面向绿色制造的半组合式船用曲轴结构件生产车间多目标调度优化

Green manufacturing-oriented multi-objective scheduling optimization for half built-up marine crank shaft component workshop

针对半组合式船用曲轴结构件规格多、批量小、体积质量大、加工精度高、生产能耗大、交货期要求严等特点,以最大完工时间最小、机器加工能耗最小、桥式起重机运输能耗最小为优化目标,研究了该类型曲轴结构件生产车间的绿色调度优化方法。将结构件制造过程细化为准备、装夹、加工、卸夹4个工艺流程,建立了集成桥式起重运输设备与机器加工设备的双资源约束、多目标优化调度数学模型;基于快速非支配排序遗传算法,提出了融合运输信息与机器信息的五段式编码,通过在算法流程中融入两种启发式选择策略对每次迭代结果进行二次优化,从而改进整个制造流程;最后,将所提模型与算法应用于上海某船用曲轴公司结构件生产车间,并与不考虑运输状态的单资源机器约束数学模型优化结果进行了对比分析,验证了所提模型与算法的有效性。

Aiming at the characteristics of half build-up marine crankshaft structure such as many specifications,small batch,large volume and mass,high processing precision,large production energy consumption and strict delivery time requirements,the green scheduling optimization method for the production workshop of this type of crankshaft structure was studied with the minimum maximum completion time,minimum machine processing energy consumption and minimum overhead traveling crane energy consumption as the optimization objectives.The manufacturing process of structural parts was divided into four technological processes of preparation,clamping,processing and unloading,and a mathematical model of double-resource constraint and multi-objective optimal scheduling for integrated bridge crane transportation equipment and machine processing equipment was established.Based on the fast and elitist multi-objective genetic algorithm,a five-segment coding method combining transportation information and machine information was proposed.Two heuristic selection strategies were incorporated into the algorithm flow to optimize the each iteration results secondarily,thus the whole manufacturing flow was improved.The proposed model and algorithm were applied to the structural parts production workshop of a marine crankshaft company in Shanghai,and compared with the optimization results of the single-resource machine constraint mathematical model without considering the transportation state,which verified the effectiveness of the proposed model and algorithm.