摘要
冲压制造离散性强、工艺复杂、能量损耗较大,为实现冲压制造过程的节能和高效运行,在保证最大完工时间受影响较小的前提下降低能耗,以冲压车间为对象进行了节能调度研究。建立面向冲压车间的多目标节能调度模型,采用多目标优化算法进行求解,得到Pareto解集。提出基于产品制造过程内含能分级的方案评价与选择方法,计算出不同调度方案下各产品的制造过程内含能并进行分级处理,选择出产品制造过程内含能较小的调度方案作为最优执行方案,提高了节能调度的可行性。最后,应用某冲压车间生产实例验证了节能调度模型和基于产品制造过程内含能分级的方案评价与选择方法的可靠性,与原始调度方案相比,车间总能耗与最大完工时间均实现了降低。
Stamping production composed by discrete flow and complicated processes consumes a great amount of energy. In order to realize energy-saving and efficient operation during stamping manufacturing, and reduce energy consumption while ensuring that the maximum completion time is less affected, an energy-saving scheduling for a stamping workshop has been conducted. The energy-saving scheduling model for the workshop is established and has been solved with a multi-objective optimization algorithm,and the Pareto solution set is obtained. Moreover, a method for evaluation and solution selection based on ranks of product embodied energy during manufacturing has been proposed. The embodied energy of each product during manufacturing under different schedules is calculated and ranked so that a schedule with smaller embodied energy of products is selected. As a result, the feasibility of energy-saving scheduling is enhanced. A case study of a stamping workshop is given to verify the reliability of the energy-saving scheduling model as well as the proposed method for solution evaluation and selection. The results show that the total energy consumption and the makespan in the workshop are both reduced compared with the original schedule.
作者
熊玮
黄海鸿
朱利斌
刘志峰
XIONG Wei;HUANG Haihong;ZHULibin;LIU Zhifeng(Key Laboratory of Green Design and Manufacturing of Mechanical Industry,Hefei University of Technology,Hefei 230009;School of Mechanical Engineering,Hefei University of Technology,Hefei 230009)
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2019年第10期217-225,共9页
Journal of Mechanical Engineering
基金
优秀青年科学基金(51722502)
国家自然科学基金国际(地区)合作与交流(51561125002)资助项目
关键词
冲压车间
节能调度
多目标优化
制造过程内含能
分级优选
stamping workshop
energy-saving scheduling
multi-objective optimization
embodied energy during manufacturing
optimal selection based on ranks