Energy Footprint Modeling and Parameter Optimization in Workshop Manufacturing Processes

doi:10.3969/j.issn.1004-132X.2022.21.004

Abstract

Abstract: To reduce the energy consumption during the parts manufacturing processes， an energy-saving focused multi-equipment machining parameter collaborative optimization method was proposed. Taking the workshop manufacturing processes with machines and robots as target， the energy footprint models considering cutting tool degradation processes were setup for the workshop system. Considering the cost index function of tool life and stability of robotic transportation， a multi-objective collaborative optimization model of machining parameters with multi-equipment systems was established. Taking the processing time as constraint， the artificial bee colony algorithm was used to obtain the global optimal parameters. Experimental results show that the optimized parameters may reduce the energy consumption of CNC machines by 17.97%， and reduce the energy consumption of the robotic transportation by 18.13%.

Key words: workshop manufacturing process, energy footprint, multi-objective optimization, tool life

摘要： 为降低零件加工过程的生产能耗，提出一种面向节能的车间生产过程多装备加工参数协同优化方法。以包含机床与机器人的定制化生产车间为研究对象，建立了考虑刀具退化动态过程的生产车间系统能量足迹模型。考虑刀具寿命、机器人运输平稳性的成本指标函数，建立了多装备系统的加工参数协同多目标优化模型。以加工时间为约束条件，使用蜂群算法获取了最优参数。实验表明，以节能目标为主的优化方案可降低机床加工能耗17.97%，降低机器人运输能耗18.13%。

关键词: 车间生产过程, 能量足迹, 多目标优化, 刀具寿命

CLC Number:

TH18

TIAN Ying, SHAO Wenting, WANG Taiyong. Energy Footprint Modeling and Parameter Optimization in Workshop Manufacturing Processes[J]. China Mechanical Engineering, 2022, 33(21): 2547-2553.

田颖, 邵文婷, 王太勇. 车间生产过程的能量足迹建模与加工参数协同优化[J]. 中国机械工程, 2022, 33(21): 2547-2553.

References

［1］曹华军，王坤，陈二恒，等. 未来绿色工厂［J］. 航空制造技术， 2018（12）：30-36.
CAO Huajun， WANG Kun， CHEN Erheng， et al. Green Factory of Future［J］. Aeronautical Manufacturing Technology， 2018（12）：30-36.
［2］王超，刘飞，庹军波. 一种数控切削机床运行能耗状态在线判别方法［J］. 中国机械工程， 2017， 28（13）：1620-1627.
WANG Chao， LIU Fei， TUO Junbo. A Method for On-line Differentiating Operations and Energy Consumption States of CNC Machines［J］. China Mechanical Engineering， 2017， 28（13）：1620-1627.
［3］PARK J， LAW K H， BHINGE R， et al. A Generalized Data-driven Energy Prediction Model with Uncertainty for a Milling Machine Tool Using Gaussian Process［C］∥10th ASME International Manufacturing Science and Engineering Conference（MSEC2015）. Charlotte， 2015：V002T05A010.
［4］ZHOU L R， LI J F， LI F Y， et al. Energy Consumption Model and Energy Efficiency of Machine Tools：a Comprehensive Literature Review［J］. Journal of Cleaner Production， 2016（112）：3721-3734.
［5］MOHAMMED A， SCHMIDT B， WANG Lihui， et al. Minimizing Energy Consumption for Robot Arm Movement［J］. Procedia CIRP， 2014（25）：400-405.
［6］PARYANTO， BROSSOG M， KOHL J， et al. Energy Consumption and Dynamic Behavior Analysis of a Six-axis Industrial Robot in an Assembly System［J］. Procedia CIRP， 2014（23）：131-136.
［7］黄拯滔，杨杰，张超勇，等. 面向能耗的数控铣削过程建模与参数优化［J］. 中国机械工程， 2016，27（18）：2524-2532.
HUANG Zhengtao， YANG Jie， ZHANG Chaoyong， et al. Energy-oriented CNC Milling Process Modelling and Parameter Optimization［J］. China Mechanical Engineering， 2016，27（18）：2524-2532.
［8］陈行政，李聪波，李丽，等. 面向能效的多工步数控铣削工艺参数多目标优化模型［J］. 计算机集成制造系统， 2016， 22（2）：538-546.
CHEN Xingzheng， LI Congbo， LI Li， et al. Multi-objective Parameter Optimization Model of Multi-pass CNC Milling for Energy Efficiency［J］. Computer Integrated Manufacturing System， 2016， 22（2）：538-546.
［9］XU L， HUANG C， LI C， et al. A Novel Intelligent Reasoning System to Estimate Energy Consumption and Optimize Cutting Parameters toward Sustainable Machining［J］. Journal of Cleaner Production， 2020， 261：121160.
［10］ZHANG J Q， LIU Q， XU W J， et al. Cross-layer Optimization Model toward Service-oriented Robotic Manufacturing Systems［J］. Journal of Manufacturing Science and Engineering， 2018， 140（4）：041002.
［11］SOBOTTKA T， KAMHUBER F， RSSLER M， et al. Hybrid Simulation-based Optimization of Discrete Parts Manufacturing to Increase Energy Efficiency and Productivity［C］∥15th Global Conference on Sustainable Manufacturing（GCSM）. Haifa， 2018：413-420.
［12］TIAN Y， ZHANG L， WANG T Y， et al. Energy Footprint Mapping Analysis-based Energy Saving Product Design Study［J］. Key Engineering Materials， 2016（693）：1966-1970.

[1]	LI Meng-Lei, GU Yo-Qin, ZHANG Hua-Liang, LIU Li-Qin, DU Juan, WEN Chu-Hua, LAN Guo-Sheng. Parallel Mechanism Structure Optimization Design Based on Multi-objective Differential Evolution Algorithm [J]. J4, 201016, 21(16): 1915-1920.
[2]	HU Fuqing, SUN Jianghong, SUN Yingjie, SUN Yutong, MA Chao, ZHOU Fuqiang, . Design and Parameter Optimization of Slicing Machines Based on New Rotary-straight Line Reciprocating Mechanisms [J]. China Mechanical Engineering, 2024, 35(04): 614-623，635.
[3]	WEI Shupeng, TANG Hongtao, LI Xixing, YANG Guanyu, ZHANG Jian. Dual-resource Constrained Flexible Machining Workshop Inverse Scheduling Problem [J]. China Mechanical Engineering, 2024, 35(03): 457-471.
[4]	LIU Yi, YI Wangmin, YAO Jiantao, WANG Xingda, YU Peng, ZHAO Yongshen. Design and Research of Heavy-duty Posture-adjusting Assembly Robots in Narrow Space [J]. China Mechanical Engineering, 2024, 35(02): 324-336.
[5]	QU Ligang, SU Yan, XIN Yufei. Automatic Layout Method of Aircraft Tank Pipelines Based on SHO-NSGA Hybrid Algorithm [J]. China Mechanical Engineering, 2023, 34(15): 1864-1872.
[6]	ZHANG Weicun, GU Hongyu. Job-shop Scheduling Problems Considering Similar Learning Effect in One-worker and Multiple-machine Partterns [J]. China Mechanical Engineering, 2023, 34(14): 1701-1709.
[7]	PENG Xiang, JIANG Haohao, GUO Yuliang, LI Jiquan, YI Bing, JIANG Shaofei, . Collaborative Optimization of Stacking Sequence and Material Distribution for Wing Skins [J]. China Mechanical Engineering, 2023, 34(12): 1415-1424,1435.
[8]	CHEN Xiren, YE Wenhua, ZHANG Chaohong, CUI Kunkun, LENG Sheng, YE Liukang. NURBS Curve-based Multi-objective Aerodynamic Optimization Design for Ultra-high-speed Elevator Fairings [J]. China Mechanical Engineering, 2023, 34(12): 1436-1445,1464.
[9]	WANG Qiulian, DUAN Xinghao. Scheduling of Flexible Job Shop Based on High-dimension and Multi-objective Migrating Bird Optimization Algorithm [J]. China Mechanical Engineering, 2022, 33(21): 2601-2612.
[10]	BAO Hong, YANG Jing, KE Qingdi, LI Hongzhen, YAO Yongzheng, . An Energy Efficiency Optimization Model of Fused Filament Fabrication 3D Printing Based on Support Vector Regression [J]. China Mechanical Engineering, 2022, 33(18): 2215-2226.
[11]	RONG Yu, DOU Tianci, ZHANG Xingchao, ZHANG LeiZ, HAO Jingyu. A Real-time Control Method for Optimal Overall Performances of Planar Redundant Robots [J]. China Mechanical Engineering, 2022, 33(16): 1928-1939.
[12]	LI Hao, XU Zhiling, XU Yong, ZHAO Youwei. Grouping Selective Assembly Method for Mechanical Products Based on Local Search Strategy for NSGA-Ⅱ [J]. China Mechanical Engineering, 2022, 33(09): 1127-1133.
[13]	SHANG Zuen, ZHAO Lijuan, LIU Xionghao, JIN Xin. Deployable Waterbomb Wheel Structure Analysis and Optimization of Mine Rescue Robots [J]. China Mechanical Engineering, 2021, 32(24): 2924-2933.
[14]	WU Xing, ZHAI Jingjing, LOU Peihuang, HU Ya, XIAO Haining. Deadlock-free Task Scheduling with Task Traveling Time for a Multi-load AGV System [J]. China Mechanical Engineering, 2021, 32(23): 2840-2849.
[15]	DONG Chenglin, LIU Haitao, YANG Junhao. Dimensional Synthesis of a Novel Asymmetric 5-DOF Hybrid Robot [J]. China Mechanical Engineering, 2021, 32(20): 2418-2426.