基于Plant Simulation的混合流水线作业序列优化
Optimization of Hybrid Assembly Line Job Sequencing Based on Plant Simulation

为了完成某公司的智能制造转型计划，对该公司车间的生产流程、生产布局以及产品的生产工艺进行了调研，根据该车间的生产特点，将其归类为混合流水线车间调度(HFSP)这一典型的NP-hard问题。以最短作业时间(SPT)调度为优化目标，使用遗传算法去解决这一问题。具体方法上使用Plant Sim-ulation仿真软件，结合现场生产实际情况，搭建起车间流水线生产模型，应用遗传算法实现最优排序，得到近似最优解。经过遗传算法计算后的生产作业序列，理论上按此指导进行生产，总的作业时间可以缩短15%左右，从而提高企业生产效率；另外，厂家只需要导入即将执行的产品数量及工艺信息到模型，经过模型计算即可获得推荐排序。因此，此方式具有一定的实际应用价值和指导意义。
In order to complete the intelligent manufacturing transformation plan of a company, the production process, production layout and product production process of the company’s workshop were investigated. According to the production characteristics of the workshop, it was classified as a typ-ical NP-hard problem of hybrid flow shop scheduling (HFSP). The shortest operation time (SPT) scheduling is taken as the optimization goal, and genetic algorithm is used to solve this problem. In the specific method, Plant Simulation software was used to build the production model of the workshop assembly line combined with the actual situation of the field production, and the genetic algorithm was used to achieve the optimal sequencing, and the approximate optimal solution was obtained. After the genetic algorithm calculation of the production sequence, theoretically according to this guidance for production, the total operation time can be shortened by about 15%, so as to improve the production efficiency of enterprises; In addition, the manufacturer only needs to import the product quantity and process information to be executed into the model, and the recommended ranking can be obtained after the model calculation. Therefore, this method has certain practical application value and guiding significance.