具有资源协同作业约束的智能制造车间资源配置优化

Considering random Flexible Manufacturing System contains handling robots which with the uncertainty of demand and the dual resource constraints, this projectdeals with the Resource Allocation Problem (RAP), i.e. under the condition of stochastic arrivals of the orders, minimizing the total amount of investment subject to constraints of both average throughput and make-span of products. Specific include: setting up the queueing network models of flexible manufacturing cells with Dual Resource Constraints (DRC) in which robots are used to load/ unload the parts and analyzing the performance of the models; putting forward the double resources optimal allocation problem of the decomposition-iterative optimization algorithm; analyzing the convergence and the equivalence property of the decomposition-iterative algorithm. Characteristic and innovation of this project lie in the following: extend the open queuing network models with finite buffer to describe the behaviors of manufacturing cells with DRC; A problem-features based branch-and-bound algorithm is put forward by means of decomposing the complicated problem into two interconnected sub-problems, one is a Capacity Configuration Problem (CCP) and the other a Buffer Allocation Problem (BAP), an iterative framework is presented between them, thus enhancing the efficiency of searching the optimal solution to RAP of a manufacturing cell with DRC. The output of this project can provide the order-driven manufacturers with scientific methodology for the resource allocation, which require to take capacity expansion or to build up a new factory.

考虑含有自动装卸机器人柔性制造单元的随机生产系统具有的需求与工时的不确定性、资源协同作业约束等特性，本项目研究其资源的优化配置方法，即在订单随机到达的情况下，配置各类制造资源的数量，使得生产系统以最小的投资满足产品的平均产出率和平均生产周期约束。具体包括：建立具有自动装卸工件机器人的制造单元资源协同作业约束排队网模型并分析其性能；提出单元资源协同作业约束优化配置问题的分解迭代优化算法；针对分解迭代算法的收敛性和最优等价性进行分析。特色与创新之处体现在：扩展了有限缓冲区容量开排队网模型的适用范围，使之能够描述资源协同作业约束的随机模型；提出了一种迭代求解制造单元资源协同作业约束优化配置问题的分支定界方法并对其进行了理论分析。研究成果将为定制型制造企业，在扩大现有生产能力或建立新工厂时，提供科学的决策方法和分析手段，优化投资效益。

针对考虑含有自动装卸机器人柔性制造单元的随机生产系统具有的需求与工时的不确定性、资源协同作业约束等特性，本项目研究其资源的优化配置方法，即在订单随机到达的情况下，配置各类制造资源的数量，使得生产系统以最小的投资满足产品的平均产出率和平均生产周期约束。具体包括：建立具有自动装卸工件机器人的制造单元资源协同作业约束排队网模型并分析其性能；提出单元资源协同作业约束优化配置问题的分解迭代优化算法；针对分解迭代算法的收敛性和最优等价性进行分析。特色与创新之处体现在：扩展了有限缓冲区容量开排队网模型的适用范围，使之能够描述资源协同作业约束的随机模型；提出了一种迭代求解制造单元资源协同作业约束优化配置问题的分支定界方法并对其进行了理论分析。研究成果将为定制型制造企业，在扩大现有生产能力或建立新工厂时，提供科学的决策方法和分析手段，优化投资效益。