复杂产品人工智能生产调度研究  

Research on the Artificial Intelligence Production Scheduling of Complex Products

作　　者：余阿东[1] YU A-dong(School of Automotive and Electrical Engineering,Xinyang Vocational and Technical College,He’nan Xinyang 464000,China)

机构地区：[1]信阳职业技术学院汽车与机电工程学院,河南信阳464000

出　　处：《机械设计与制造》2024年第7期26-30,共5页Machinery Design & Manufacture

基　　金：河南省哲学社会科学规划项目(2021BJJ082)。

摘　　要：针对复杂产品生产调度协同性不足问题,提出一种基于关键链的多产品人工智能生产调度模式。结合复杂产品时序约束特点,以最小产品拖期和在制品库存为优化目标,搭建了基于关键链的多产品项目人工智能生产调度优化模型,基于遗传算法与模拟退火算法,设计了遗传退火算法(GA-SA)对多产品项目人工智能生产调度优化模型求解,并以某重型机械企业生产的矿渣立磨为例验证了优化模型和智能算法的有效性,实现了复杂产品生产调度精益性和智能性目标,研究结果表明:采用GA-SA+关键链调度方法,产品可以做到准时交付且在制品库存减少24%。Aiming at the lack of the coordination in the complex products production scheduling,this paper proposes a multiproduct artificial intelligence production scheduling model based on critical chain.Combined with the characteristics of the complex product timing constraints and taking the minimum product delay and WIP inventory as the optimization objectives,an artificial intelligence production scheduling optimization model of multiproduct project based on critical chain is established.Combining genetic algorithm with simulated annealing algorithm,genetic annealing algorithm(GA-SA)is designed to solve the model.Taking the slag vertical mill produced by a heavy machinery enterprise as an example,the effectiveness of the optimization model and intelligent algorithm is verified,and the goal of lean and intelligent production scheduling of complex products is realized.The research results show that:when the GA-SA+critical chain scheduling method is adopted,the products can be delivered on time and WIP inventory can be reduced by 24%.

关 键 词：关键链 复杂产品 生产调度 遗传退火算法 人工智能 

分 类 号：TH16[机械工程—机械制造及自动化]