考虑AGV运输和机器转速的作业车间绿色调度研究

Green scheduling of job shop considering AGV transportation and machine speed

在车间实际生产中,机器在加工状态和空载状态下都需要消耗能量,且机器在不同转速下的能耗也不同。此外,随着自动导引车(AGV)在车间的广泛应用,其能耗也不可忽略,因此对考虑AGV和机器转速的作业车间绿色调度问题进行研究具有重要意义。完工时间不仅被认为是表示车间生产效率的指标,而且在一定程度上意味着机器空载能耗的减少、机器利用率的提高。为此,对考虑AGV运输和机器转速的作业车间完工时间和能耗优化问题进行了研究。首先,对作业车间机器的能耗、AGV能耗进行了分析,探讨了AGV、工件和机器之间的工艺约束,建立了考虑AGV运输和机器转速的作业车间绿色调度模型;然后,采用两阶段优化的方式分别对完工时间和车间总能耗进行了优化,在第一阶段,机器以最高转速进行了加工,采用改进麻雀搜索算法对其最大完工时间进行了优化;在第二阶段,在保证第一阶段优化得到的完工时间最小值不变的前提下,提出了一种间隙档位调整策略,通过降低部分工序的机器转速来降低车间能源消耗,实现对车间总能耗的优化;最后,采用标准用例对算法进行了仿真实验。研究结果表明:在第一阶段采用改进麻雀搜索算法,提高了种群质量,加快了算法的收敛速度,算法具有较强的跳出局部最优能力;第二阶段在保证完工时间的基础上,采取间隙档位调整策略来降低能耗,通过10个用例测试表明能耗可减少1.13%~5.18%。该结果验证了考虑AGV和机器转速绿色调度模型的正确性以及改进麻雀算法的有效性。

In actual production in the workshop,energy of machine will be consumed not only in the processing state,but also in the no-load state,and the energy consumption of machines will vary at different processing speed.In addition,with the wide application of automated guided vehicle(AGV)in workshops,its energy consumption can not be ignored,therefore the research on green scheduling of job shops considering AGV and machine speed is of great significance.Makespan is not only regarded as the efficiency indicator of workshop production,but also,to a certain extent,means the reduction indicator of machine energy consumption in no-load state and the improvement indicator of machine utilization.Based on this,the makespan and energy consumption optimization problem of the job shop considering AGV transportation and machine speed was studied.Firstly,the machine energy consumption and AGV energy consumption of job shop were analyzed,and the process constraints among AGV,job and machine were explored.And the green job shop scheduling model considering AGV transportation and machine speed was established.Then,the two-stage optimization method was adopted to optimize makespan and energy consumption of job shop.In the first stage,the machine processed at the highest speed and used an improved sparrow search algorithm to optimize makespan;in the second stage,while the makespan optimized in the first stage remained unchanged,the gap gear adjustment strategy was proposed to reduce energy consumption in job shop by reducing the machine speed of some processes to achieve optimization of the total energy consumption in job shop.Finally,the algorithms were simulated and verified using standard use cases through simulation.The experimental results show that in the first stage,the improved sparrow search algorithm can improve the quality of the population,accelerate the convergence speed of the algorithm,jump out of the local optimal solution,and obtain better makespan.In the second stage,on the basis of above makespan,the gap adjustment strategy is adopted to reduce the energy consumption,and the energy consumption can be reduced by 1.13%~5.18%through 10 use cases.The results verify the correctness of the green scheduling model considering AGV and machine speed and the effectiveness of the improved sparrow algorithm.