of cold rolling enterprise. The management level and the production capacity could be improved with rational and feasible planning. However, since the establishment of planning and scheduling schema is largely restricted by the capacity of mills, the inventory of work in process, the specification and quality of products and delivery date, the schemas have to be with the characteristics of dynamic, adaptive and robust. Depended on a key project of National High-Tech Research and Development Programme, this dissertation studies the planning and scheduling problem for cold rolling process in accordance with the current production and management mode. The main contents of this dissertation are as follows.
The scheduling problem of cold rolling mill is summarized as an asymmetric double traveling salesman problem that is implemented by job scheduling of cold rolling process due to the production specification of mill. The multi-objective scheduling model based on the Pareto optimization is constructed which includes three objectives, i.e. the change in width, thick of entrance and exit between two continuous rolling steel coils. A Pareto Multi-Objective Ant Colony Algorithm (PAACO) depending on Pareto non-dominated set is then proposed. The final scheduling result is obtained from the non-dominated set.
A Subspace Adaptive Clustering with Interval Feature on Time Window (SACIT) is presented for grouping the orders according to their specifications. Based on the connection among mills in BaoSteel Cold Rolled Sheet Mill, the tandem cold mill is regarded as the center of the enterprise and the batch planning method of the whole flow is presented which considers the capacity of cold rolling mill and process specification. Using the proposed Time-segment Ant Colony Optimization (TACO), the orders production planning and capacity allocation are carried out taking account to the delivery date, the inventory of work in process and the production route of products.
The partly reconfigurable hybrid Petri-net model is established to reduce the interference by the periodic maintenance and regular technology adjustment of some mills. A Finite-Searching Ant Colony Optimization (FSACO) is introduced by means of mill capacity, delivery date and affectivity of orders. In the period of maintenance and regular technology adjustment of mills, the production flows of part of orders are reallocated via the method and the proposed FSACO searches orders with high priority and make them close to due date in the restriction of mill load.
Through the researching on the characteristics of dynamic events in the process of production, the dynamic planning and scheduling system based on the multi-agent is established with hybrid Petri net and UML technology. The different dynamic rescheduling non-linear programming models are constructed to the whole flow production and the reconfigurable mills. A Dynamic Constraint Ant Colony Optimization (DCACO) and a Contract Fetch Approach Based on Ant Colony Clustering (CFAAC) are presented to obtain the dynamic scheduling result.
The production planning and scheduling system for the BaoSteel Cold Rolling Sheet Mill is established based on the above-mentioned models and algorithms and is applied to the practical production process. The results indicate the presented method in this dissertation can improve the strategy capacity of the planning and scheduling system, reduce production cost and the complexity of scheduling process and enhance the adaptability of the system.
根据冷轧机组生产特点,为解决生产调度问题,把排产过程归纳为非对称双旅行商问题,以生产合同序列的宽度变化、入口厚度变化和出口厚度变化作求解的子目标,建立基于Pareto的多目标冷轧机组生产作业计划模型。构造了基于Pareto非支配集的自适应多目标蚁群算法,得到Pareto非支配解集表示调度结果,为机组生产调度系统提供多个可行的批量作业计划用于选择。
根据定货合同的特点,利用待产合同的宽度、入口厚度、出口厚度与交货期数据建立子空间聚类模型,提出了带有交货期区间特征的子空间聚类方法完成合同组批。根据宝钢冷轧薄板厂机组分布关系,以冷轧机组为中心结点,考虑机组的生产能力和工艺规程,建立了针对准时交货、合理分配产能和降低在制品库存的全流程合同计划模型,利用分时蚁群算法,依据合同的交货期、在制品库存和产品的生产流向要求,实现合同生产排产和产能分配。
通过研究宝钢冷轧薄板厂各个机组的生产特点,针对二次冷轧机组与平整机组之间、各个涂镀机组之间可以生产相同产品的特殊性,建立了基于部分重构的冷轧生产过程混杂Petri网生产调度模型,并分机组类别构造线性+规划模型。利用提出的有限搜索蚁群算法,限制算法搜索范围,在机组定修与计划工艺调整期间,对生产合同的生产流向进行部分生产重构。
通过研究冷轧薄板厂生产过程中突发故障、插入紧急合同等动态事件的特点,利用混杂Petri网和UML技术建立多Agent系统模型。针对全流程生产合同分配、可重构机组生产的不同情况,建立了相应的动态重调度模型。同时,将事件特征、时间等因素加入到蚁群搜索过程中,提出了用于求解的动态约束蚁群算法和基于蚁群聚类的合同选取方法。
基于上述模型与算法,应用软件工程技术开发了宝钢冷轧薄板厂的生产计划与调度系统,通过上海宝钢冷轧薄板厂的实际运行情况表明,本文提出的方法可以提高冷轧企业生产计划与调度过程的决策能力,达到了提高生产效率、减轻调度过程的复杂度和提高系统适应能力的目的。
One of the key functions is the production planning and scheduling of management information system of cold rolling enterprise. The management level and the production capacity could be improved with rational and feasible planning. However, since the establishment of planning and scheduling schema is largely restricted by the capacity of mills, the inventory of work in process, the specification and quality of products and delivery date, the schemas have to be with the characteristics of dynamic, adaptive and robust. Depended on a key project of National High-Tech Research and Development Programme, this dissertation studies the planning and scheduling problem for cold rolling process in accordance with the current production and management mode. The main contents of this dissertation are as follows.
The scheduling problem of cold rolling mill is summarized as an asymmetric double traveling salesman problem that is implemented by job scheduling of cold rolling process due to the production specification of mill. The multi-objective scheduling model based on the Pareto optimization is constructed which includes three objectives, i.e. the change in width, thick of entrance and exit between two continuous rolling steel coils. A Pareto Multi-Objective Ant Colony Algorithm (PAACO) depending on Pareto non-dominated set is then proposed. The final scheduling result is obtained from the non-dominated set.
A Subspace Adaptive Clustering with Interval Feature on Time Window (SACIT) is presented for grouping the orders according to their specifications. Based on the connection among mills in BaoSteel Cold Rolled Sheet Mill, the tandem cold mill is regarded as the center of the enterprise and the batch planning method of the whole flow is presented which considers the capacity of cold rolling mill and process specification. Using the proposed Time-segment Ant Colony Optimization (TACO), the orders production planning and capacity allocation are carried out taking account to the delivery date, the inventory of work in process and the production route of products.
The partly reconfigurable hybrid Petri-net model is established to reduce the interference by the periodic maintenance and regular technology adjustment of some mills. A Finite-Searching Ant Colony Optimization (FSACO) is introduced by means of mill capacity, delivery date and affectivity of orders. In the period of maintenance and regular technology adjustment of mills, the production flows of part of orders are reallocated via the method and the proposed FSACO searches orders with high priority and make them close to due date in the restriction of mill load.
Through the researching on the characteristics of dynamic events in the process of production, the dynamic planning and scheduling system based on the multi-agent is established with hybrid Petri net and UML technology. The different dynamic rescheduling non-linear programming models are constructed to the whole flow production and the reconfigurable mills. A Dynamic Constraint Ant Colony Optimization (DCACO) and a Contract Fetch Approach Based on Ant Colony Clustering (CFAAC) are presented to obtain the dynamic scheduling result.
The production planning and scheduling system for the BaoSteel Cold Rolling Sheet Mill is established based on the above-mentioned models and algorithms and is applied to the practical production process. The results indicate the presented method in this dissertation can improve the strategy capacity of the planning and scheduling system, reduce production cost and the complexity of scheduling process and enhance the adaptability of the system.
引文
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